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提交 755bd88a authored 作者: Thomas Mueller's avatar Thomas Mueller
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h2/build.bat
浏览文件 @ 755bd88a
......@@ -4,4 +4,4 @@ if exist bin/org/h2/build/Build.class goto buildOK
if not exist bin mkdir bin
javac -sourcepath src/tools -d bin src/tools/org/h2/build/*.java
:buildOK
java -Xmx512m -cp "bin;%JAVA_HOME%/lib/tools.jar;temp" org.h2.build.Build %*
\ No newline at end of file
"%JAVA_HOME%/bin/java" -Xmx512m -cp "bin;%JAVA_HOME%/lib/tools.jar;temp" org.h2.build.Build %*
\ No newline at end of file
h2/build.sh
浏览文件 @ 755bd88a
......@@ -8,4 +8,4 @@ if [ ! -f "bin/org/h2/build/Build.class" ] ; then
fi
javac -sourcepath src/tools -d bin src/tools/org/h2/build/*.java
fi
java -Xmx512m -cp "bin:$JAVA_HOME/lib/tools.jar:temp" org.h2.build.Build $@
"$JAVA_HOME/bin/java" -Xmx512m -cp "bin:$JAVA_HOME/lib/tools.jar:temp" org.h2.build.Build $@
h2/src/docsrc/html/changelog.html
浏览文件 @ 755bd88a
......@@ -16,7 +16,9 @@ Change Log
<h1>Change Log</h1>
<h2>Next Version (unreleased)</h2>
<ul><li>NOT IN(SELECT ...) was incorrect if the subquery returns no rows.
<ul><li>Timestamp columns such as TIMESTAMP(6) were not compatible to other database.
</li><li>Opening a large database was slow if there was a problem opening the previous time.
</li><li>NOT IN(SELECT ...) was incorrect if the subquery returns no rows.
</li><li>CREATE TABLE AS SELECT did not work correctly in the multi-version concurrency mode.
</li><li>Support a comma before closing a list, as in: create table test(id int,)
</li><li>MySQL compatibility: linked tables had lower case column names on some systems.
......
h2/src/docsrc/html/faq.html
浏览文件 @ 755bd88a
......@@ -111,6 +111,10 @@ Every CLOB or BLOB can be up to 256 GB as well. The size limit of the index data
The maximum file size for FAT or FAT32 file systems is 4 GB. So if you use FAT or FAT32, the
limit is 4 GB for the data.
</p>
<p>
The larger the database, the more main memory is required. Currently the mininum main memory required for a 12 GB database
is around 240 MB.
</p>
<br /><a name="reliable"></a>
<h3>Is it Reliable?</h3>
......
h2/src/docsrc/html/jaqu.html
浏览文件 @ 755bd88a
......@@ -252,7 +252,8 @@ Unlike when using annotations, the compiler can check the syntax even for multi-
objects (multi-column indexes, multi-column primary keys and so on).
This solution is very flexible because the definition is written in regular Java code:
Unlike when using annotations, your code can select the right configuration depending
on the environment if required.
on the environment if required. Unlike XML mapping configuration, the configuration
is integrated in the class itself.
</p>
<h2>Ideas</h2>
......
h2/src/docsrc/html/performance.html
浏览文件 @ 755bd88a
......@@ -20,6 +20,8 @@ Performance
PolePosition Benchmark</a><br />
<a href="#application_profiling">
Application Profiling</a><br />
<a href="#database_profiling">
Database Profiling</a><br />
<a href="#database_performance_tuning">
Performance Tuning</a><br />
......@@ -290,10 +292,60 @@ Premature or 'blind' optimization should be avoided, as it is not an efficient w
There are various ways to analyze the application. In some situations it is possible to
compare two implementations and use System.currentTimeMillis() to find out which one is faster.
But this does not work for complex applications with many modules, and for memory problems.
</p>
<p>
A very good tool to measure both the memory and the CPU is the
<a href="http://www.yourkit.com">YourKit Java Profiler</a>. This tool is also used
to optimize the performance and memory footprint of this database engine.
</p>
<p>
A simple way to profile an application is to use the built-in profiling tool of java. Example:
</p>
<pre>
java -Xrunhprof:cpu=samples,depth=16 com.acme.Test
</pre>
<p>
Unfortunately, it is only possible to profile the application from start to end.
</p>
<br /><a name="database_profiling"></a>
<h2>Database Profiling</h2>
<p>
The ConvertTraceFile tool generates SQL statement statistics at the end of the SQL script file.
The format used is similar to the profiling data generated when using java -Xrunhprof.
As an example, execute the the following script using the H2 Console:
</p>
<pre>
SET TRACE_LEVEL_FILE 3;
DROP TABLE IF EXISTS TEST;
CREATE TABLE TEST(ID INT PRIMARY KEY, NAME VARCHAR(255));
@LOOP 1000 INSERT INTO TEST VALUES(?, ?);
SET TRACE_LEVEL_FILE 0;
</pre>
<p>
Now convert the .trace.db file using the ConvertTraceFile tool:
</p>
<pre>
java -cp h2.jar org.h2.tools.ConvertTraceFile
-traceFile "~/test.trace.db" -script "~/test.sql"
</pre>
<p>
The generated file <code>test.sql</code> will contain the SQL statements as well as the
following profiling data (results vary):
</p>
<pre>
-----------------------------------------
-- SQL Statement Statistics
-- time: total time in milliseconds (accumulated)
-- count: how many times the statement ran
-- result: total update count or row count
-----------------------------------------
-- self accu time count result sql
-- 62% 62% 158 1000 1000 INSERT INTO TEST VALUES(?, ?);
-- 37% 100% 93 1 0 CREATE TABLE TEST(ID INT PRIMARY KEY, NAME VARCHAR(255));
-- 0% 100% 0 1 0 DROP TABLE IF EXISTS TEST;
-- 0% 100% 0 1 0 SET TRACE_LEVEL_FILE 3;
</pre>
<br /><a name="database_performance_tuning"></a>
<h2>Database Performance Tuning</h2>
......
h2/src/docsrc/html/roadmap.html
浏览文件 @ 755bd88a
......@@ -248,7 +248,6 @@ Of course, patches are always welcome, but are not always applied as is. Patches
</li><li>Support multiple directories (on different hard drives) for the same database
</li><li>Server protocol: use challenge response authentication, but client sends hash(user+password) encrypted with response
</li><li>Support EXEC[UTE] (doesn't return a result set, compatible to MS SQL Server)
</li><li>GROUP BY and DISTINCT: support large groups (buffer to disk), do not keep large sets in memory
</li><li>Support native XML data type
</li><li>Support triggers with a string property or option: SpringTrigger, OSGITrigger
</li><li>Clustering: adding a node should be very fast and without interrupting clients (very short lock)
......
h2/src/docsrc/html/tutorial.html
浏览文件 @ 755bd88a
......@@ -391,6 +391,30 @@ add the following snippet to your web.xml file (after context-param and before f
<p>
For details on how to access the database, see the code DbStarter.java
</p>
<p>
By default the DbStarter listener opens a connection using the database URL jdbc:h2:~/test
and user name and password 'sa'. It can also start the TCP server, however this is disabled by default.
To enable it, use the db.tcpServer parameter in web.xml. Here is the complete list of options.
These options are set just after the display-name and description tag, but before any listener and filter tags:
</p>
<pre>
&lt;context-param>
&lt;param-name>db.url&lt;/param-name>
&lt;param-value>jdbc:h2:~/test&lt;/param-value>
&lt;/context-param>
&lt;context-param>
&lt;param-name>db.user&lt;/param-name>
&lt;param-value>sa&lt;/param-value>
&lt;/context-param>
&lt;context-param>
&lt;param-name>db.password&lt;/param-name>
&lt;param-value>sa&lt;/param-value>
&lt;/context-param>
&lt;context-param>
&lt;param-name>db.tcpServer&lt;/param-name>
&lt;param-value>-tcpAllowOthers&lt;/param-value>
&lt;/context-param>
</pre>
<br /><a name="csv"></a>
<h2>CSV (Comma Separated Values) Support</h2>
......
h2/src/docsrc/text/_docs_en.utf8.txt
浏览文件 @ 755bd88a
......@@ -4250,7 +4250,7 @@ JaQu
What is JaQu
@jaqu_1002_p
JaQu stands for Java Query and allows to access databases using pure Java. JaQu replaces SQL, JDBC, and O/R frameworks such as Hibernate. JaQu is something like LINQ for Java (LINQ stands for "language integrated query" and is a Microsoft .NET technology). The following JaQu code:
JaQu stands for Java Query and allows to access databases using pure Java. JaQu provides a fluent interface (or internal DSL) for building SQL statements. JaQu replaces SQL, JDBC, and O/R frameworks such as Hibernate. JaQu is something like LINQ for Java (LINQ stands for "language integrated query" and is a Microsoft .NET technology). The following JaQu code:
@jaqu_1003_p
stands for the SQL statement:
......@@ -4292,54 +4292,60 @@ src/test/org/h2/test/jaqu/* (samples and tests)
src/tools/org/h2/jaqu/* (framework)
@jaqu_1016_h2
Requirements
Building the JaQu library
@jaqu_1017_p
JaQu requires Java 1.5. Annotations are not need. Currently, JaQu is only tested with the H2 database engine, however in theory it should work with any database that supports the JDBC API.
To create the JaQu jar file, run: <code>build jarJaqu</code> . This will create the file <code>bin/h2jaqu.jar</code> .
@jaqu_1018_h2
Requirements
@jaqu_1019_p
JaQu requires Java 1.5. Annotations are not need. Currently, JaQu is only tested with the H2 database engine, however in theory it should work with any database that supports the JDBC API.
@jaqu_1020_h2
Example Code
@jaqu_1019_h2
@jaqu_1021_h2
Configuration
@jaqu_1020_p
@jaqu_1022_p
JaQu does not require any kind of configuration is you want to use the default mapping. To define table indices, or if you want to map a class to a table with a different name, or a field to a column with another name, create a function called 'define' in the data class. Example:
@jaqu_1021_p
@jaqu_1023_p
The method 'define()' contains the mapping definition. It is called once when the class is used for the first time. Like annotations, the mapping is defined in the class itself. Unlike when using annotations, the compiler can check the syntax even for multi-column objects (multi-column indexes, multi-column primary keys and so on). This solution is very flexible because the definition is written in regular Java code: Unlike when using annotations, your code can select the right configuration depending on the environment if required.
@jaqu_1022_h2
@jaqu_1024_h2
Ideas
@jaqu_1023_p
@jaqu_1025_p
This project has just been started, and nothing is fixed yet. Some ideas for what to implement include:
@jaqu_1024_li
@jaqu_1026_li
Provide API level compatibility with JPA (so that JaQu can be used as an extension of JPA).
@jaqu_1025_li
@jaqu_1027_li
Internally use a JPA implementation (for example Hibernate) instead of SQL directly.
@jaqu_1026_li
@jaqu_1028_li
Use PreparedStatements and cache them.
@jaqu_1027_h2
@jaqu_1029_h2
Related Projects
@jaqu_1028_a
@jaqu_1030_a
JEQUEL: Java Embedded QUEry Language
@jaqu_1029_a
@jaqu_1031_a
Quaere
@jaqu_1030_a
@jaqu_1032_a
Quaere (Alias implementation)
@jaqu_1031_a
@jaqu_1033_a
JoSQL
@jaqu_1032_a
@jaqu_1034_a
Google Group about adding LINQ features to Java
@license_1000_h1
......@@ -5420,265 +5426,265 @@ PolePosition Benchmark
Application Profiling
@performance_1004_a
Database Profiling
@performance_1005_a
Performance Tuning
@performance_1005_h2
@performance_1006_h2
Performance Comparison
@performance_1006_p
@performance_1007_p
In most cases H2 is a lot faster than all other (open source and not open source) database engines. Please note this is mostly a single connection benchmark run on one computer.
@performance_1007_h3
@performance_1008_h3
Embedded
@performance_1008_th
@performance_1009_th
Test Case
@performance_1009_th
@performance_1010_th
Unit
@performance_1010_th
@performance_1011_th
H2
@performance_1011_th
@performance_1012_th
HSQLDB
@performance_1012_th
@performance_1013_th
Derby
@performance_1013_td
Simple: Init
@performance_1014_td
ms
Simple: Init
@performance_1015_td
719
ms
@performance_1016_td
1344
719
@performance_1017_td
2906
1344
@performance_1018_td
Simple: Query (random)
2906
@performance_1019_td
ms
Simple: Query (random)
@performance_1020_td
328
ms
@performance_1021_td
328
@performance_1022_td
1578
328
@performance_1023_td
Simple: Query (sequential)
1578
@performance_1024_td
ms
Simple: Query (sequential)
@performance_1025_td
250
ms
@performance_1026_td
250
@performance_1027_td
1484
250
@performance_1028_td
Simple: Update (random)
1484
@performance_1029_td
ms
Simple: Update (random)
@performance_1030_td
688
ms
@performance_1031_td
1828
688
@performance_1032_td
14922
1828
@performance_1033_td
Simple: Delete (sequential)
14922
@performance_1034_td
ms
Simple: Delete (sequential)
@performance_1035_td
203
ms
@performance_1036_td
265
203
@performance_1037_td
10235
265
@performance_1038_td
Simple: Memory Usage
10235
@performance_1039_td
MB
Simple: Memory Usage
@performance_1040_td
6
MB
@performance_1041_td
9
6
@performance_1042_td
11
9
@performance_1043_td
BenchA: Init
11
@performance_1044_td
ms
BenchA: Init
@performance_1045_td
422
ms
@performance_1046_td
672
422
@performance_1047_td
4328
672
@performance_1048_td
BenchA: Transactions
4328
@performance_1049_td
ms
BenchA: Transactions
@performance_1050_td
6969
ms
@performance_1051_td
3531
6969
@performance_1052_td
16719
3531
@performance_1053_td
BenchA: Memory Usage
16719
@performance_1054_td
MB
BenchA: Memory Usage
@performance_1055_td
10
MB
@performance_1056_td
10
@performance_1057_td
9
10
@performance_1058_td
BenchB: Init
9
@performance_1059_td
ms
BenchB: Init
@performance_1060_td
1703
ms
@performance_1061_td
3937
1703
@performance_1062_td
13844
3937
@performance_1063_td
BenchB: Transactions
13844
@performance_1064_td
ms
BenchB: Transactions
@performance_1065_td
2360
ms
@performance_1066_td
1328
2360
@performance_1067_td
5797
1328
@performance_1068_td
BenchB: Memory Usage
5797
@performance_1069_td
MB
BenchB: Memory Usage
@performance_1070_td
8
MB
@performance_1071_td
9
8
@performance_1072_td
8
9
@performance_1073_td
BenchC: Init
8
@performance_1074_td
ms
BenchC: Init
@performance_1075_td
718
ms
@performance_1076_td
468
718
@performance_1077_td
5328
468
@performance_1078_td
BenchC: Transactions
5328
@performance_1079_td
ms
BenchC: Transactions
@performance_1080_td
2688
ms
@performance_1081_td
60828
2688
@performance_1082_td
7109
60828
@performance_1083_td
BenchC: Memory Usage
7109
@performance_1084_td
MB
BenchC: Memory Usage
@performance_1085_td
10
MB
@performance_1086_td
14
10
@performance_1087_td
9
14
@performance_1088_td
Executed Statements
9
@performance_1089_td
#
Executed Statements
@performance_1090_td
594255
#
@performance_1091_td
594255
......@@ -5687,382 +5693,382 @@ Executed Statements
594255
@performance_1093_td
Total Time
594255
@performance_1094_td
ms
Total Time
@performance_1095_td
17048
ms
@performance_1096_td
74779
17048
@performance_1097_td
84250
74779
@performance_1098_td
Statement per Second
84250
@performance_1099_td
#
Statement per Second
@performance_1100_td
34857
#
@performance_1101_td
7946
34857
@performance_1102_td
7946
@performance_1103_td
7053
@performance_1103_h3
@performance_1104_h3
Client-Server
@performance_1104_th
@performance_1105_th
Test Case
@performance_1105_th
@performance_1106_th
Unit
@performance_1106_th
@performance_1107_th
H2
@performance_1107_th
@performance_1108_th
HSQLDB
@performance_1108_th
@performance_1109_th
Derby
@performance_1109_th
@performance_1110_th
PostgreSQL
@performance_1110_th
@performance_1111_th
MySQL
@performance_1111_td
@performance_1112_td
Simple: Init
@performance_1112_td
@performance_1113_td
ms
@performance_1113_td
@performance_1114_td
2516
@performance_1114_td
@performance_1115_td
3109
@performance_1115_td
@performance_1116_td
7078
@performance_1116_td
@performance_1117_td
4625
@performance_1117_td
@performance_1118_td
2859
@performance_1118_td
@performance_1119_td
Simple: Query (random)
@performance_1119_td
@performance_1120_td
ms
@performance_1120_td
@performance_1121_td
2890
@performance_1121_td
@performance_1122_td
2547
@performance_1122_td
@performance_1123_td
8843
@performance_1123_td
@performance_1124_td
7703
@performance_1124_td
@performance_1125_td
3203
@performance_1125_td
@performance_1126_td
Simple: Query (sequential)
@performance_1126_td
@performance_1127_td
ms
@performance_1127_td
@performance_1128_td
2953
@performance_1128_td
@performance_1129_td
2407
@performance_1129_td
@performance_1130_td
8516
@performance_1130_td
@performance_1131_td
6953
@performance_1131_td
@performance_1132_td
3516
@performance_1132_td
@performance_1133_td
Simple: Update (random)
@performance_1133_td
@performance_1134_td
ms
@performance_1134_td
@performance_1135_td
3141
@performance_1135_td
@performance_1136_td
3671
@performance_1136_td
18125
@performance_1137_td
7797
18125
@performance_1138_td
4687
7797
@performance_1139_td
Simple: Delete (sequential)
4687
@performance_1140_td
ms
Simple: Delete (sequential)
@performance_1141_td
1000
ms
@performance_1142_td
1219
1000
@performance_1143_td
12891
1219
@performance_1144_td
3547
12891
@performance_1145_td
1938
3547
@performance_1146_td
Simple: Memory Usage
1938
@performance_1147_td
MB
Simple: Memory Usage
@performance_1148_td
6
MB
@performance_1149_td
10
6
@performance_1150_td
14
10
@performance_1151_td
0
14
@performance_1152_td
1
0
@performance_1153_td
BenchA: Init
1
@performance_1154_td
ms
BenchA: Init
@performance_1155_td
2266
ms
@performance_1156_td
2484
2266
@performance_1157_td
7797
2484
@performance_1158_td
4234
7797
@performance_1159_td
4703
4234
@performance_1160_td
BenchA: Transactions
4703
@performance_1161_td
ms
BenchA: Transactions
@performance_1162_td
11078
ms
@performance_1163_td
8875
11078
@performance_1164_td
26328
8875
@performance_1165_td
18641
26328
@performance_1166_td
11187
18641
@performance_1167_td
BenchA: Memory Usage
11187
@performance_1168_td
MB
BenchA: Memory Usage
@performance_1169_td
8
MB
@performance_1170_td
13
8
@performance_1171_td
10
13
@performance_1172_td
0
10
@performance_1173_td
1
0
@performance_1174_td
BenchB: Init
1
@performance_1175_td
ms
BenchB: Init
@performance_1176_td
8422
ms
@performance_1177_td
12531
8422
@performance_1178_td
27734
12531
@performance_1179_td
18609
27734
@performance_1180_td
12312
18609
@performance_1181_td
BenchB: Transactions
12312
@performance_1182_td
ms
BenchB: Transactions
@performance_1183_td
4125
ms
@performance_1184_td
3344
4125
@performance_1185_td
7875
3344
@performance_1186_td
7922
7875
@performance_1187_td
3266
7922
@performance_1188_td
BenchB: Memory Usage
3266
@performance_1189_td
MB
BenchB: Memory Usage
@performance_1190_td
9
MB
@performance_1191_td
10
9
@performance_1192_td
8
10
@performance_1193_td
0
8
@performance_1194_td
1
0
@performance_1195_td
BenchC: Init
1
@performance_1196_td
ms
BenchC: Init
@performance_1197_td
1781
ms
@performance_1198_td
1609
1781
@performance_1199_td
6797
1609
@performance_1200_td
2453
6797
@performance_1201_td
3328
2453
@performance_1202_td
BenchC: Transactions
3328
@performance_1203_td
ms
BenchC: Transactions
@performance_1204_td
8453
ms
@performance_1205_td
62469
8453
@performance_1206_td
19859
62469
@performance_1207_td
11516
19859
@performance_1208_td
7062
11516
@performance_1209_td
BenchC: Memory Usage
7062
@performance_1210_td
MB
BenchC: Memory Usage
@performance_1211_td
10
MB
@performance_1212_td
15
10
@performance_1213_td
9
15
@performance_1214_td
0
9
@performance_1215_td
1
0
@performance_1216_td
Executed Statements
1
@performance_1217_td
#
Executed Statements
@performance_1218_td
594255
#
@performance_1219_td
594255
......@@ -6077,543 +6083,567 @@ Executed Statements
594255
@performance_1223_td
Total Time
594255
@performance_1224_td
ms
Total Time
@performance_1225_td
48625
ms
@performance_1226_td
104265
48625
@performance_1227_td
151843
104265
@performance_1228_td
94000
151843
@performance_1229_td
58061
94000
@performance_1230_td
Statement per Second
58061
@performance_1231_td
#
Statement per Second
@performance_1232_td
12221
#
@performance_1233_td
5699
12221
@performance_1234_td
3913
5699
@performance_1235_td
6321
3913
@performance_1236_td
6321
@performance_1237_td
10235
@performance_1237_h3
@performance_1238_h3
Benchmark Results and Comments
@performance_1238_h4
@performance_1239_h4
H2
@performance_1239_p
@performance_1240_p
Version 1.0.67 (2008-02-22) was used for the test. For simpler operations, the performance of H2 is about the same as for HSQLDB. For more complex queries, the query optimizer is very important. However H2 is not very fast in every case, certain kind of queries may still be slow. One situation where is H2 is slow is large result sets, because they are buffered to disk if more than a certain number of records are returned. The advantage of buffering is, there is no limit on the result set size. The open/close time is almost fixed, because of the file locking protocol: The engine waits 20 ms after opening a database to ensure the database files are not opened by another process.
@performance_1240_h4
@performance_1241_h4
HSQLDB
@performance_1241_p
@performance_1242_p
Version 1.8.0.8 was used for the test. Cached tables are used in this test (hsqldb.default_table_type=cached), and the write delay is 1 second (SET WRITE_DELAY 1). HSQLDB is fast when using simple operations. HSQLDB is very slow in the last test (BenchC: Transactions), probably because is has a bad query optimizer. One query where HSQLDB is slow is a two-table join:
@performance_1242_p
@performance_1243_p
The PolePosition benchmark also shows that the query optimizer does not do a very good job for some queries. A disadvantage in HSQLDB is the slow startup / shutdown time (currently not listed) when using bigger databases. The reason is, a backup of the database is created whenever the database is opened or closed.
@performance_1243_h4
@performance_1244_h4
Derby
@performance_1244_p
@performance_1245_p
Version 10.3.1.4 was used for the test. Derby is clearly the slowest embedded database in this test. This seems to be a structural problem, because all operations are really slow. It will not be easy for the developers of Derby to improve the performance to a reasonable level. A few problems have been identified: Leaving autocommit on is a problem for Derby. If it is switched off during the whole test, the results are about 20% better for Derby.
@performance_1245_h4
@performance_1246_h4
PostgreSQL
@performance_1246_p
@performance_1247_p
Version 8.1.4 was used for the test. The following options where changed in postgresql.conf: fsync = off, commit_delay = 1000. PostgreSQL is run in server mode. It looks like the base performance is slower than MySQL, the reason could be the network layer. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
@performance_1247_h4
@performance_1248_h4
MySQL
@performance_1248_p
@performance_1249_p
Version 5.0.22 was used for the test. MySQL was run with the InnoDB backend. The setting innodb_flush_log_at_trx_commit (found in the my.ini file) was set to 0. Otherwise (and by default), MySQL is really slow (around 140 statements per second in this test) because it tries to flush the data to disk for each commit. For small transactions (when autocommit is on) this is really slow. But many use cases use small or relatively small transactions. Too bad this setting is not listed in the configuration wizard, and it always overwritten when using the wizard. You need to change this setting manually in the file my.ini, and then restart the service. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
@performance_1249_h4
@performance_1250_h4
Firebird
@performance_1250_p
@performance_1251_p
Firebird 1.5 (default installation) was tested, but the results are not published currently. It is possible to run the performance test with the Firebird database, and any information on how to configure Firebird for higher performance are welcome.
@performance_1251_h4
@performance_1252_h4
Why Oracle / MS SQL Server / DB2 are Not Listed
@performance_1252_p
@performance_1253_p
The license of these databases does not allow to publish benchmark results. This doesn't mean that they are fast. They are in fact quite slow, and need a lot of memory. But you will need to test this yourself. SQLite was not tested because the JDBC driver doesn't support transactions.
@performance_1253_h3
@performance_1254_h3
About this Benchmark
@performance_1254_h4
@performance_1255_h4
Number of Connections
@performance_1255_p
@performance_1256_p
This is mostly a single-connection benchmark. BenchB uses multiple connections; the other tests use one connection.
@performance_1256_h4
@performance_1257_h4
Real-World Tests
@performance_1257_p
@performance_1258_p
Good benchmarks emulate real-world use cases. This benchmark includes 3 test cases: A simple test case with one table and many small updates / deletes. BenchA is similar to the TPC-A test, but single connection / single threaded (see also: www.tpc.org). BenchB is similar to the TPC-B test, using multiple connections (one thread per connection). BenchC is similar to the TPC-C test, but single connection / single threaded.
@performance_1258_h4
@performance_1259_h4
Comparing Embedded with Server Databases
@performance_1259_p
@performance_1260_p
This is mainly a benchmark for embedded databases (where the application runs in the same virtual machine than the database engine). However MySQL and PostgreSQL are not Java databases and cannot be embedded into a Java application. For the Java databases, both embedded and server modes are tested.
@performance_1260_h4
@performance_1261_h4
Test Platform
@performance_1261_p
@performance_1262_p
This test is run on Windows XP with the virus scanner switched off. The VM used is Sun JDK 1.5.
@performance_1262_h4
@performance_1263_h4
Multiple Runs
@performance_1263_p
@performance_1264_p
When a Java benchmark is run first, the code is not fully compiled and therefore runs slower than when running multiple times. A benchmark should always run the same test multiple times and ignore the first run(s). This benchmark runs three times, but only the last run is measured.
@performance_1264_h4
@performance_1265_h4
Memory Usage
@performance_1265_p
@performance_1266_p
It is not enough to measure the time taken, the memory usage is important as well. Performance can be improved in databases by using a bigger in-memory cache, but there is only a limited amount of memory available on the system. HSQLDB tables are kept fully in memory by default; this benchmark uses 'disk based' tables for all databases. Unfortunately, it is not so easy to calculate the memory usage of PostgreSQL and MySQL, because they run in a different process than the test. This benchmark currently does not print memory usage of those databases.
@performance_1266_h4
@performance_1267_h4
Delayed Operations
@performance_1267_p
@performance_1268_p
Some databases delay some operations (for example flushing the buffers) until after the benchmark is run. This benchmark waits between each database tested, and each database runs in a different process (sequentially).
@performance_1268_h4
@performance_1269_h4
Transaction Commit / Durability
@performance_1269_p
@performance_1270_p
Durability means transaction committed to the database will not be lost. Some databases (for example MySQL) try to enforce this by default by calling fsync() to flush the buffers, but most hard drives don't actually flush all data. Calling fsync() slows down transaction commit a lot, but doesn't always make data durable. When comparing the results, it is important to think about the effect. Many database suggest to 'batch' operations when possible. This benchmark switches off autocommit when loading the data, and calls commit after each 1000 inserts. However many applications need 'short' transactions at runtime (a commit after each update). This benchmark commits after each update / delete in the simple benchmark, and after each business transaction in the other benchmarks. For databases that support delayed commits, a delay of one second is used.
@performance_1270_h4
@performance_1271_h4
Using Prepared Statements
@performance_1271_p
@performance_1272_p
Wherever possible, the test cases use prepared statements.
@performance_1272_h4
@performance_1273_h4
Currently Not Tested: Startup Time
@performance_1273_p
@performance_1274_p
The startup time of a database engine is important as well for embedded use. This time is not measured currently. Also, not tested is the time used to create a database and open an existing database. Here, one (wrapper) connection is opened at the start, and for each step a new connection is opened and then closed. That means the Open/Close time listed is for opening a connection if the database is already in use.
@performance_1274_h2
@performance_1275_h2
PolePosition Benchmark
@performance_1275_p
@performance_1276_p
The PolePosition is an open source benchmark. The algorithms are all quite simple. It was developed / sponsored by db4o.
@performance_1276_th
@performance_1277_th
Test Case
@performance_1277_th
@performance_1278_th
Unit
@performance_1278_th
@performance_1279_th
H2
@performance_1279_th
@performance_1280_th
HSQLDB
@performance_1280_th
@performance_1281_th
MySQL
@performance_1281_td
@performance_1282_td
Melbourne write
@performance_1282_td
@performance_1283_td
ms
@performance_1283_td
@performance_1284_td
369
@performance_1284_td
@performance_1285_td
249
@performance_1285_td
@performance_1286_td
2022
@performance_1286_td
@performance_1287_td
Melbourne read
@performance_1287_td
@performance_1288_td
ms
@performance_1288_td
@performance_1289_td
47
@performance_1289_td
@performance_1290_td
49
@performance_1290_td
@performance_1291_td
93
@performance_1291_td
@performance_1292_td
Melbourne read_hot
@performance_1292_td
@performance_1293_td
ms
@performance_1293_td
@performance_1294_td
24
@performance_1294_td
@performance_1295_td
43
@performance_1295_td
@performance_1296_td
95
@performance_1296_td
@performance_1297_td
Melbourne delete
@performance_1297_td
@performance_1298_td
ms
@performance_1298_td
@performance_1299_td
147
@performance_1299_td
@performance_1300_td
133
@performance_1300_td
@performance_1301_td
176
@performance_1301_td
@performance_1302_td
Sepang write
@performance_1302_td
@performance_1303_td
ms
@performance_1303_td
@performance_1304_td
965
@performance_1304_td
@performance_1305_td
1201
@performance_1305_td
@performance_1306_td
3213
@performance_1306_td
@performance_1307_td
Sepang read
@performance_1307_td
@performance_1308_td
ms
@performance_1308_td
@performance_1309_td
765
@performance_1309_td
@performance_1310_td
948
@performance_1310_td
@performance_1311_td
3455
@performance_1311_td
@performance_1312_td
Sepang read_hot
@performance_1312_td
@performance_1313_td
ms
@performance_1313_td
@performance_1314_td
789
@performance_1314_td
@performance_1315_td
859
@performance_1315_td
@performance_1316_td
3563
@performance_1316_td
@performance_1317_td
Sepang delete
@performance_1317_td
@performance_1318_td
ms
@performance_1318_td
@performance_1319_td
1384
@performance_1319_td
@performance_1320_td
1596
@performance_1320_td
@performance_1321_td
6214
@performance_1321_td
@performance_1322_td
Bahrain write
@performance_1322_td
@performance_1323_td
ms
@performance_1323_td
@performance_1324_td
1186
@performance_1324_td
@performance_1325_td
1387
@performance_1325_td
@performance_1326_td
6904
@performance_1326_td
@performance_1327_td
Bahrain query_indexed_string
@performance_1327_td
@performance_1328_td
ms
@performance_1328_td
@performance_1329_td
336
@performance_1329_td
@performance_1330_td
170
@performance_1330_td
@performance_1331_td
693
@performance_1331_td
@performance_1332_td
Bahrain query_string
@performance_1332_td
@performance_1333_td
ms
@performance_1333_td
@performance_1334_td
18064
@performance_1334_td
@performance_1335_td
39703
@performance_1335_td
@performance_1336_td
41243
@performance_1336_td
@performance_1337_td
Bahrain query_indexed_int
@performance_1337_td
@performance_1338_td
ms
@performance_1338_td
@performance_1339_td
104
@performance_1339_td
@performance_1340_td
134
@performance_1340_td
@performance_1341_td
678
@performance_1341_td
@performance_1342_td
Bahrain update
@performance_1342_td
@performance_1343_td
ms
@performance_1343_td
@performance_1344_td
191
@performance_1344_td
@performance_1345_td
87
@performance_1345_td
@performance_1346_td
159
@performance_1346_td
@performance_1347_td
Bahrain delete
@performance_1347_td
@performance_1348_td
ms
@performance_1348_td
@performance_1349_td
1215
@performance_1349_td
@performance_1350_td
729
@performance_1350_td
@performance_1351_td
6812
@performance_1351_td
@performance_1352_td
Imola retrieve
@performance_1352_td
@performance_1353_td
ms
@performance_1353_td
@performance_1354_td
198
@performance_1354_td
@performance_1355_td
194
@performance_1355_td
@performance_1356_td
4036
@performance_1356_td
@performance_1357_td
Barcelona write
@performance_1357_td
@performance_1358_td
ms
@performance_1358_td
@performance_1359_td
413
@performance_1359_td
@performance_1360_td
832
@performance_1360_td
@performance_1361_td
3191
@performance_1361_td
@performance_1362_td
Barcelona read
@performance_1362_td
@performance_1363_td
ms
@performance_1363_td
@performance_1364_td
119
@performance_1364_td
@performance_1365_td
160
@performance_1365_td
@performance_1366_td
1177
@performance_1366_td
@performance_1367_td
Barcelona query
@performance_1367_td
@performance_1368_td
ms
@performance_1368_td
@performance_1369_td
20
@performance_1369_td
@performance_1370_td
5169
@performance_1370_td
@performance_1371_td
101
@performance_1371_td
@performance_1372_td
Barcelona delete
@performance_1372_td
@performance_1373_td
ms
@performance_1373_td
@performance_1374_td
388
@performance_1374_td
@performance_1375_td
319
@performance_1375_td
@performance_1376_td
3287
@performance_1376_td
@performance_1377_td
Total
@performance_1377_td
@performance_1378_td
ms
@performance_1378_td
@performance_1379_td
26724
@performance_1379_td
@performance_1380_td
53962
@performance_1380_td
@performance_1381_td
87112
@performance_1381_h2
@performance_1382_h2
Application Profiling
@performance_1382_h3
@performance_1383_h3
Analyze First
@performance_1383_p
Before trying to optimize the performance, it is important to know where the time is actually spent. The same is true for memory problems. Premature or 'blind' optimization should be avoided, as it is not an efficient way to solve the problem. There are various ways to analyze the application. In some situations it is possible to compare two implementations and use System.currentTimeMillis() to find out which one is faster. But this does not work for complex applications with many modules, and for memory problems. A very good tool to measure both the memory and the CPU is the <a href="http://www.yourkit.com">YourKit Java Profiler</a> . This tool is also used to optimize the performance and memory footprint of this database engine.
@performance_1384_p
Before trying to optimize the performance, it is important to know where the time is actually spent. The same is true for memory problems. Premature or 'blind' optimization should be avoided, as it is not an efficient way to solve the problem. There are various ways to analyze the application. In some situations it is possible to compare two implementations and use System.currentTimeMillis() to find out which one is faster. But this does not work for complex applications with many modules, and for memory problems.
@performance_1385_p
A very good tool to measure both the memory and the CPU is the <a href="http://www.yourkit.com">YourKit Java Profiler</a> . This tool is also used to optimize the performance and memory footprint of this database engine.
@performance_1386_p
A simple way to profile an application is to use the built-in profiling tool of java. Example:
@performance_1387_p
Unfortunately, it is only possible to profile the application from start to end.
@performance_1388_h2
Database Profiling
@performance_1389_p
The ConvertTraceFile tool generates SQL statement statistics at the end of the SQL script file. The format used is similar to the profiling data generated when using java -Xrunhprof. As an example, execute the the following script using the H2 Console:
@performance_1390_p
Now convert the .trace.db file using the ConvertTraceFile tool:
@performance_1391_p
The generated file <code>test.sql</code> will contain the SQL statements as well as the following profiling data (results vary):
@performance_1384_h2
@performance_1392_h2
Database Performance Tuning
@performance_1385_h3
@performance_1393_h3
Virus Scanners
@performance_1386_p
@performance_1394_p
Some virus scanners scan files every time they are accessed. It is very important for performance that database files are not scanned for viruses. The database engine does never interprets the data stored in the files as programs, that means even if somebody would store a virus in a database file, this would be harmless (when the virus does not run, it cannot spread). Some virus scanners allow excluding file endings. Make sure files ending with .db are not scanned.
@performance_1387_h3
@performance_1395_h3
Using the Trace Options
@performance_1388_p
@performance_1396_p
If the main performance hot spots are in the database engine, in many cases the performance can be optimized by creating additional indexes, or changing the schema. Sometimes the application does not directly generate the SQL statements, for example if an O/R mapping tool is used. To view the SQL statements and JDBC API calls, you can use the trace options. For more information, see <a href="features.html#trace_options">Using the Trace Options</a> .
@performance_1389_h3
@performance_1397_h3
Index Usage
@performance_1390_p
@performance_1398_p
This database uses indexes to improve the performance of SELECT, UPDATE and DELETE statements. If a column is used in the WHERE clause of a query, and if an index exists on this column, then the index can be used. Multi-column indexes are used if all or the first columns of the index are used. Both equality lookup and range scans are supported. Indexes are not used to order result sets: The results are sorted in memory if required. Indexes are created automatically for primary key and unique constraints. Indexes are also created for foreign key constraints, if required. For other columns, indexes need to be created manually using the CREATE INDEX statement.
@performance_1391_h3
@performance_1399_h3
Optimizer
@performance_1392_p
@performance_1400_p
This database uses a cost based optimizer. For simple and queries and queries with medium complexity (less than 7 tables in the join), the expected cost (running time) of all possible plans is calculated, and the plan with the lowest cost is used. For more complex queries, the algorithm first tries all possible combinations for the first few tables, and the remaining tables added using a greedy algorithm (this works well for most joins). Afterwards a genetic algorithm is used to test at most 2000 distinct plans. Only left-deep plans are evaluated.
@performance_1393_h3
@performance_1401_h3
Expression Optimization
@performance_1394_p
@performance_1402_p
After the statement is parsed, all expressions are simplified automatically if possible. Operations are evaluated only once if all parameters are constant. Functions are also optimized, but only if the function is constant (always returns the same result for the same parameter values). If the WHERE clause is always false, then the table is not accessed at all.
@performance_1395_h3
@performance_1403_h3
COUNT(*) Optimization
@performance_1396_p
@performance_1404_p
If the query only counts all rows of a table, then the data is not accessed. However, this is only possible if no WHERE clause is used, that means it only works for queries of the form SELECT COUNT(*) FROM table.
@performance_1397_h3
@performance_1405_h3
Updating Optimizer Statistics / Column Selectivity
@performance_1398_p
@performance_1406_p
When executing a query, at most one index per joined table can be used. If the same table is joined multiple times, for each join only one index is used. Example: for the query SELECT * FROM TEST T1, TEST T2 WHERE T1.NAME='A' AND T2.ID=T1.ID, two index can be used, in this case the index on NAME for T1 and the index on ID for T2.
@performance_1399_p
@performance_1407_p
If a table has multiple indexes, sometimes more than one index could be used. Example: if there is a table TEST(ID, NAME, FIRSTNAME) and an index on each column, then two indexes could be used for the query SELECT * FROM TEST WHERE NAME='A' AND FIRSTNAME='B', the index on NAME or the index on FIRSTNAME. It is not possible to use both indexes at the same time. Which index is used depends on the selectivity of the column. The selectivity describes the 'uniqueness' of values in a column. A selectivity of 100 means each value appears only once, and a selectivity of 1 means the same value appears in many or most rows. For the query above, the index on NAME should be used if the table contains more distinct names than first names.
@performance_1400_p
@performance_1408_p
The SQL statement ANALYZE can be used to automatically estimate the selectivity of the columns in the tables. This command should be run from time to time to improve the query plans generated by the optimizer.
@performance_1401_h3
@performance_1409_h3
Optimization Examples
@performance_1402_p
@performance_1410_p
See <code>src/test/org/h2/samples/optimizations.sql</code> for a few examples of queries that benefit from special optimizations built into the database.
@quickstart_1000_h1
......@@ -7385,387 +7415,390 @@ Server protocol: use challenge response authentication, but client sends hash(us
Support EXEC[UTE] (doesn't return a result set, compatible to MS SQL Server)
@roadmap_1224_li
GROUP BY and DISTINCT: support large groups (buffer to disk), do not keep large sets in memory
Support native XML data type
@roadmap_1225_li
Support native XML data type
Support triggers with a string property or option: SpringTrigger, OSGITrigger
@roadmap_1226_li
Support triggers with a string property or option: SpringTrigger, OSGITrigger
Clustering: adding a node should be very fast and without interrupting clients (very short lock)
@roadmap_1227_li
Clustering: adding a node should be very fast and without interrupting clients (very short lock)
Support materialized views (using triggers)
@roadmap_1228_li
Support materialized views (using triggers)
Store dates in local time zone (portability of database files)
@roadmap_1229_li
Store dates in local time zone (portability of database files)
Ability to resize the cache array when resizing the cache
@roadmap_1230_li
Ability to resize the cache array when resizing the cache
Time based cache writing (one second after writing the log)
@roadmap_1231_li
Time based cache writing (one second after writing the log)
Check state of H2 driver for DDLUtils: https://issues.apache.org/jira/browse/DDLUTILS-185
@roadmap_1232_li
Check state of H2 driver for DDLUtils: https://issues.apache.org/jira/browse/DDLUTILS-185
Index usage for REGEXP LIKE.
@roadmap_1233_li
Index usage for REGEXP LIKE.
Add a role DBA (like ADMIN).
@roadmap_1234_li
Add a role DBA (like ADMIN).
Better support multiple processors for in-memory databases.
@roadmap_1235_li
Better support multiple processors for in-memory databases.
Access rights: remember the owner of an object. COMMENT: allow owner of object to change it.
@roadmap_1236_li
Access rights: remember the owner of an object. COMMENT: allow owner of object to change it.
Implement INSTEAD OF trigger.
@roadmap_1237_li
Implement INSTEAD OF trigger.
Access rights: Finer grained access control (grant access for specific functions)
@roadmap_1238_li
Access rights: Finer grained access control (grant access for specific functions)
Support N'text'
@roadmap_1239_li
Support N'text'
Support SCOPE_IDENTITY() to avoid problems when inserting rows in a trigger
@roadmap_1240_li
Support SCOPE_IDENTITY() to avoid problems when inserting rows in a trigger
Set a connection read only (Connection.setReadOnly)
@roadmap_1241_li
Set a connection read only (Connection.setReadOnly)
In MySQL mode, for AUTO_INCREMENT columns, don't set the primary key
@roadmap_1242_li
In MySQL mode, for AUTO_INCREMENT columns, don't set the primary key
Use JDK 1.4 file locking to create the lock file (but not yet by default); writing a system property to detect concurrent access from the same VM (different classloaders).
@roadmap_1243_li
Use JDK 1.4 file locking to create the lock file (but not yet by default); writing a system property to detect concurrent access from the same VM (different classloaders).
Support compatibility for jdbc:hsqldb:res:
@roadmap_1244_li
Support compatibility for jdbc:hsqldb:res:
In the MySQL and PostgreSQL, use lower case identifiers by default (DatabaseMetaData.storesLowerCaseIdentifiers = true)
@roadmap_1245_li
In the MySQL and PostgreSQL, use lower case identifiers by default (DatabaseMetaData.storesLowerCaseIdentifiers = true)
Provide a simple, lightweight O/R mapping tool
@roadmap_1246_li
Provide a simple, lightweight O/R mapping tool
Provide an Java SQL builder with standard and H2 syntax
@roadmap_1247_li
Provide an Java SQL builder with standard and H2 syntax
Trace: write OS, file system, JVM,... when opening the database
@roadmap_1248_li
Trace: write OS, file system, JVM,... when opening the database
Support indexes for views (probably requires materialized views)
@roadmap_1249_li
Support indexes for views (probably requires materialized views)
Document SET SEARCH_PATH, BEGIN, EXECUTE, parameters
@roadmap_1250_li
Document SET SEARCH_PATH, BEGIN, EXECUTE, parameters
Browser: use Desktop.isDesktopSupported and browse when using JDK 1.6
@roadmap_1251_li
Browser: use Desktop.isDesktopSupported and browse when using JDK 1.6
Server: use one listener (detect if the request comes from an PG or TCP client)
@roadmap_1252_li
Server: use one listener (detect if the request comes from an PG or TCP client)
Store dates as 'local'. Existing files use GMT. Use escape syntax for compatibility.
@roadmap_1253_li
Store dates as 'local'. Existing files use GMT. Use escape syntax for compatibility.
Support data type INTERVAL
@roadmap_1254_li
Support data type INTERVAL
NATURAL JOIN: MySQL and PostgreSQL don't repeat columns when using SELECT * ...
@roadmap_1255_li
NATURAL JOIN: MySQL and PostgreSQL don't repeat columns when using SELECT * ...
Optimize SELECT MIN(ID), MAX(ID), COUNT(*) FROM TEST WHERE ID BETWEEN 100 AND 200
@roadmap_1256_li
Optimize SELECT MIN(ID), MAX(ID), COUNT(*) FROM TEST WHERE ID BETWEEN 100 AND 200
Support Oracle functions: TRUNC, NVL2, TO_CHAR, TO_DATE, TO_NUMBER
@roadmap_1257_li
Support Oracle functions: TRUNC, NVL2, TO_CHAR, TO_DATE, TO_NUMBER
Sequence: PostgreSQL compatibility (rename, create) (http://www.postgresql.org/docs/8.2/static/sql-altersequence.html)
@roadmap_1258_li
Sequence: PostgreSQL compatibility (rename, create) (http://www.postgresql.org/docs/8.2/static/sql-altersequence.html)
DISTINCT: Support large result sets by sorting on all columns (additionally) and then removing duplicates.
@roadmap_1259_li
DISTINCT: Support large result sets by sorting on all columns (additionally) and then removing duplicates.
File system that writes to two file systems (replicating file system)
@roadmap_1260_li
File system that writes to two file systems (replicating file system)
File system with a background writer thread; test if this is faster
@roadmap_1261_li
File system with a background writer thread; test if this is faster
FTP access to a database (.csv for a table, a directory for a schema, a file for a lob, a script.sql file).
@roadmap_1262_li
FTP access to a database (.csv for a table, a directory for a schema, a file for a lob, a script.sql file).
LIMIT and OFFSET for GROUP_CONCAT
@roadmap_1263_li
LIMIT and OFFSET for GROUP_CONCAT
Support triggers for INFORMATION_SCHEMA tables (to better support PostgreSQL catalog: rebuild after creating new tables)
@roadmap_1264_li
Support triggers for INFORMATION_SCHEMA tables (to better support PostgreSQL catalog: rebuild after creating new tables)
Better document the source code
@roadmap_1265_li
Better document the source code
Support select * from dual a left join dual b on b.x=(select max(x) from dual)
@roadmap_1266_li
Support select * from dual a left join dual b on b.x=(select max(x) from dual)
Optimization: don't lock when the database is read-only
@roadmap_1267_li
Optimization: don't lock when the database is read-only
Integrate spatial functions from http://geosysin.iict.ch/irstv-trac/wiki/H2spatial/Download
@roadmap_1268_li
Integrate spatial functions from http://geosysin.iict.ch/irstv-trac/wiki/H2spatial/Download
Support COSH, SINH, and TANH functions
@roadmap_1269_li
Support COSH, SINH, and TANH functions
Native search: support "phrase search", wildcard search (* and ?), case-insensitive search, boolean operators, and grouping
@roadmap_1270_li
Native search: support "phrase search", wildcard search (* and ?), case-insensitive search, boolean operators, and grouping
Improve documentation of access rights
@roadmap_1271_li
Improve documentation of access rights
Support ENUM data type (see MySQL, PostgreSQL, MS SQL Server, maybe others)
@roadmap_1272_li
Support ENUM data type (see MySQL, PostgreSQL, MS SQL Server, maybe others)
Command line option for the H2 Console and TCP configuration (which .h2.server.properties and .h2.keystore to use)
@roadmap_1273_li
Command line option for the H2 Console and TCP configuration (which .h2.server.properties and .h2.keystore to use)
Support a schema name for Java functions
@roadmap_1274_li
Support a schema name for Java functions
Remember the domain of a column
@roadmap_1275_li
Remember the domain of a column
Support Jackcess (MS Access databases)
@roadmap_1276_li
Support Jackcess (MS Access databases)
Built-in methods to write large objects (BLOB and CLOB): FILE_WRITE('test.txt', 'Hello World')
@roadmap_1277_li
Built-in methods to write large objects (BLOB and CLOB): FILE_WRITE('test.txt', 'Hello World')
Change package name in version 2.0: org.h2database
@roadmap_1278_li
Change package name in version 2.0: org.h2database
MVCC: support transactionally consistent backups using SCRIPT
@roadmap_1279_li
MVCC: support transactionally consistent backups using SCRIPT
Improve time to open large databases (see mail 'init time for distributed setup')
@roadmap_1280_li
Improve time to open large databases (see mail 'init time for distributed setup')
Use ARRAY for fulltext search return value, at least internally in the native implementation (and as an option for the user)
@roadmap_1281_li
Use ARRAY for fulltext search return value, at least internally in the native implementation (and as an option for the user)
Move Maven 2 repository from hsql.sf.net to h2database.sf.net
@roadmap_1282_li
Move Maven 2 repository from hsql.sf.net to h2database.sf.net
Java 1.5 tool: JdbcUtils.closeSilently(s1, s2,...)
@roadmap_1283_li
Java 1.5 tool: JdbcUtils.closeSilently(s1, s2,...)
Javadoc: document design patterns used
@roadmap_1284_li
Javadoc: document design patterns used
Triggers for metadata tables; use for PostgreSQL catalog
@roadmap_1285_li
Triggers for metadata tables; use for PostgreSQL catalog
Does the FTP server has problems with multithreading?
@roadmap_1286_li
Does the FTP server has problems with multithreading?
Write an article about SQLInjection (h2\src\docsrc\html\images\SQLInjection.txt)
@roadmap_1287_li
Write an article about SQLInjection (h2\src\docsrc\html\images\SQLInjection.txt)
Convert SQL-injection-2.txt to html document, include SQLInjection.java sample
@roadmap_1288_li
Convert SQL-injection-2.txt to html document, include SQLInjection.java sample
Send SQL Injection solution proposal to MySQL, Derby, HSQLDB,...
@roadmap_1289_li
Send SQL Injection solution proposal to MySQL, Derby, HSQLDB,...
Improve LOB in directories performance
@roadmap_1290_li
Improve LOB in directories performance
Optimize OR conditions: convert them to IN(...) if possible.
@roadmap_1291_li
Optimize OR conditions: convert them to IN(...) if possible.
Web site design: http://www.igniterealtime.org/projects/openfire/index.jsp
@roadmap_1292_li
Web site design: http://www.igniterealtime.org/projects/openfire/index.jsp
HSQLDB compatibility: Openfire server uses: CREATE SCHEMA PUBLIC AUTHORIZATION DBA; CREATE USER SA PASSWORD ""; GRANT DBA TO SA; SET SCHEMA PUBLIC
@roadmap_1293_li
HSQLDB compatibility: Openfire server uses: CREATE SCHEMA PUBLIC AUTHORIZATION DBA; CREATE USER SA PASSWORD ""; GRANT DBA TO SA; SET SCHEMA PUBLIC
Web site: Rename Performance to Comparison [/Compatibility], move Comparison to Other Database Engines to Comparison, move Products that Work with H2 to Comparison, move Performance Tuning to Advanced Topics
@roadmap_1294_li
Web site: Rename Performance to Comparison [/Compatibility], move Comparison to Other Database Engines to Comparison, move Products that Work with H2 to Comparison, move Performance Tuning to Advanced Topics
Translation: use ?? in help.csv
@roadmap_1295_li
Translation: use ?? in help.csv
Translated .pdf
@roadmap_1296_li
Translated .pdf
Cluster: hot deploy (adding a node on runtime)
@roadmap_1297_li
Cluster: hot deploy (adding a node on runtime)
Test with PostgreSQL Version 8.2
@roadmap_1298_li
Test with PostgreSQL Version 8.2
Website: Don't use frames.
@roadmap_1299_li
Website: Don't use frames.
Try again with Lobo browser (pure Java)
@roadmap_1300_li
Try again with Lobo browser (pure Java)
Recovery tool: bad blocks should be converted to INSERT INTO SYSTEM_ERRORS(...), and things should go into the .trace.db file
@roadmap_1301_li
Recovery tool: bad blocks should be converted to INSERT INTO SYSTEM_ERRORS(...), and things should go into the .trace.db file
RECOVER=2 to backup the database, run recovery, open the database
@roadmap_1302_li
RECOVER=2 to backup the database, run recovery, open the database
Recovery should work with encrypted databases
@roadmap_1303_li
Recovery should work with encrypted databases
Corruption: new error code, add help
@roadmap_1304_li
Corruption: new error code, add help
Space reuse: after init, scan all storages and free those that don't belong to a live database object
@roadmap_1305_li
Space reuse: after init, scan all storages and free those that don't belong to a live database object
SysProperties: change everything to H2_...
@roadmap_1306_li
SysProperties: change everything to H2_...
Use FilterIn / FilterOut putStream?
@roadmap_1307_li
Use FilterIn / FilterOut putStream?
Access rights: add missing features (users should be 'owner' of objects; missing rights for sequences; dropping objects)
@roadmap_1308_li
Access rights: add missing features (users should be 'owner' of objects; missing rights for sequences; dropping objects)
Support NOCACHE table option (Oracle)
@roadmap_1309_li
Support NOCACHE table option (Oracle)
Index usage for UPDATE ... WHERE .. IN (SELECT...)
@roadmap_1310_li
Index usage for UPDATE ... WHERE .. IN (SELECT...)
Add regular javadocs (using the default doclet, but another css) to the homepage.
@roadmap_1311_li
Add regular javadocs (using the default doclet, but another css) to the homepage.
The database should be kept open for a longer time when using the server mode.
@roadmap_1312_li
The database should be kept open for a longer time when using the server mode.
Javadocs: for each tool, add a copy &amp; paste sample in the class level.
@roadmap_1313_li
Javadocs: for each tool, add a copy &amp; paste sample in the class level.
Javadocs: add @author tags.
@roadmap_1314_li
Javadocs: add @author tags.
Fluent API for tools: Server.createTcpServer().setPort(9081).setPassword(password).start();
@roadmap_1315_li
Fluent API for tools: Server.createTcpServer().setPort(9081).setPassword(password).start();
MySQL compatibility: real SQL statements for SHOW TABLES, DESCRIBE TEST (then remove from Shell)
@roadmap_1316_li
MySQL compatibility: real SQL statements for SHOW TABLES, DESCRIBE TEST (then remove from Shell)
Use a default delay of 1 second before closing a database.
@roadmap_1317_li
Use a default delay of 1 second before closing a database.
Maven: upload source code and javadocs as well.
@roadmap_1318_li
Maven: upload source code and javadocs as well.
Write (log) to system table before adding to internal data structures.
@roadmap_1319_li
Write (log) to system table before adding to internal data structures.
Support very large deletes and updates.
@roadmap_1320_li
Support very large deletes and updates.
Doclet (javadocs): constructors are not listed.
@roadmap_1321_li
Doclet (javadocs): constructors are not listed.
Support direct lookup for MIN and MAX when using WHERE (see todo.txt / Direct Lookup).
@roadmap_1322_li
Support direct lookup for MIN and MAX when using WHERE (see todo.txt / Direct Lookup).
Support other array types (String[], double[]) in PreparedStatement.setObject(int, Object);
@roadmap_1323_li
Support other array types (String[], double[]) in PreparedStatement.setObject(int, Object);
MVCC should not be memory bound (uncommitted data is kept in memory in the delta index; maybe using a regular btree index solves the problem).
@roadmap_1324_li
MVCC should not be memory bound (uncommitted data is kept in memory in the delta index; maybe using a regular btree index solves the problem).
Support CREATE TEMPORARY LINKED TABLE.
@roadmap_1325_li
Support CREATE TEMPORARY LINKED TABLE.
MySQL compatibility: SELECT @variable := x FROM SYSTEM_RANGE(1, 50);
@roadmap_1326_li
MySQL compatibility: SELECT @variable := x FROM SYSTEM_RANGE(1, 50);
Oracle compatibility: support NLS_DATE_FORMAT.
@roadmap_1327_li
Oracle compatibility: support NLS_DATE_FORMAT.
Support flashback queries as in Oracle.
@roadmap_1328_li
Support flashback queries as in Oracle.
Import / Export of fixed with text files.
@roadmap_1329_li
Import / Export of fixed with text files.
Support for OUT parameters in user-defined procedures.
@roadmap_1330_li
Support for OUT parameters in user-defined procedures.
Support getGeneratedKeys to return multiple rows when used with batch updates. This is supported by MySQL, but not Derby. Both PostgreSQL and HSQLDB don't support getGeneratedKeys. Also support it when using INSERT ... SELECT.
@roadmap_1331_li
Support getGeneratedKeys to return multiple rows when used with batch updates. This is supported by MySQL, but not Derby. Both PostgreSQL and HSQLDB don't support getGeneratedKeys. Also support it when using INSERT ... SELECT.
HSQLDB compatibility: automatic data type for SUM if value is the value is too big (by default use the same type as the data).
@roadmap_1332_li
HSQLDB compatibility: automatic data type for SUM if value is the value is too big (by default use the same type as the data).
Improve the optimizer to select the right index for special cases: where id between 2 and 4 and booleanColumn
@roadmap_1333_li
Improve the optimizer to select the right index for special cases: where id between 2 and 4 and booleanColumn
Enable warning for 'Local variable declaration hides another field or variable'.
@roadmap_1334_li
Enable warning for 'Local variable declaration hides another field or variable'.
Linked tables: make hidden columns available (Oracle: rowid and ora_rowscn columns).
@roadmap_1335_li
Linked tables: make hidden columns available (Oracle: rowid and ora_rowscn columns).
Support merge join.
@roadmap_1336_li
Support merge join.
H2 Console: in-place autocomplete (need to merge query and result frame, use div).
@roadmap_1337_li
H2 Console: in-place autocomplete (need to merge query and result frame, use div).
MySQL compatibility: update test1 t1, test2 t2 set t1.id = t2.id where t1.id = t2.id;
@roadmap_1338_li
MySQL compatibility: update test1 t1, test2 t2 set t1.id = t2.id where t1.id = t2.id;
Oracle: support DECODE method (convert to CASE WHEN).
@roadmap_1339_li
Oracle: support DECODE method (convert to CASE WHEN).
Support large databases: split LOB (BLOB, CLOB) to multiple directories / disks (similar to tablespaces).
@roadmap_1340_li
Support large databases: split LOB (BLOB, CLOB) to multiple directories / disks (similar to tablespaces).
Support to assign a primary key index a user defined name.
@roadmap_1341_li
Support to assign a primary key index a user defined name.
Cluster: Add feature to make sure cluster nodes can not get out of sync (for example by stopping one process).
@roadmap_1342_li
Cluster: Add feature to make sure cluster nodes can not get out of sync (for example by stopping one process).
H2 Console: support configuration option for fixed width (monospace) font.
@roadmap_1343_li
H2 Console: support configuration option for fixed width (monospace) font.
Native fulltext search: support analyzers (specially for Chinese, Japanese).
@roadmap_1344_li
Native fulltext search: support analyzers (specially for Chinese, Japanese).
Automatically compact databases from time to time (as a background process).
@roadmap_1345_li
Automatically compact databases from time to time (as a background process).
Support GRANT SELECT, UPDATE ON *.
@roadmap_1346_li
Support GRANT SELECT, UPDATE ON *.
Test Eclipse DTP.
@roadmap_1347_li
Test Eclipse DTP.
Support JMX: Create an MBean for each database and server (support JConsole).
@roadmap_1348_li
Support JMX: Create an MBean for each database and server (support JConsole).
H2 Console: autocomplete: keep the previous setting
@roadmap_1349_h2
@roadmap_1349_li
executeBatch: option to stop at the first failed statement.
@roadmap_1350_h2
Not Planned
@roadmap_1350_li
@roadmap_1351_li
HSQLDB (did) support this: select id i from test where i>0 (other databases don't). Supporting it may break compatibility.
@roadmap_1351_li
@roadmap_1352_li
String.intern (so that Strings can be compared with ==) will not be used because some VMs have problems when used extensively.
@search_1000_b
......@@ -8176,300 +8209,303 @@ Add the h2.jar file your web application, and add the following snippet to your
@tutorial_1099_p
For details on how to access the database, see the code DbStarter.java
@tutorial_1100_h2
@tutorial_1100_p
By default the DbStarter listener opens a connection using the database URL jdbc:h2:~/test and user name and password 'sa'. It can also start the TCP server, however this is disabled by default. To enable it, use the db.tcpServer parameter in web.xml. Here is the complete list of options. These options are set just after the display-name and description tag, but before any listener and filter tags:
@tutorial_1101_h2
CSV (Comma Separated Values) Support
@tutorial_1101_p
@tutorial_1102_p
The CSV file support can be used inside the database using the functions CSVREAD and CSVWRITE, and the CSV library can be used outside the database as a standalone tool.
@tutorial_1102_h3
@tutorial_1103_h3
Writing a CSV File from Within a Database
@tutorial_1103_p
@tutorial_1104_p
The built-in function CSVWRITE can be used to create a CSV file from a query. Example:
@tutorial_1104_h3
@tutorial_1105_h3
Reading a CSV File from Within a Database
@tutorial_1105_p
@tutorial_1106_p
A CSV file can be read using the function CSVREAD. Example:
@tutorial_1106_h3
@tutorial_1107_h3
Writing a CSV File from a Java Application
@tutorial_1107_p
@tutorial_1108_p
The CSV tool can be used in a Java application even when not using a database at all. Example:
@tutorial_1108_h3
@tutorial_1109_h3
Reading a CSV File from a Java Application
@tutorial_1109_p
@tutorial_1110_p
It is possible to read a CSV file without opening a database. Example:
@tutorial_1110_h2
@tutorial_1111_h2
Upgrade, Backup, and Restore
@tutorial_1111_h3
@tutorial_1112_h3
Database Upgrade
@tutorial_1112_p
@tutorial_1113_p
The recommended way to upgrade from one version of the database engine to the next version is to create a backup of the database (in the form of a SQL script) using the old engine, and then execute the SQL script using the new engine.
@tutorial_1113_h3
@tutorial_1114_h3
Backup using the Script Tool
@tutorial_1114_p
@tutorial_1115_p
There are different ways to backup a database. For example, it is possible to copy the database files. However, this is not recommended while the database is in use. Also, the database files are not human readable and quite large. The recommended way to backup a database is to create a compressed SQL script file. This can be done using the Script tool:
@tutorial_1115_p
@tutorial_1116_p
It is also possible to use the SQL command SCRIPT to create the backup of the database. For more information about the options, see the SQL command SCRIPT. The backup can be done remotely, however the file will be created on the server side. The built in FTP server could be used to retrieve the file from the server.
@tutorial_1116_h3
@tutorial_1117_h3
Restore from a Script
@tutorial_1117_p
@tutorial_1118_p
To restore a database from a SQL script file, you can use the RunScript tool:
@tutorial_1118_p
@tutorial_1119_p
For more information about the options, see the SQL command RUNSCRIPT. The restore can be done remotely, however the file needs to be on the server side. The built in FTP server could be used to copy the file to the server. It is also possible to use the SQL command RUNSCRIPT to execute a SQL script. SQL script files may contain references to other script files, in the form of RUNSCRIPT commands. However, when using the server mode, the references script files need to be available on the server side.
@tutorial_1119_h3
@tutorial_1120_h3
Online Backup
@tutorial_1120_p
@tutorial_1121_p
The BACKUP SQL statement and the Backup tool both create a zip file with all database files. However, the contents of this file are not human readable. Other than the SCRIPT statement, the BACKUP statement does not lock the database objects, and therefore does not block other users. The resulting backup is transactionally consistent:
@tutorial_1121_p
@tutorial_1122_p
The Backup tool (org.h2.tools.Backup) can not be used to create a online backup; the database must not be in use while running this program.
@tutorial_1122_h2
@tutorial_1123_h2
Command Line Tools
@tutorial_1123_p
@tutorial_1124_p
This database comes with a number of command line tools. To get more information about a tool, start it with the parameter '-?', for example:
@tutorial_1124_p
@tutorial_1125_p
The command line tools are:
@tutorial_1125_b
@tutorial_1126_b
Backup
@tutorial_1126_li
@tutorial_1127_li
creates a backup of a database.
@tutorial_1127_b
@tutorial_1128_b
ChangeFileEncryption
@tutorial_1128_li
@tutorial_1129_li
allows changing the file encryption password or algorithm of a database.
@tutorial_1129_b
@tutorial_1130_b
Console
@tutorial_1130_li
@tutorial_1131_li
starts the browser based H2 Console.
@tutorial_1131_b
@tutorial_1132_b
ConvertTraceFile
@tutorial_1132_li
@tutorial_1133_li
converts a .trace.db file to a Java application and SQL script.
@tutorial_1133_b
@tutorial_1134_b
CreateCluster
@tutorial_1134_li
@tutorial_1135_li
creates a cluster from a standalone database.
@tutorial_1135_b
@tutorial_1136_b
DeleteDbFiles
@tutorial_1136_li
@tutorial_1137_li
deletes all files belonging to a database.
@tutorial_1137_b
@tutorial_1138_b
Script
@tutorial_1138_li
@tutorial_1139_li
allows converting a database to a SQL script for backup or migration.
@tutorial_1139_b
@tutorial_1140_b
Recover
@tutorial_1140_li
@tutorial_1141_li
helps recovering a corrupted database.
@tutorial_1141_b
@tutorial_1142_b
Restore
@tutorial_1142_li
@tutorial_1143_li
restores a backup of a database.
@tutorial_1143_b
@tutorial_1144_b
RunScript
@tutorial_1144_li
@tutorial_1145_li
runs a SQL script against a database.
@tutorial_1145_b
@tutorial_1146_b
Server
@tutorial_1146_li
@tutorial_1147_li
is used in the server mode to start a H2 server.
@tutorial_1147_b
@tutorial_1148_b
Shell
@tutorial_1148_li
@tutorial_1149_li
is a command line database tool.
@tutorial_1149_p
@tutorial_1150_p
The tools can also be called from an application by calling the main or another public methods. For details, see the Javadoc documentation.
@tutorial_1150_h2
@tutorial_1151_h2
Using OpenOffice Base
@tutorial_1151_p
@tutorial_1152_p
OpenOffice.org Base supports database access over the JDBC API. To connect to a H2 database using OpenOffice Base, you first need to add the JDBC driver to OpenOffice. The steps to connect to a H2 database are:
@tutorial_1152_li
@tutorial_1153_li
Start OpenOffice Writer, go to [Tools], [Options]
@tutorial_1153_li
@tutorial_1154_li
Make sure you have selected a Java runtime environment in OpenOffice.org / Java
@tutorial_1154_li
@tutorial_1155_li
Click [Class Path...], [Add Archive...]
@tutorial_1155_li
@tutorial_1156_li
Select your h2.jar (location is up to you, could be wherever you choose)
@tutorial_1156_li
@tutorial_1157_li
Click [OK] (as much as needed), stop OpenOffice (including the Quickstarter)
@tutorial_1157_li
@tutorial_1158_li
Start OpenOffice Base
@tutorial_1158_li
@tutorial_1159_li
Connect to an existing database; select JDBC; [Next]
@tutorial_1159_li
@tutorial_1160_li
Example datasource URL: jdbc:h2:~/test
@tutorial_1160_li
@tutorial_1161_li
JDBC driver class: org.h2.Driver
@tutorial_1161_p
@tutorial_1162_p
Now you can access the database stored in the current users home directory.
@tutorial_1162_p
@tutorial_1163_p
To use H2 in NeoOffice (OpenOffice without X11):
@tutorial_1163_li
@tutorial_1164_li
In NeoOffice, go to [NeoOffice], [Preferences]
@tutorial_1164_li
@tutorial_1165_li
Look for the page under [NeoOffice], [Java]
@tutorial_1165_li
@tutorial_1166_li
Click [Classpath], [Add Archive...]
@tutorial_1166_li
@tutorial_1167_li
Select your h2.jar (location is up to you, could be wherever you choose)
@tutorial_1167_li
@tutorial_1168_li
Click [OK] (as much as needed), restart NeoOffice.
@tutorial_1168_p
@tutorial_1169_p
Now, when creating a new database using the "Database Wizard":
@tutorial_1169_li
@tutorial_1170_li
Select "connect to existing database" and the type "jdbc". Click next.
@tutorial_1170_li
@tutorial_1171_li
Enter your h2 database URL. The normal behavior of H2 is that a new db is created if it doesn't exist.
@tutorial_1171_li
@tutorial_1172_li
Next step - up to you... you can just click finish and start working.
@tutorial_1172_p
@tutorial_1173_p
Another solution to use H2 in NeoOffice is:
@tutorial_1173_li
@tutorial_1174_li
Package the h2 jar within an extension package
@tutorial_1174_li
@tutorial_1175_li
Install it as a Java extension in NeoOffice
@tutorial_1175_p
@tutorial_1176_p
This can be done by create it using the NetBeans OpenOffice plugin. See also <a href="http://wiki.services.openoffice.org/wiki/Extensions_development_java">Extensions Development</a> .
@tutorial_1176_h2
@tutorial_1177_h2
Java Web Start / JNLP
@tutorial_1177_p
@tutorial_1178_p
When using Java Web Start / JNLP (Java Network Launch Protocol), permissions tags must be set in the .jnlp file, and the application .jar file must be signed. Otherwise, when trying to write to the file system, the following exception will occur: java.security.AccessControlException: access denied (java.io.FilePermission ... read). Example permission tags:
@tutorial_1178_h2
@tutorial_1179_h2
Using a Connection Pool
@tutorial_1179_p
@tutorial_1180_p
For many databases, opening a connection is slow, and it is a good idea to use a connection pool to re-use connections. For H2 however opening a connection usually is fast if the database is already open. Using a connection pool for H2 actually slows down the process a bit, except if file encryption is used (in this case opening a connection is about half as fast as using a connection pool). A simple connection pool is included in H2. It is based on the <a href="http://www.source-code.biz/snippets/java/8.htm">Mini Connection Pool Manager</a> from Christian d'Heureuse. There are other, more complex connection pools available, for example <a href="http://jakarta.apache.org/commons/dbcp/">DBCP</a> . The build-in connection pool is used as follows:
@tutorial_1180_h2
@tutorial_1181_h2
Fulltext Search
@tutorial_1181_p
@tutorial_1182_p
H2 supports Lucene full text search and native full text search implementation.
@tutorial_1182_h3
@tutorial_1183_h3
Using the Native Full Text Search
@tutorial_1183_p
@tutorial_1184_p
To initialize, call:
@tutorial_1184_p
@tutorial_1185_p
You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using:
@tutorial_1185_p
@tutorial_1186_p
PUBLIC is the schema, TEST is the table name. The list of column names (column separated) is optional, in this case all columns are indexed. The index is updated in read time. To search the index, use the following query:
@tutorial_1186_p
@tutorial_1187_p
You can also call the index from within a Java application:
@tutorial_1187_h3
@tutorial_1188_h3
Using the Lucene Fulltext Search
@tutorial_1188_p
@tutorial_1189_p
To use the Lucene full text search, you need the Lucene library in the classpath. How his is done depends on the application; if you use the H2 Console, you can add the Lucene jar file to the environment variables H2DRIVERS or CLASSPATH. To initialize the Lucene full text search in a database, call:
@tutorial_1189_p
@tutorial_1190_p
You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using:
@tutorial_1190_p
@tutorial_1191_p
PUBLIC is the schema, TEST is the table name. The list of column names (column separated) is optional, in this case all columns are indexed. The index is updated in read time. To search the index, use the following query:
@tutorial_1191_p
@tutorial_1192_p
You can also call the index from within a Java application:
@tutorial_1192_h2
@tutorial_1193_h2
User-Defined Variables
@tutorial_1193_p
@tutorial_1194_p
This database supports user-defined variables. Variables start with @ and can be used wherever expressions or parameters are used. Variables not persisted and session scoped, that means only visible for the session where they are defined. A value is usually assigned using the SET command:
@tutorial_1194_p
@tutorial_1195_p
It is also possible to change a value using the SET() method. This is useful in queries:
@tutorial_1195_p
@tutorial_1196_p
Variables that are not set evaluate to NULL. The data type of a user-defined variable is the data type of the value assigned to it, that means it is not necessary (or possible) to declare variable names before using them. There are no restrictions on the assigned values; large objects (LOBs) are supported as well.
@tutorial_1196_h2
@tutorial_1197_h2
Date and Time
@tutorial_1197_p
@tutorial_1198_p
Date, time and timestamp values support ISO 8601 formatting, including time zone:
@tutorial_1198_p
@tutorial_1199_p
If the time zone is not set, the value is parsed using the current time zone setting of the system. Date and time information is stored in H2 database files in GMT (Greenwich Mean Time). If the database is opened using another system time zone, the date and time will change accordingly. If you want to move a database from one time zone to the other and don't want this to happen, you need to create a SQL script file using the SCRIPT command or Script tool, and then load the database using the RUNSCRIPT command or the RunScript tool in the new time zone.
h2/src/docsrc/text/_docs_ja.utf8.txt
浏览文件 @ 755bd88a
......@@ -4252,7 +4252,7 @@ Sourceファイル
#What is JaQu
@jaqu_1002_p
#JaQu stands for Java Query and allows to access databases using pure Java. JaQu replaces SQL, JDBC, and O/R frameworks such as Hibernate. JaQu is something like LINQ for Java (LINQ stands for "language integrated query" and is a Microsoft .NET technology). The following JaQu code:
#JaQu stands for Java Query and allows to access databases using pure Java. JaQu provides a fluent interface (or internal DSL) for building SQL statements. JaQu replaces SQL, JDBC, and O/R frameworks such as Hibernate. JaQu is something like LINQ for Java (LINQ stands for "language integrated query" and is a Microsoft .NET technology). The following JaQu code:
@jaqu_1003_p
#stands for the SQL statement:
......@@ -4294,54 +4294,60 @@ Sourceファイル
#src/tools/org/h2/jaqu/* (framework)
@jaqu_1016_h2
必要条件
#Building the JaQu library #必要条件
@jaqu_1017_p
#JaQu requires Java 1.5. Annotations are not need. Currently, JaQu is only tested with the H2 database engine, however in theory it should work with any database that supports the JDBC API.
#To create the JaQu jar file, run: <code>build jarJaqu</code> . This will create the file <code>bin/h2jaqu.jar</code> .
@jaqu_1018_h2
必要条件
@jaqu_1019_p
#JaQu requires Java 1.5. Annotations are not need. Currently, JaQu is only tested with the H2 database engine, however in theory it should work with any database that supports the JDBC API.
@jaqu_1020_h2
#Example Code
@jaqu_1019_h2
@jaqu_1021_h2
#Configuration
@jaqu_1020_p
@jaqu_1022_p
#JaQu does not require any kind of configuration is you want to use the default mapping. To define table indices, or if you want to map a class to a table with a different name, or a field to a column with another name, create a function called 'define' in the data class. Example:
@jaqu_1021_p
@jaqu_1023_p
#The method 'define()' contains the mapping definition. It is called once when the class is used for the first time. Like annotations, the mapping is defined in the class itself. Unlike when using annotations, the compiler can check the syntax even for multi-column objects (multi-column indexes, multi-column primary keys and so on). This solution is very flexible because the definition is written in regular Java code: Unlike when using annotations, your code can select the right configuration depending on the environment if required.
@jaqu_1022_h2
@jaqu_1024_h2
#Ideas
@jaqu_1023_p
@jaqu_1025_p
#This project has just been started, and nothing is fixed yet. Some ideas for what to implement include:
@jaqu_1024_li
@jaqu_1026_li
#Provide API level compatibility with JPA (so that JaQu can be used as an extension of JPA).
@jaqu_1025_li
@jaqu_1027_li
#Internally use a JPA implementation (for example Hibernate) instead of SQL directly.
@jaqu_1026_li
@jaqu_1028_li
#Use PreparedStatements and cache them.
@jaqu_1027_h2
@jaqu_1029_h2
#Related Projects
@jaqu_1028_a
@jaqu_1030_a
#JEQUEL: Java Embedded QUEry Language
@jaqu_1029_a
@jaqu_1031_a
#Quaere
@jaqu_1030_a
@jaqu_1032_a
#Quaere (Alias implementation)
@jaqu_1031_a
@jaqu_1033_a
#JoSQL
@jaqu_1032_a
@jaqu_1034_a
#Google Group about adding LINQ features to Java
@license_1000_h1
......@@ -5425,265 +5431,265 @@ See what this database can do and how to use these features.
#Application Profiling
@performance_1004_a
#Database Profiling
@performance_1005_a
#Performance Tuning
@performance_1005_h2
@performance_1006_h2
#Performance Comparison
@performance_1006_p
@performance_1007_p
#In most cases H2 is a lot faster than all other (open source and not open source) database engines. Please note this is mostly a single connection benchmark run on one computer.
@performance_1007_h3
@performance_1008_h3
#Embedded
@performance_1008_th
#Test Case
@performance_1009_th
#Unit
#Test Case
@performance_1010_th
H2
#Unit #H2
@performance_1011_th
HSQLDB
H2
@performance_1012_th
Derby
HSQLDB
@performance_1013_td
#Simple: Init
@performance_1013_th
Derby
@performance_1014_td
#ms
#Simple: Init
@performance_1015_td
#719
#ms
@performance_1016_td
#1344
#719
@performance_1017_td
#2906
#1344
@performance_1018_td
#Simple: Query (random)
#2906
@performance_1019_td
#ms
#Simple: Query (random)
@performance_1020_td
#328
#ms
@performance_1021_td
#328
@performance_1022_td
#1578
#328
@performance_1023_td
#Simple: Query (sequential)
#1578
@performance_1024_td
#ms
#Simple: Query (sequential)
@performance_1025_td
#250
#ms
@performance_1026_td
#250
@performance_1027_td
#1484
#250
@performance_1028_td
#Simple: Update (random)
#1484
@performance_1029_td
#ms
#Simple: Update (random)
@performance_1030_td
#688
#ms
@performance_1031_td
#1828
#688
@performance_1032_td
#14922
#1828
@performance_1033_td
#Simple: Delete (sequential)
#14922
@performance_1034_td
#ms
#Simple: Delete (sequential)
@performance_1035_td
#203
#ms
@performance_1036_td
#265
#203
@performance_1037_td
#10235
#265
@performance_1038_td
#Simple: Memory Usage
#10235
@performance_1039_td
#MB
#Simple: Memory Usage
@performance_1040_td
#6
#MB
@performance_1041_td
#9
#6
@performance_1042_td
#11
#9
@performance_1043_td
#BenchA: Init
#11
@performance_1044_td
#ms
#BenchA: Init
@performance_1045_td
#422
#ms
@performance_1046_td
#672
#422
@performance_1047_td
#4328
#672
@performance_1048_td
#BenchA: Transactions
#4328
@performance_1049_td
#ms
#BenchA: Transactions
@performance_1050_td
#6969
#ms
@performance_1051_td
#3531
#6969
@performance_1052_td
#16719
#3531
@performance_1053_td
#BenchA: Memory Usage
#16719
@performance_1054_td
#MB
#BenchA: Memory Usage
@performance_1055_td
#10
#MB
@performance_1056_td
#10
@performance_1057_td
#9
#10
@performance_1058_td
#BenchB: Init
#9
@performance_1059_td
#ms
#BenchB: Init
@performance_1060_td
#1703
#ms
@performance_1061_td
#3937
#1703
@performance_1062_td
#13844
#3937
@performance_1063_td
#BenchB: Transactions
#13844
@performance_1064_td
#ms
#BenchB: Transactions
@performance_1065_td
#2360
#ms
@performance_1066_td
#1328
#2360
@performance_1067_td
#5797
#1328
@performance_1068_td
#BenchB: Memory Usage
#5797
@performance_1069_td
#MB
#BenchB: Memory Usage
@performance_1070_td
#8
#MB
@performance_1071_td
#9
#8
@performance_1072_td
#8
#9
@performance_1073_td
#BenchC: Init
#8
@performance_1074_td
#ms
#BenchC: Init
@performance_1075_td
#718
#ms
@performance_1076_td
#468
#718
@performance_1077_td
#5328
#468
@performance_1078_td
#BenchC: Transactions
#5328
@performance_1079_td
#ms
#BenchC: Transactions
@performance_1080_td
#2688
#ms
@performance_1081_td
#60828
#2688
@performance_1082_td
#7109
#60828
@performance_1083_td
#BenchC: Memory Usage
#7109
@performance_1084_td
#MB
#BenchC: Memory Usage
@performance_1085_td
#10
#MB
@performance_1086_td
#14
#10
@performance_1087_td
#9
#14
@performance_1088_td
#Executed Statements
#9
@performance_1089_td
##
#Executed Statements ###
@performance_1090_td
#594255
##
@performance_1091_td
#594255
......@@ -5692,382 +5698,382 @@ Derby
#594255
@performance_1093_td
#Total Time
#594255
@performance_1094_td
#ms
#Total Time
@performance_1095_td
#17048
#ms
@performance_1096_td
#74779
#17048
@performance_1097_td
#84250
#74779
@performance_1098_td
#Statement per Second
#84250
@performance_1099_td
##
#Statement per Second ###
@performance_1100_td
#34857
##
@performance_1101_td
#7946
#34857
@performance_1102_td
#7946
@performance_1103_td
#7053
@performance_1103_h3
@performance_1104_h3
#Client-Server
@performance_1104_th
#Test Case
@performance_1105_th
#Unit
#Test Case
@performance_1106_th
H2
#Unit #H2
@performance_1107_th
HSQLDB
H2
@performance_1108_th
Derby
HSQLDB
@performance_1109_th
PostgreSQL
Derby
@performance_1110_th
PostgreSQL
@performance_1111_th
MySQL
@performance_1111_td
@performance_1112_td
#Simple: Init
@performance_1112_td
@performance_1113_td
#ms
@performance_1113_td
@performance_1114_td
#2516
@performance_1114_td
@performance_1115_td
#3109
@performance_1115_td
@performance_1116_td
#7078
@performance_1116_td
@performance_1117_td
#4625
@performance_1117_td
@performance_1118_td
#2859
@performance_1118_td
@performance_1119_td
#Simple: Query (random)
@performance_1119_td
@performance_1120_td
#ms
@performance_1120_td
@performance_1121_td
#2890
@performance_1121_td
@performance_1122_td
#2547
@performance_1122_td
@performance_1123_td
#8843
@performance_1123_td
@performance_1124_td
#7703
@performance_1124_td
@performance_1125_td
#3203
@performance_1125_td
@performance_1126_td
#Simple: Query (sequential)
@performance_1126_td
@performance_1127_td
#ms
@performance_1127_td
@performance_1128_td
#2953
@performance_1128_td
@performance_1129_td
#2407
@performance_1129_td
@performance_1130_td
#8516
@performance_1130_td
@performance_1131_td
#6953
@performance_1131_td
@performance_1132_td
#3516
@performance_1132_td
@performance_1133_td
#Simple: Update (random)
@performance_1133_td
@performance_1134_td
#ms
@performance_1134_td
@performance_1135_td
#3141
@performance_1135_td
@performance_1136_td
#3671
@performance_1136_td
@performance_1137_td
#18125
@performance_1137_td
@performance_1138_td
#7797
@performance_1138_td
#4687
@performance_1139_td
#Simple: Delete (sequential)
#4687
@performance_1140_td
#ms
#Simple: Delete (sequential)
@performance_1141_td
#1000
#ms
@performance_1142_td
#1219
#1000
@performance_1143_td
#12891
#1219
@performance_1144_td
#3547
#12891
@performance_1145_td
#1938
#3547
@performance_1146_td
#Simple: Memory Usage
#1938
@performance_1147_td
#MB
#Simple: Memory Usage
@performance_1148_td
#6
#MB
@performance_1149_td
#10
#6
@performance_1150_td
#14
#10
@performance_1151_td
#0
#14
@performance_1152_td
#1
#0
@performance_1153_td
#BenchA: Init
#1
@performance_1154_td
#ms
#BenchA: Init
@performance_1155_td
#2266
#ms
@performance_1156_td
#2484
#2266
@performance_1157_td
#7797
#2484
@performance_1158_td
#4234
#7797
@performance_1159_td
#4703
#4234
@performance_1160_td
#BenchA: Transactions
#4703
@performance_1161_td
#ms
#BenchA: Transactions
@performance_1162_td
#11078
#ms
@performance_1163_td
#8875
#11078
@performance_1164_td
#26328
#8875
@performance_1165_td
#18641
#26328
@performance_1166_td
#11187
#18641
@performance_1167_td
#BenchA: Memory Usage
#11187
@performance_1168_td
#MB
#BenchA: Memory Usage
@performance_1169_td
#8
#MB
@performance_1170_td
#13
#8
@performance_1171_td
#10
#13
@performance_1172_td
#0
#10
@performance_1173_td
#1
#0
@performance_1174_td
#BenchB: Init
#1
@performance_1175_td
#ms
#BenchB: Init
@performance_1176_td
#8422
#ms
@performance_1177_td
#12531
#8422
@performance_1178_td
#27734
#12531
@performance_1179_td
#18609
#27734
@performance_1180_td
#12312
#18609
@performance_1181_td
#BenchB: Transactions
#12312
@performance_1182_td
#ms
#BenchB: Transactions
@performance_1183_td
#4125
#ms
@performance_1184_td
#3344
#4125
@performance_1185_td
#7875
#3344
@performance_1186_td
#7922
#7875
@performance_1187_td
#3266
#7922
@performance_1188_td
#BenchB: Memory Usage
#3266
@performance_1189_td
#MB
#BenchB: Memory Usage
@performance_1190_td
#9
#MB
@performance_1191_td
#10
#9
@performance_1192_td
#8
#10
@performance_1193_td
#0
#8
@performance_1194_td
#1
#0
@performance_1195_td
#BenchC: Init
#1
@performance_1196_td
#ms
#BenchC: Init
@performance_1197_td
#1781
#ms
@performance_1198_td
#1609
#1781
@performance_1199_td
#6797
#1609
@performance_1200_td
#2453
#6797
@performance_1201_td
#3328
#2453
@performance_1202_td
#BenchC: Transactions
#3328
@performance_1203_td
#ms
#BenchC: Transactions
@performance_1204_td
#8453
#ms
@performance_1205_td
#62469
#8453
@performance_1206_td
#19859
#62469
@performance_1207_td
#11516
#19859
@performance_1208_td
#7062
#11516
@performance_1209_td
#BenchC: Memory Usage
#7062
@performance_1210_td
#MB
#BenchC: Memory Usage
@performance_1211_td
#10
#MB
@performance_1212_td
#15
#10
@performance_1213_td
#9
#15
@performance_1214_td
#0
#9
@performance_1215_td
#1
#0
@performance_1216_td
#Executed Statements
#1
@performance_1217_td
##
#Executed Statements ###
@performance_1218_td
#594255
##
@performance_1219_td
#594255
......@@ -6082,543 +6088,567 @@ MySQL
#594255
@performance_1223_td
#Total Time
#594255
@performance_1224_td
#ms
#Total Time
@performance_1225_td
#48625
#ms
@performance_1226_td
#104265
#48625
@performance_1227_td
#151843
#104265
@performance_1228_td
#94000
#151843
@performance_1229_td
#58061
#94000
@performance_1230_td
#Statement per Second
#58061
@performance_1231_td
##
#Statement per Second ###
@performance_1232_td
#12221
##
@performance_1233_td
#5699
#12221
@performance_1234_td
#3913
#5699
@performance_1235_td
#6321
#3913
@performance_1236_td
#6321
@performance_1237_td
#10235
@performance_1237_h3
@performance_1238_h3
#Benchmark Results and Comments
@performance_1238_h4
@performance_1239_h4
H2
@performance_1239_p
@performance_1240_p
#Version 1.0.67 (2008-02-22) was used for the test. For simpler operations, the performance of H2 is about the same as for HSQLDB. For more complex queries, the query optimizer is very important. However H2 is not very fast in every case, certain kind of queries may still be slow. One situation where is H2 is slow is large result sets, because they are buffered to disk if more than a certain number of records are returned. The advantage of buffering is, there is no limit on the result set size. The open/close time is almost fixed, because of the file locking protocol: The engine waits 20 ms after opening a database to ensure the database files are not opened by another process.
@performance_1240_h4
@performance_1241_h4
HSQLDB
@performance_1241_p
@performance_1242_p
#Version 1.8.0.8 was used for the test. Cached tables are used in this test (hsqldb.default_table_type=cached), and the write delay is 1 second (SET WRITE_DELAY 1). HSQLDB is fast when using simple operations. HSQLDB is very slow in the last test (BenchC: Transactions), probably because is has a bad query optimizer. One query where HSQLDB is slow is a two-table join:
@performance_1242_p
@performance_1243_p
#The PolePosition benchmark also shows that the query optimizer does not do a very good job for some queries. A disadvantage in HSQLDB is the slow startup / shutdown time (currently not listed) when using bigger databases. The reason is, a backup of the database is created whenever the database is opened or closed.
@performance_1243_h4
@performance_1244_h4
Derby
@performance_1244_p
@performance_1245_p
#Version 10.3.1.4 was used for the test. Derby is clearly the slowest embedded database in this test. This seems to be a structural problem, because all operations are really slow. It will not be easy for the developers of Derby to improve the performance to a reasonable level. A few problems have been identified: Leaving autocommit on is a problem for Derby. If it is switched off during the whole test, the results are about 20% better for Derby.
@performance_1245_h4
@performance_1246_h4
PostgreSQL
@performance_1246_p
@performance_1247_p
#Version 8.1.4 was used for the test. The following options where changed in postgresql.conf: fsync = off, commit_delay = 1000. PostgreSQL is run in server mode. It looks like the base performance is slower than MySQL, the reason could be the network layer. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
@performance_1247_h4
@performance_1248_h4
MySQL
@performance_1248_p
@performance_1249_p
#Version 5.0.22 was used for the test. MySQL was run with the InnoDB backend. The setting innodb_flush_log_at_trx_commit (found in the my.ini file) was set to 0. Otherwise (and by default), MySQL is really slow (around 140 statements per second in this test) because it tries to flush the data to disk for each commit. For small transactions (when autocommit is on) this is really slow. But many use cases use small or relatively small transactions. Too bad this setting is not listed in the configuration wizard, and it always overwritten when using the wizard. You need to change this setting manually in the file my.ini, and then restart the service. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
@performance_1249_h4
@performance_1250_h4
#Firebird
@performance_1250_p
@performance_1251_p
#Firebird 1.5 (default installation) was tested, but the results are not published currently. It is possible to run the performance test with the Firebird database, and any information on how to configure Firebird for higher performance are welcome.
@performance_1251_h4
@performance_1252_h4
#Why Oracle / MS SQL Server / DB2 are Not Listed
@performance_1252_p
@performance_1253_p
#The license of these databases does not allow to publish benchmark results. This doesn't mean that they are fast. They are in fact quite slow, and need a lot of memory. But you will need to test this yourself. SQLite was not tested because the JDBC driver doesn't support transactions.
@performance_1253_h3
@performance_1254_h3
#About this Benchmark
@performance_1254_h4
@performance_1255_h4
#Number of Connections
@performance_1255_p
@performance_1256_p
#This is mostly a single-connection benchmark. BenchB uses multiple connections; the other tests use one connection.
@performance_1256_h4
@performance_1257_h4
#Real-World Tests
@performance_1257_p
@performance_1258_p
#Good benchmarks emulate real-world use cases. This benchmark includes 3 test cases: A simple test case with one table and many small updates / deletes. BenchA is similar to the TPC-A test, but single connection / single threaded (see also: www.tpc.org). BenchB is similar to the TPC-B test, using multiple connections (one thread per connection). BenchC is similar to the TPC-C test, but single connection / single threaded.
@performance_1258_h4
@performance_1259_h4
#Comparing Embedded with Server Databases
@performance_1259_p
@performance_1260_p
#This is mainly a benchmark for embedded databases (where the application runs in the same virtual machine than the database engine). However MySQL and PostgreSQL are not Java databases and cannot be embedded into a Java application. For the Java databases, both embedded and server modes are tested.
@performance_1260_h4
@performance_1261_h4
#Test Platform
@performance_1261_p
@performance_1262_p
#This test is run on Windows XP with the virus scanner switched off. The VM used is Sun JDK 1.5.
@performance_1262_h4
@performance_1263_h4
#Multiple Runs
@performance_1263_p
@performance_1264_p
#When a Java benchmark is run first, the code is not fully compiled and therefore runs slower than when running multiple times. A benchmark should always run the same test multiple times and ignore the first run(s). This benchmark runs three times, but only the last run is measured.
@performance_1264_h4
@performance_1265_h4
#Memory Usage
@performance_1265_p
@performance_1266_p
#It is not enough to measure the time taken, the memory usage is important as well. Performance can be improved in databases by using a bigger in-memory cache, but there is only a limited amount of memory available on the system. HSQLDB tables are kept fully in memory by default; this benchmark uses 'disk based' tables for all databases. Unfortunately, it is not so easy to calculate the memory usage of PostgreSQL and MySQL, because they run in a different process than the test. This benchmark currently does not print memory usage of those databases.
@performance_1266_h4
@performance_1267_h4
#Delayed Operations
@performance_1267_p
@performance_1268_p
#Some databases delay some operations (for example flushing the buffers) until after the benchmark is run. This benchmark waits between each database tested, and each database runs in a different process (sequentially).
@performance_1268_h4
@performance_1269_h4
#Transaction Commit / Durability
@performance_1269_p
@performance_1270_p
#Durability means transaction committed to the database will not be lost. Some databases (for example MySQL) try to enforce this by default by calling fsync() to flush the buffers, but most hard drives don't actually flush all data. Calling fsync() slows down transaction commit a lot, but doesn't always make data durable. When comparing the results, it is important to think about the effect. Many database suggest to 'batch' operations when possible. This benchmark switches off autocommit when loading the data, and calls commit after each 1000 inserts. However many applications need 'short' transactions at runtime (a commit after each update). This benchmark commits after each update / delete in the simple benchmark, and after each business transaction in the other benchmarks. For databases that support delayed commits, a delay of one second is used.
@performance_1270_h4
@performance_1271_h4
#Using Prepared Statements
@performance_1271_p
@performance_1272_p
#Wherever possible, the test cases use prepared statements.
@performance_1272_h4
@performance_1273_h4
#Currently Not Tested: Startup Time
@performance_1273_p
@performance_1274_p
#The startup time of a database engine is important as well for embedded use. This time is not measured currently. Also, not tested is the time used to create a database and open an existing database. Here, one (wrapper) connection is opened at the start, and for each step a new connection is opened and then closed. That means the Open/Close time listed is for opening a connection if the database is already in use.
@performance_1274_h2
@performance_1275_h2
#PolePosition Benchmark
@performance_1275_p
@performance_1276_p
#The PolePosition is an open source benchmark. The algorithms are all quite simple. It was developed / sponsored by db4o.
@performance_1276_th
#Test Case
@performance_1277_th
#Unit
#Test Case
@performance_1278_th
H2
#Unit #H2
@performance_1279_th
HSQLDB
H2
@performance_1280_th
HSQLDB
@performance_1281_th
MySQL
@performance_1281_td
@performance_1282_td
#Melbourne write
@performance_1282_td
@performance_1283_td
#ms
@performance_1283_td
@performance_1284_td
#369
@performance_1284_td
@performance_1285_td
#249
@performance_1285_td
@performance_1286_td
#2022
@performance_1286_td
@performance_1287_td
#Melbourne read
@performance_1287_td
@performance_1288_td
#ms
@performance_1288_td
@performance_1289_td
#47
@performance_1289_td
@performance_1290_td
#49
@performance_1290_td
@performance_1291_td
#93
@performance_1291_td
@performance_1292_td
#Melbourne read_hot
@performance_1292_td
@performance_1293_td
#ms
@performance_1293_td
@performance_1294_td
#24
@performance_1294_td
@performance_1295_td
#43
@performance_1295_td
@performance_1296_td
#95
@performance_1296_td
@performance_1297_td
#Melbourne delete
@performance_1297_td
@performance_1298_td
#ms
@performance_1298_td
@performance_1299_td
#147
@performance_1299_td
@performance_1300_td
#133
@performance_1300_td
@performance_1301_td
#176
@performance_1301_td
@performance_1302_td
#Sepang write
@performance_1302_td
@performance_1303_td
#ms
@performance_1303_td
@performance_1304_td
#965
@performance_1304_td
@performance_1305_td
#1201
@performance_1305_td
@performance_1306_td
#3213
@performance_1306_td
@performance_1307_td
#Sepang read
@performance_1307_td
@performance_1308_td
#ms
@performance_1308_td
@performance_1309_td
#765
@performance_1309_td
@performance_1310_td
#948
@performance_1310_td
@performance_1311_td
#3455
@performance_1311_td
@performance_1312_td
#Sepang read_hot
@performance_1312_td
@performance_1313_td
#ms
@performance_1313_td
@performance_1314_td
#789
@performance_1314_td
@performance_1315_td
#859
@performance_1315_td
@performance_1316_td
#3563
@performance_1316_td
@performance_1317_td
#Sepang delete
@performance_1317_td
@performance_1318_td
#ms
@performance_1318_td
@performance_1319_td
#1384
@performance_1319_td
@performance_1320_td
#1596
@performance_1320_td
@performance_1321_td
#6214
@performance_1321_td
@performance_1322_td
#Bahrain write
@performance_1322_td
@performance_1323_td
#ms
@performance_1323_td
@performance_1324_td
#1186
@performance_1324_td
@performance_1325_td
#1387
@performance_1325_td
@performance_1326_td
#6904
@performance_1326_td
@performance_1327_td
#Bahrain query_indexed_string
@performance_1327_td
@performance_1328_td
#ms
@performance_1328_td
@performance_1329_td
#336
@performance_1329_td
@performance_1330_td
#170
@performance_1330_td
@performance_1331_td
#693
@performance_1331_td
@performance_1332_td
#Bahrain query_string
@performance_1332_td
@performance_1333_td
#ms
@performance_1333_td
@performance_1334_td
#18064
@performance_1334_td
@performance_1335_td
#39703
@performance_1335_td
@performance_1336_td
#41243
@performance_1336_td
@performance_1337_td
#Bahrain query_indexed_int
@performance_1337_td
@performance_1338_td
#ms
@performance_1338_td
@performance_1339_td
#104
@performance_1339_td
@performance_1340_td
#134
@performance_1340_td
@performance_1341_td
#678
@performance_1341_td
@performance_1342_td
#Bahrain update
@performance_1342_td
@performance_1343_td
#ms
@performance_1343_td
@performance_1344_td
#191
@performance_1344_td
@performance_1345_td
#87
@performance_1345_td
@performance_1346_td
#159
@performance_1346_td
@performance_1347_td
#Bahrain delete
@performance_1347_td
@performance_1348_td
#ms
@performance_1348_td
@performance_1349_td
#1215
@performance_1349_td
@performance_1350_td
#729
@performance_1350_td
@performance_1351_td
#6812
@performance_1351_td
@performance_1352_td
#Imola retrieve
@performance_1352_td
@performance_1353_td
#ms
@performance_1353_td
@performance_1354_td
#198
@performance_1354_td
@performance_1355_td
#194
@performance_1355_td
@performance_1356_td
#4036
@performance_1356_td
@performance_1357_td
#Barcelona write
@performance_1357_td
@performance_1358_td
#ms
@performance_1358_td
@performance_1359_td
#413
@performance_1359_td
@performance_1360_td
#832
@performance_1360_td
@performance_1361_td
#3191
@performance_1361_td
@performance_1362_td
#Barcelona read
@performance_1362_td
@performance_1363_td
#ms
@performance_1363_td
@performance_1364_td
#119
@performance_1364_td
@performance_1365_td
#160
@performance_1365_td
@performance_1366_td
#1177
@performance_1366_td
@performance_1367_td
#Barcelona query
@performance_1367_td
@performance_1368_td
#ms
@performance_1368_td
@performance_1369_td
#20
@performance_1369_td
@performance_1370_td
#5169
@performance_1370_td
@performance_1371_td
#101
@performance_1371_td
@performance_1372_td
#Barcelona delete
@performance_1372_td
@performance_1373_td
#ms
@performance_1373_td
@performance_1374_td
#388
@performance_1374_td
@performance_1375_td
#319
@performance_1375_td
@performance_1376_td
#3287
@performance_1376_td
@performance_1377_td
#Total
@performance_1377_td
@performance_1378_td
#ms
@performance_1378_td
@performance_1379_td
#26724
@performance_1379_td
@performance_1380_td
#53962
@performance_1380_td
@performance_1381_td
#87112
@performance_1381_h2
@performance_1382_h2
#Application Profiling
@performance_1382_h3
@performance_1383_h3
#Analyze First
@performance_1383_p
#Before trying to optimize the performance, it is important to know where the time is actually spent. The same is true for memory problems. Premature or 'blind' optimization should be avoided, as it is not an efficient way to solve the problem. There are various ways to analyze the application. In some situations it is possible to compare two implementations and use System.currentTimeMillis() to find out which one is faster. But this does not work for complex applications with many modules, and for memory problems. A very good tool to measure both the memory and the CPU is the <a href="http://www.yourkit.com">YourKit Java Profiler</a> . This tool is also used to optimize the performance and memory footprint of this database engine.
@performance_1384_p
#Before trying to optimize the performance, it is important to know where the time is actually spent. The same is true for memory problems. Premature or 'blind' optimization should be avoided, as it is not an efficient way to solve the problem. There are various ways to analyze the application. In some situations it is possible to compare two implementations and use System.currentTimeMillis() to find out which one is faster. But this does not work for complex applications with many modules, and for memory problems.
@performance_1385_p
#A very good tool to measure both the memory and the CPU is the <a href="http://www.yourkit.com">YourKit Java Profiler</a> . This tool is also used to optimize the performance and memory footprint of this database engine.
@performance_1386_p
#A simple way to profile an application is to use the built-in profiling tool of java. Example:
@performance_1387_p
#Unfortunately, it is only possible to profile the application from start to end.
@performance_1388_h2
#Database Profiling
@performance_1389_p
#The ConvertTraceFile tool generates SQL statement statistics at the end of the SQL script file. The format used is similar to the profiling data generated when using java -Xrunhprof. As an example, execute the the following script using the H2 Console:
@performance_1390_p
#Now convert the .trace.db file using the ConvertTraceFile tool:
@performance_1391_p
#The generated file <code>test.sql</code> will contain the SQL statements as well as the following profiling data (results vary):
@performance_1384_h2
@performance_1392_h2
#Database Performance Tuning
@performance_1385_h3
@performance_1393_h3
#Virus Scanners
@performance_1386_p
@performance_1394_p
#Some virus scanners scan files every time they are accessed. It is very important for performance that database files are not scanned for viruses. The database engine does never interprets the data stored in the files as programs, that means even if somebody would store a virus in a database file, this would be harmless (when the virus does not run, it cannot spread). Some virus scanners allow excluding file endings. Make sure files ending with .db are not scanned.
@performance_1387_h3
@performance_1395_h3
トレースオプションを使用する
@performance_1388_p
@performance_1396_p
#If the main performance hot spots are in the database engine, in many cases the performance can be optimized by creating additional indexes, or changing the schema. Sometimes the application does not directly generate the SQL statements, for example if an O/R mapping tool is used. To view the SQL statements and JDBC API calls, you can use the trace options. For more information, see <a href="features.html#trace_options">Using the Trace Options</a> .
@performance_1389_h3
@performance_1397_h3
#Index Usage
@performance_1390_p
@performance_1398_p
#This database uses indexes to improve the performance of SELECT, UPDATE and DELETE statements. If a column is used in the WHERE clause of a query, and if an index exists on this column, then the index can be used. Multi-column indexes are used if all or the first columns of the index are used. Both equality lookup and range scans are supported. Indexes are not used to order result sets: The results are sorted in memory if required. Indexes are created automatically for primary key and unique constraints. Indexes are also created for foreign key constraints, if required. For other columns, indexes need to be created manually using the CREATE INDEX statement.
@performance_1391_h3
@performance_1399_h3
#Optimizer
@performance_1392_p
@performance_1400_p
#This database uses a cost based optimizer. For simple and queries and queries with medium complexity (less than 7 tables in the join), the expected cost (running time) of all possible plans is calculated, and the plan with the lowest cost is used. For more complex queries, the algorithm first tries all possible combinations for the first few tables, and the remaining tables added using a greedy algorithm (this works well for most joins). Afterwards a genetic algorithm is used to test at most 2000 distinct plans. Only left-deep plans are evaluated.
@performance_1393_h3
@performance_1401_h3
#Expression Optimization
@performance_1394_p
@performance_1402_p
#After the statement is parsed, all expressions are simplified automatically if possible. Operations are evaluated only once if all parameters are constant. Functions are also optimized, but only if the function is constant (always returns the same result for the same parameter values). If the WHERE clause is always false, then the table is not accessed at all.
@performance_1395_h3
@performance_1403_h3
#COUNT(*) Optimization
@performance_1396_p
@performance_1404_p
#If the query only counts all rows of a table, then the data is not accessed. However, this is only possible if no WHERE clause is used, that means it only works for queries of the form SELECT COUNT(*) FROM table.
@performance_1397_h3
@performance_1405_h3
#Updating Optimizer Statistics / Column Selectivity
@performance_1398_p
@performance_1406_p
#When executing a query, at most one index per joined table can be used. If the same table is joined multiple times, for each join only one index is used. Example: for the query SELECT * FROM TEST T1, TEST T2 WHERE T1.NAME='A' AND T2.ID=T1.ID, two index can be used, in this case the index on NAME for T1 and the index on ID for T2.
@performance_1399_p
@performance_1407_p
#If a table has multiple indexes, sometimes more than one index could be used. Example: if there is a table TEST(ID, NAME, FIRSTNAME) and an index on each column, then two indexes could be used for the query SELECT * FROM TEST WHERE NAME='A' AND FIRSTNAME='B', the index on NAME or the index on FIRSTNAME. It is not possible to use both indexes at the same time. Which index is used depends on the selectivity of the column. The selectivity describes the 'uniqueness' of values in a column. A selectivity of 100 means each value appears only once, and a selectivity of 1 means the same value appears in many or most rows. For the query above, the index on NAME should be used if the table contains more distinct names than first names.
@performance_1400_p
@performance_1408_p
#The SQL statement ANALYZE can be used to automatically estimate the selectivity of the columns in the tables. This command should be run from time to time to improve the query plans generated by the optimizer.
@performance_1401_h3
@performance_1409_h3
#Optimization Examples
@performance_1402_p
@performance_1410_p
#See <code>src/test/org/h2/samples/optimizations.sql</code> for a few examples of queries that benefit from special optimizations built into the database.
@quickstart_1000_h1
......@@ -7393,387 +7423,390 @@ SQLコマンドがコマンドエリアに表示されます。
#Support EXEC[UTE] (doesn't return a result set, compatible to MS SQL Server)
@roadmap_1224_li
#GROUP BY and DISTINCT: support large groups (buffer to disk), do not keep large sets in memory
#Support native XML data type
@roadmap_1225_li
#Support native XML data type
#Support triggers with a string property or option: SpringTrigger, OSGITrigger
@roadmap_1226_li
#Support triggers with a string property or option: SpringTrigger, OSGITrigger
#Clustering: adding a node should be very fast and without interrupting clients (very short lock)
@roadmap_1227_li
#Clustering: adding a node should be very fast and without interrupting clients (very short lock)
#Support materialized views (using triggers)
@roadmap_1228_li
#Support materialized views (using triggers)
#Store dates in local time zone (portability of database files)
@roadmap_1229_li
#Store dates in local time zone (portability of database files)
#Ability to resize the cache array when resizing the cache
@roadmap_1230_li
#Ability to resize the cache array when resizing the cache
#Time based cache writing (one second after writing the log)
@roadmap_1231_li
#Time based cache writing (one second after writing the log)
#Check state of H2 driver for DDLUtils: https://issues.apache.org/jira/browse/DDLUTILS-185
@roadmap_1232_li
#Check state of H2 driver for DDLUtils: https://issues.apache.org/jira/browse/DDLUTILS-185
#Index usage for REGEXP LIKE.
@roadmap_1233_li
#Index usage for REGEXP LIKE.
#Add a role DBA (like ADMIN).
@roadmap_1234_li
#Add a role DBA (like ADMIN).
#Better support multiple processors for in-memory databases.
@roadmap_1235_li
#Better support multiple processors for in-memory databases.
#Access rights: remember the owner of an object. COMMENT: allow owner of object to change it.
@roadmap_1236_li
#Access rights: remember the owner of an object. COMMENT: allow owner of object to change it.
#Implement INSTEAD OF trigger.
@roadmap_1237_li
#Implement INSTEAD OF trigger.
#Access rights: Finer grained access control (grant access for specific functions)
@roadmap_1238_li
#Access rights: Finer grained access control (grant access for specific functions)
#Support N'text'
@roadmap_1239_li
#Support N'text'
#Support SCOPE_IDENTITY() to avoid problems when inserting rows in a trigger
@roadmap_1240_li
#Support SCOPE_IDENTITY() to avoid problems when inserting rows in a trigger
#Set a connection read only (Connection.setReadOnly)
@roadmap_1241_li
#Set a connection read only (Connection.setReadOnly)
#In MySQL mode, for AUTO_INCREMENT columns, don't set the primary key
@roadmap_1242_li
#In MySQL mode, for AUTO_INCREMENT columns, don't set the primary key
#Use JDK 1.4 file locking to create the lock file (but not yet by default); writing a system property to detect concurrent access from the same VM (different classloaders).
@roadmap_1243_li
#Use JDK 1.4 file locking to create the lock file (but not yet by default); writing a system property to detect concurrent access from the same VM (different classloaders).
#Support compatibility for jdbc:hsqldb:res:
@roadmap_1244_li
#Support compatibility for jdbc:hsqldb:res:
#In the MySQL and PostgreSQL, use lower case identifiers by default (DatabaseMetaData.storesLowerCaseIdentifiers = true)
@roadmap_1245_li
#In the MySQL and PostgreSQL, use lower case identifiers by default (DatabaseMetaData.storesLowerCaseIdentifiers = true)
#Provide a simple, lightweight O/R mapping tool
@roadmap_1246_li
#Provide a simple, lightweight O/R mapping tool
#Provide an Java SQL builder with standard and H2 syntax
@roadmap_1247_li
#Provide an Java SQL builder with standard and H2 syntax
#Trace: write OS, file system, JVM,... when opening the database
@roadmap_1248_li
#Trace: write OS, file system, JVM,... when opening the database
#Support indexes for views (probably requires materialized views)
@roadmap_1249_li
#Support indexes for views (probably requires materialized views)
#Document SET SEARCH_PATH, BEGIN, EXECUTE, parameters
@roadmap_1250_li
#Document SET SEARCH_PATH, BEGIN, EXECUTE, parameters
#Browser: use Desktop.isDesktopSupported and browse when using JDK 1.6
@roadmap_1251_li
#Browser: use Desktop.isDesktopSupported and browse when using JDK 1.6
#Server: use one listener (detect if the request comes from an PG or TCP client)
@roadmap_1252_li
#Server: use one listener (detect if the request comes from an PG or TCP client)
#Store dates as 'local'. Existing files use GMT. Use escape syntax for compatibility.
@roadmap_1253_li
#Store dates as 'local'. Existing files use GMT. Use escape syntax for compatibility.
#Support data type INTERVAL
@roadmap_1254_li
#Support data type INTERVAL
#NATURAL JOIN: MySQL and PostgreSQL don't repeat columns when using SELECT * ...
@roadmap_1255_li
#NATURAL JOIN: MySQL and PostgreSQL don't repeat columns when using SELECT * ...
#Optimize SELECT MIN(ID), MAX(ID), COUNT(*) FROM TEST WHERE ID BETWEEN 100 AND 200
@roadmap_1256_li
#Optimize SELECT MIN(ID), MAX(ID), COUNT(*) FROM TEST WHERE ID BETWEEN 100 AND 200
#Support Oracle functions: TRUNC, NVL2, TO_CHAR, TO_DATE, TO_NUMBER
@roadmap_1257_li
#Support Oracle functions: TRUNC, NVL2, TO_CHAR, TO_DATE, TO_NUMBER
#Sequence: PostgreSQL compatibility (rename, create) (http://www.postgresql.org/docs/8.2/static/sql-altersequence.html)
@roadmap_1258_li
#Sequence: PostgreSQL compatibility (rename, create) (http://www.postgresql.org/docs/8.2/static/sql-altersequence.html)
#DISTINCT: Support large result sets by sorting on all columns (additionally) and then removing duplicates.
@roadmap_1259_li
#DISTINCT: Support large result sets by sorting on all columns (additionally) and then removing duplicates.
#File system that writes to two file systems (replicating file system)
@roadmap_1260_li
#File system that writes to two file systems (replicating file system)
#File system with a background writer thread; test if this is faster
@roadmap_1261_li
#File system with a background writer thread; test if this is faster
#FTP access to a database (.csv for a table, a directory for a schema, a file for a lob, a script.sql file).
@roadmap_1262_li
#FTP access to a database (.csv for a table, a directory for a schema, a file for a lob, a script.sql file).
#LIMIT and OFFSET for GROUP_CONCAT
@roadmap_1263_li
#LIMIT and OFFSET for GROUP_CONCAT
#Support triggers for INFORMATION_SCHEMA tables (to better support PostgreSQL catalog: rebuild after creating new tables)
@roadmap_1264_li
#Support triggers for INFORMATION_SCHEMA tables (to better support PostgreSQL catalog: rebuild after creating new tables)
#Better document the source code
@roadmap_1265_li
#Better document the source code
#Support select * from dual a left join dual b on b.x=(select max(x) from dual)
@roadmap_1266_li
#Support select * from dual a left join dual b on b.x=(select max(x) from dual)
#Optimization: don't lock when the database is read-only
@roadmap_1267_li
#Optimization: don't lock when the database is read-only
#Integrate spatial functions from http://geosysin.iict.ch/irstv-trac/wiki/H2spatial/Download
@roadmap_1268_li
#Integrate spatial functions from http://geosysin.iict.ch/irstv-trac/wiki/H2spatial/Download
#Support COSH, SINH, and TANH functions
@roadmap_1269_li
#Support COSH, SINH, and TANH functions
#Native search: support "phrase search", wildcard search (* and ?), case-insensitive search, boolean operators, and grouping
@roadmap_1270_li
#Native search: support "phrase search", wildcard search (* and ?), case-insensitive search, boolean operators, and grouping
#Improve documentation of access rights
@roadmap_1271_li
#Improve documentation of access rights
#Support ENUM data type (see MySQL, PostgreSQL, MS SQL Server, maybe others)
@roadmap_1272_li
#Support ENUM data type (see MySQL, PostgreSQL, MS SQL Server, maybe others)
#Command line option for the H2 Console and TCP configuration (which .h2.server.properties and .h2.keystore to use)
@roadmap_1273_li
#Command line option for the H2 Console and TCP configuration (which .h2.server.properties and .h2.keystore to use)
#Support a schema name for Java functions
@roadmap_1274_li
#Support a schema name for Java functions
#Remember the domain of a column
@roadmap_1275_li
#Remember the domain of a column
#Support Jackcess (MS Access databases)
@roadmap_1276_li
#Support Jackcess (MS Access databases)
#Built-in methods to write large objects (BLOB and CLOB): FILE_WRITE('test.txt', 'Hello World')
@roadmap_1277_li
#Built-in methods to write large objects (BLOB and CLOB): FILE_WRITE('test.txt', 'Hello World')
#Change package name in version 2.0: org.h2database
@roadmap_1278_li
#Change package name in version 2.0: org.h2database
#MVCC: support transactionally consistent backups using SCRIPT
@roadmap_1279_li
#MVCC: support transactionally consistent backups using SCRIPT
#Improve time to open large databases (see mail 'init time for distributed setup')
@roadmap_1280_li
#Improve time to open large databases (see mail 'init time for distributed setup')
#Use ARRAY for fulltext search return value, at least internally in the native implementation (and as an option for the user)
@roadmap_1281_li
#Use ARRAY for fulltext search return value, at least internally in the native implementation (and as an option for the user)
#Move Maven 2 repository from hsql.sf.net to h2database.sf.net
@roadmap_1282_li
#Move Maven 2 repository from hsql.sf.net to h2database.sf.net
#Java 1.5 tool: JdbcUtils.closeSilently(s1, s2,...)
@roadmap_1283_li
#Java 1.5 tool: JdbcUtils.closeSilently(s1, s2,...)
#Javadoc: document design patterns used
@roadmap_1284_li
#Javadoc: document design patterns used
#Triggers for metadata tables; use for PostgreSQL catalog
@roadmap_1285_li
#Triggers for metadata tables; use for PostgreSQL catalog
#Does the FTP server has problems with multithreading?
@roadmap_1286_li
#Does the FTP server has problems with multithreading?
#Write an article about SQLInjection (h2\src\docsrc\html\images\SQLInjection.txt)
@roadmap_1287_li
#Write an article about SQLInjection (h2\src\docsrc\html\images\SQLInjection.txt)
#Convert SQL-injection-2.txt to html document, include SQLInjection.java sample
@roadmap_1288_li
#Convert SQL-injection-2.txt to html document, include SQLInjection.java sample
#Send SQL Injection solution proposal to MySQL, Derby, HSQLDB,...
@roadmap_1289_li
#Send SQL Injection solution proposal to MySQL, Derby, HSQLDB,...
#Improve LOB in directories performance
@roadmap_1290_li
#Improve LOB in directories performance
#Optimize OR conditions: convert them to IN(...) if possible.
@roadmap_1291_li
#Optimize OR conditions: convert them to IN(...) if possible.
#Web site design: http://www.igniterealtime.org/projects/openfire/index.jsp
@roadmap_1292_li
#Web site design: http://www.igniterealtime.org/projects/openfire/index.jsp
#HSQLDB compatibility: Openfire server uses: CREATE SCHEMA PUBLIC AUTHORIZATION DBA; CREATE USER SA PASSWORD ""; GRANT DBA TO SA; SET SCHEMA PUBLIC
@roadmap_1293_li
#HSQLDB compatibility: Openfire server uses: CREATE SCHEMA PUBLIC AUTHORIZATION DBA; CREATE USER SA PASSWORD ""; GRANT DBA TO SA; SET SCHEMA PUBLIC
#Web site: Rename Performance to Comparison [/Compatibility], move Comparison to Other Database Engines to Comparison, move Products that Work with H2 to Comparison, move Performance Tuning to Advanced Topics
@roadmap_1294_li
#Web site: Rename Performance to Comparison [/Compatibility], move Comparison to Other Database Engines to Comparison, move Products that Work with H2 to Comparison, move Performance Tuning to Advanced Topics
#Translation: use ?? in help.csv
@roadmap_1295_li
#Translation: use ?? in help.csv
#Translated .pdf
@roadmap_1296_li
#Translated .pdf
#Cluster: hot deploy (adding a node on runtime)
@roadmap_1297_li
#Cluster: hot deploy (adding a node on runtime)
#Test with PostgreSQL Version 8.2
@roadmap_1298_li
#Test with PostgreSQL Version 8.2
#Website: Don't use frames.
@roadmap_1299_li
#Website: Don't use frames.
#Try again with Lobo browser (pure Java)
@roadmap_1300_li
#Try again with Lobo browser (pure Java)
#Recovery tool: bad blocks should be converted to INSERT INTO SYSTEM_ERRORS(...), and things should go into the .trace.db file
@roadmap_1301_li
#Recovery tool: bad blocks should be converted to INSERT INTO SYSTEM_ERRORS(...), and things should go into the .trace.db file
#RECOVER=2 to backup the database, run recovery, open the database
@roadmap_1302_li
#RECOVER=2 to backup the database, run recovery, open the database
#Recovery should work with encrypted databases
@roadmap_1303_li
#Recovery should work with encrypted databases
#Corruption: new error code, add help
@roadmap_1304_li
#Corruption: new error code, add help
#Space reuse: after init, scan all storages and free those that don't belong to a live database object
@roadmap_1305_li
#Space reuse: after init, scan all storages and free those that don't belong to a live database object
#SysProperties: change everything to H2_...
@roadmap_1306_li
#SysProperties: change everything to H2_...
#Use FilterIn / FilterOut putStream?
@roadmap_1307_li
#Use FilterIn / FilterOut putStream?
#Access rights: add missing features (users should be 'owner' of objects; missing rights for sequences; dropping objects)
@roadmap_1308_li
#Access rights: add missing features (users should be 'owner' of objects; missing rights for sequences; dropping objects)
#Support NOCACHE table option (Oracle)
@roadmap_1309_li
#Support NOCACHE table option (Oracle)
#Index usage for UPDATE ... WHERE .. IN (SELECT...)
@roadmap_1310_li
#Index usage for UPDATE ... WHERE .. IN (SELECT...)
#Add regular javadocs (using the default doclet, but another css) to the homepage.
@roadmap_1311_li
#Add regular javadocs (using the default doclet, but another css) to the homepage.
#The database should be kept open for a longer time when using the server mode.
@roadmap_1312_li
#The database should be kept open for a longer time when using the server mode.
#Javadocs: for each tool, add a copy &amp; paste sample in the class level.
@roadmap_1313_li
#Javadocs: for each tool, add a copy &amp; paste sample in the class level.
#Javadocs: add @author tags.
@roadmap_1314_li
#Javadocs: add @author tags.
#Fluent API for tools: Server.createTcpServer().setPort(9081).setPassword(password).start();
@roadmap_1315_li
#Fluent API for tools: Server.createTcpServer().setPort(9081).setPassword(password).start();
#MySQL compatibility: real SQL statements for SHOW TABLES, DESCRIBE TEST (then remove from Shell)
@roadmap_1316_li
#MySQL compatibility: real SQL statements for SHOW TABLES, DESCRIBE TEST (then remove from Shell)
#Use a default delay of 1 second before closing a database.
@roadmap_1317_li
#Use a default delay of 1 second before closing a database.
#Maven: upload source code and javadocs as well.
@roadmap_1318_li
#Maven: upload source code and javadocs as well.
#Write (log) to system table before adding to internal data structures.
@roadmap_1319_li
#Write (log) to system table before adding to internal data structures.
#Support very large deletes and updates.
@roadmap_1320_li
#Support very large deletes and updates.
#Doclet (javadocs): constructors are not listed.
@roadmap_1321_li
#Doclet (javadocs): constructors are not listed.
#Support direct lookup for MIN and MAX when using WHERE (see todo.txt / Direct Lookup).
@roadmap_1322_li
#Support direct lookup for MIN and MAX when using WHERE (see todo.txt / Direct Lookup).
#Support other array types (String[], double[]) in PreparedStatement.setObject(int, Object);
@roadmap_1323_li
#Support other array types (String[], double[]) in PreparedStatement.setObject(int, Object);
#MVCC should not be memory bound (uncommitted data is kept in memory in the delta index; maybe using a regular btree index solves the problem).
@roadmap_1324_li
#MVCC should not be memory bound (uncommitted data is kept in memory in the delta index; maybe using a regular btree index solves the problem).
#Support CREATE TEMPORARY LINKED TABLE.
@roadmap_1325_li
#Support CREATE TEMPORARY LINKED TABLE.
#MySQL compatibility: SELECT @variable := x FROM SYSTEM_RANGE(1, 50);
@roadmap_1326_li
#MySQL compatibility: SELECT @variable := x FROM SYSTEM_RANGE(1, 50);
#Oracle compatibility: support NLS_DATE_FORMAT.
@roadmap_1327_li
#Oracle compatibility: support NLS_DATE_FORMAT.
#Support flashback queries as in Oracle.
@roadmap_1328_li
#Support flashback queries as in Oracle.
#Import / Export of fixed with text files.
@roadmap_1329_li
#Import / Export of fixed with text files.
#Support for OUT parameters in user-defined procedures.
@roadmap_1330_li
#Support for OUT parameters in user-defined procedures.
#Support getGeneratedKeys to return multiple rows when used with batch updates. This is supported by MySQL, but not Derby. Both PostgreSQL and HSQLDB don't support getGeneratedKeys. Also support it when using INSERT ... SELECT.
@roadmap_1331_li
#Support getGeneratedKeys to return multiple rows when used with batch updates. This is supported by MySQL, but not Derby. Both PostgreSQL and HSQLDB don't support getGeneratedKeys. Also support it when using INSERT ... SELECT.
#HSQLDB compatibility: automatic data type for SUM if value is the value is too big (by default use the same type as the data).
@roadmap_1332_li
#HSQLDB compatibility: automatic data type for SUM if value is the value is too big (by default use the same type as the data).
#Improve the optimizer to select the right index for special cases: where id between 2 and 4 and booleanColumn
@roadmap_1333_li
#Improve the optimizer to select the right index for special cases: where id between 2 and 4 and booleanColumn
#Enable warning for 'Local variable declaration hides another field or variable'.
@roadmap_1334_li
#Enable warning for 'Local variable declaration hides another field or variable'.
#Linked tables: make hidden columns available (Oracle: rowid and ora_rowscn columns).
@roadmap_1335_li
#Linked tables: make hidden columns available (Oracle: rowid and ora_rowscn columns).
#Support merge join.
@roadmap_1336_li
#Support merge join.
#H2 Console: in-place autocomplete (need to merge query and result frame, use div).
@roadmap_1337_li
#H2 Console: in-place autocomplete (need to merge query and result frame, use div).
#MySQL compatibility: update test1 t1, test2 t2 set t1.id = t2.id where t1.id = t2.id;
@roadmap_1338_li
#MySQL compatibility: update test1 t1, test2 t2 set t1.id = t2.id where t1.id = t2.id;
#Oracle: support DECODE method (convert to CASE WHEN).
@roadmap_1339_li
#Oracle: support DECODE method (convert to CASE WHEN).
#Support large databases: split LOB (BLOB, CLOB) to multiple directories / disks (similar to tablespaces).
@roadmap_1340_li
#Support large databases: split LOB (BLOB, CLOB) to multiple directories / disks (similar to tablespaces).
#Support to assign a primary key index a user defined name.
@roadmap_1341_li
#Support to assign a primary key index a user defined name.
#Cluster: Add feature to make sure cluster nodes can not get out of sync (for example by stopping one process).
@roadmap_1342_li
#Cluster: Add feature to make sure cluster nodes can not get out of sync (for example by stopping one process).
#H2 Console: support configuration option for fixed width (monospace) font.
@roadmap_1343_li
#H2 Console: support configuration option for fixed width (monospace) font.
#Native fulltext search: support analyzers (specially for Chinese, Japanese).
@roadmap_1344_li
#Native fulltext search: support analyzers (specially for Chinese, Japanese).
#Automatically compact databases from time to time (as a background process).
@roadmap_1345_li
#Automatically compact databases from time to time (as a background process).
#Support GRANT SELECT, UPDATE ON *.
@roadmap_1346_li
#Support GRANT SELECT, UPDATE ON *.
#Test Eclipse DTP.
@roadmap_1347_li
#Test Eclipse DTP.
#Support JMX: Create an MBean for each database and server (support JConsole).
@roadmap_1348_li
#Support JMX: Create an MBean for each database and server (support JConsole).
#H2 Console: autocomplete: keep the previous setting
@roadmap_1349_h2
@roadmap_1349_li
#executeBatch: option to stop at the first failed statement.
@roadmap_1350_h2
#Not Planned
@roadmap_1350_li
@roadmap_1351_li
#HSQLDB (did) support this: select id i from test where i>0 (other databases don't). Supporting it may break compatibility.
@roadmap_1351_li
@roadmap_1352_li
#String.intern (so that Strings can be compared with ==) will not be used because some VMs have problems when used extensively.
@search_1000_b
......@@ -8186,300 +8219,303 @@ Webアプリケーション内からデータベースに接続するには様
@tutorial_1099_p
データベースへのアクセス方法についての詳細は、DbStarter.javaコードをご覧下さい。
@tutorial_1100_h2
@tutorial_1100_p
#By default the DbStarter listener opens a connection using the database URL jdbc:h2:~/test and user name and password 'sa'. It can also start the TCP server, however this is disabled by default. To enable it, use the db.tcpServer parameter in web.xml. Here is the complete list of options. These options are set just after the display-name and description tag, but before any listener and filter tags:
@tutorial_1101_h2
CSV (Comma Separated Values) サポート
@tutorial_1101_p
@tutorial_1102_p
データベースにCSVREADとCSVWRITEの関数を使用することで、 CSVファイルサポートを使用することができ、スタンドアロンツールとしてデータベースの外でCSVライブラリを使用することができます。
@tutorial_1102_h3
@tutorial_1103_h3
データベース内からCSVファイルに書き込む
@tutorial_1103_p
@tutorial_1104_p
クエリからCSVファイルを作成するのに、組込み関数 CSVWRITEを使用することができます。例:
@tutorial_1104_h3
@tutorial_1105_h3
データベース内からCSVファイルを読み込む
@tutorial_1105_p
@tutorial_1106_p
CSVREAD関数を使用してCSVファイルを読み込むことができます。 例:
@tutorial_1106_h3
@tutorial_1107_h3
JavaアプリケーションからCSVファイルに書き込む
@tutorial_1107_p
@tutorial_1108_p
データベースを全く使用しなくても、JavaアプリケーションでCSVツールを使用することができます。 例:
@tutorial_1108_h3
@tutorial_1109_h3
JavaアプリケーションからCSVファイルを読み込む
@tutorial_1109_p
@tutorial_1110_p
データベースを開かなくてもCSVファイルを読み込むことができます。 例:
@tutorial_1110_h2
@tutorial_1111_h2
アップグレード、 バックアップ、修復
@tutorial_1111_h3
@tutorial_1112_h3
データベースのアップグレー
@tutorial_1112_p
@tutorial_1113_p
あるバージョンのデータベースエンジンを次のバージョンにアップグレードする際の推奨する方法は、 古いエンジンを使って(SQLスクリプトのフォームでの)データベースのバックアップを作成し、新しいエンジンを使ってSQLスクリプトを実行します。
@tutorial_1113_h3
@tutorial_1114_h3
バックアップ
@tutorial_1114_p
@tutorial_1115_p
異なった方法のデータベースのバックアップがあります。例えば、データベースファイルをコピーすることが可能です。しかしながら、この方法はデータベースが使用されている間は推奨しません。データベースは人が判読しやすく、極めて大きいというわけではありません。データベースバックアップの推奨する方法は、圧縮したSQLスクリプトを作成することです。この方法は、バックアップツールを使用することで可能です:
@tutorial_1115_p
@tutorial_1116_p
オプションについての情報は、SQLコマンドスクリプトをご覧下さい。バックアップは遠隔で行えますが、ファイルはサーバー側に作られます。サーバーからファイルを取るのに、ビルトインFTPサーバーを使用することができます。データベースのバックアップを作るのに、SQLコマンドスクリプトを 使用することもできます。
@tutorial_1116_h3
@tutorial_1117_h3
修復
@tutorial_1117_p
@tutorial_1118_p
SQLスクリプトファイルからデータベースを修復するには、RunScriptツールを使用する必要があります:
@tutorial_1118_p
@tutorial_1119_p
オプションについての情報は、SQLコマンド RUNSCRIPTをご覧下さい。修復は遠隔で行えますが、サーバー側にファイルが存在する必要があります。サーバーからファイルをコピーするのに、ビルトインFTPサーバーを使用することができます。SQLスクリプトを実行するために、 SQLコマンド RUNSCRIPTを使用することができます。SQLスクリプトファイルには、RUNSCRIPTコマンドのフォーム内に他のスクリプトファイルのリファレンスが含まれています。しかしながら、サーバーモードを使用している時、リファレンススクリプトファイルはサーバー側で利用可能であることが必要です。
@tutorial_1119_h3
@tutorial_1120_h3
オンラインバックアップ
@tutorial_1120_p
@tutorial_1121_p
BACKUP SQLステートメントとバックアップツールの両方が全てのデータベースファイルをzipファイル形式で作成します。しかし、このファイルのコンテンツは人間が解読可能なものではありません。SCRIPTステートメントを除いて、BACKUPステートメントはデータベースオブジェクトをロックしないため、他のユーザーをブロックしません。結果として、バックアップは一貫性のあるトランザクションです:
@tutorial_1121_p
@tutorial_1122_p
バックアップツール (org.h2.tools.Backup) はオンラインバックアップを作成するために利用されません; このプログラムが実行されている間、データベースは使用されてはいけません。
@tutorial_1122_h2
@tutorial_1123_h2
#Command Line Tools
@tutorial_1123_p
@tutorial_1124_p
#This database comes with a number of command line tools. To get more information about a tool, start it with the parameter '-?', for example:
@tutorial_1124_p
@tutorial_1125_p
#The command line tools are:
@tutorial_1125_b
@tutorial_1126_b
バックアップ
@tutorial_1126_li
@tutorial_1127_li
#creates a backup of a database.
@tutorial_1127_b
@tutorial_1128_b
#ChangeFileEncryption
@tutorial_1128_li
@tutorial_1129_li
#allows changing the file encryption password or algorithm of a database.
@tutorial_1129_b
@tutorial_1130_b
#Console
@tutorial_1130_li
@tutorial_1131_li
#starts the browser based H2 Console.
@tutorial_1131_b
@tutorial_1132_b
#ConvertTraceFile
@tutorial_1132_li
@tutorial_1133_li
#converts a .trace.db file to a Java application and SQL script.
@tutorial_1133_b
@tutorial_1134_b
#CreateCluster
@tutorial_1134_li
@tutorial_1135_li
#creates a cluster from a standalone database.
@tutorial_1135_b
@tutorial_1136_b
#DeleteDbFiles
@tutorial_1136_li
@tutorial_1137_li
#deletes all files belonging to a database.
@tutorial_1137_b
@tutorial_1138_b
#Script
@tutorial_1138_li
@tutorial_1139_li
#allows converting a database to a SQL script for backup or migration.
@tutorial_1139_b
@tutorial_1140_b
#Recover
@tutorial_1140_li
@tutorial_1141_li
#helps recovering a corrupted database.
@tutorial_1141_b
@tutorial_1142_b
#Restore
@tutorial_1142_li
@tutorial_1143_li
#restores a backup of a database.
@tutorial_1143_b
@tutorial_1144_b
#RunScript
@tutorial_1144_li
@tutorial_1145_li
#runs a SQL script against a database.
@tutorial_1145_b
@tutorial_1146_b
Server
@tutorial_1146_li
@tutorial_1147_li
#is used in the server mode to start a H2 server.
@tutorial_1147_b
@tutorial_1148_b
#Shell
@tutorial_1148_li
@tutorial_1149_li
#is a command line database tool.
@tutorial_1149_p
@tutorial_1150_p
#The tools can also be called from an application by calling the main or another public methods. For details, see the Javadoc documentation.
@tutorial_1150_h2
@tutorial_1151_h2
OpenOffice Baseを使用する
@tutorial_1151_p
@tutorial_1152_p
OpenOffice.org Base はJDBC API上のデータベースアクセスをサポートしています。 OpenOffice Baseを使ってH2データベースに接続するためには、最初にOpenOfficeにJDBCドライバを追加する必要があります。H2データベースに接続する手順:
@tutorial_1152_li
#Start OpenOffice Writer, go to [Tools], [Options]
@tutorial_1153_li
#Make sure you have selected a Java runtime environment in OpenOffice.org / Java
#Start OpenOffice Writer, go to [Tools], [Options]
@tutorial_1154_li
#Click [Class Path...], [Add Archive...]
#Make sure you have selected a Java runtime environment in OpenOffice.org / Java
@tutorial_1155_li
#Select your h2.jar (location is up to you, could be wherever you choose)
#Click [Class Path...], [Add Archive...]
@tutorial_1156_li
#Click [OK] (as much as needed), stop OpenOffice (including the Quickstarter)
#Select your h2.jar (location is up to you, could be wherever you choose)
@tutorial_1157_li
OpenOffice Base を起動する
#Click [OK] (as much as needed), stop OpenOffice (including the Quickstarter) #OpenOffice Base を起動する
@tutorial_1158_li
存在するデータベースに接続し、JDBCを選択し、[Next] をクリックする
OpenOffice Base を起動する
@tutorial_1159_li
#Example datasource URL: jdbc:h2:~/test
存在するデータベースに接続し、JDBCを選択し、[Next] をクリックする
@tutorial_1160_li
#Example datasource URL: jdbc:h2:~/test #JDBCドライバクラス: org.h2.Driver
@tutorial_1161_li
JDBCドライバクラス: org.h2.Driver
@tutorial_1161_p
@tutorial_1162_p
#Now you can access the database stored in the current users home directory.
@tutorial_1162_p
@tutorial_1163_p
#To use H2 in NeoOffice (OpenOffice without X11):
@tutorial_1163_li
@tutorial_1164_li
#In NeoOffice, go to [NeoOffice], [Preferences]
@tutorial_1164_li
@tutorial_1165_li
#Look for the page under [NeoOffice], [Java]
@tutorial_1165_li
@tutorial_1166_li
#Click [Classpath], [Add Archive...]
@tutorial_1166_li
@tutorial_1167_li
#Select your h2.jar (location is up to you, could be wherever you choose)
@tutorial_1167_li
@tutorial_1168_li
#Click [OK] (as much as needed), restart NeoOffice.
@tutorial_1168_p
@tutorial_1169_p
#Now, when creating a new database using the "Database Wizard":
@tutorial_1169_li
@tutorial_1170_li
#Select "connect to existing database" and the type "jdbc". Click next.
@tutorial_1170_li
@tutorial_1171_li
#Enter your h2 database URL. The normal behavior of H2 is that a new db is created if it doesn't exist.
@tutorial_1171_li
@tutorial_1172_li
#Next step - up to you... you can just click finish and start working.
@tutorial_1172_p
@tutorial_1173_p
#Another solution to use H2 in NeoOffice is:
@tutorial_1173_li
@tutorial_1174_li
#Package the h2 jar within an extension package
@tutorial_1174_li
@tutorial_1175_li
#Install it as a Java extension in NeoOffice
@tutorial_1175_p
@tutorial_1176_p
#This can be done by create it using the NetBeans OpenOffice plugin. See also <a href="http://wiki.services.openoffice.org/wiki/Extensions_development_java">Extensions Development</a> .
@tutorial_1176_h2
@tutorial_1177_h2
Java Web Start / JNLP
@tutorial_1177_p
@tutorial_1178_p
Java Web Start / JNLP (Java Network Launch Protocol) を使用している時、パーミッションタグは.jnlp ファイルに設定され、application.jarファイルは署名されていなければなりません。そうでなければ、ファイルシステムに書き込もうとした時、次の例外が発生するでしょう: java.security.AccessControlException: access denied (java.io.FilePermission ... read) パーミッションタグの例:
@tutorial_1178_h2
@tutorial_1179_h2
#Using a Connection Pool
@tutorial_1179_p
@tutorial_1180_p
#For many databases, opening a connection is slow, and it is a good idea to use a connection pool to re-use connections. For H2 however opening a connection usually is fast if the database is already open. Using a connection pool for H2 actually slows down the process a bit, except if file encryption is used (in this case opening a connection is about half as fast as using a connection pool). A simple connection pool is included in H2. It is based on the <a href="http://www.source-code.biz/snippets/java/8.htm">Mini Connection Pool Manager</a> from Christian d'Heureuse. There are other, more complex connection pools available, for example <a href="http://jakarta.apache.org/commons/dbcp/">DBCP</a> . The build-in connection pool is used as follows:
@tutorial_1180_h2
@tutorial_1181_h2
フルテキストサーチ
@tutorial_1181_p
@tutorial_1182_p
H2はLuceneフルテキストサーチとnativeフルテキストサーチの実装をサポートしています。
@tutorial_1182_h3
@tutorial_1183_h3
Nativeフルテキストサーチを使用する
@tutorial_1183_p
初期化するには、次を呼び出します:
@tutorial_1184_p
#You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using:
初期化するには、次を呼び出します:
@tutorial_1185_p
PUBLICはスキーマ、TESTはテーブル名です。カラム名のリスト (分離されたカラム) はオプションです。このケースでは、全てのカラムがインデックスです。インデックスはリードタイムに更新されます。インデックスを検索するには、次のクエリーを使用します:
#You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using: #PUBLICはスキーマ、TESTはテーブル名です。カラム名のリスト (分離されたカラム) はオプションです。このケースでは、全てのカラムがインデックスです。インデックスはリードタイムに更新されます。インデックスを検索するには、次のクエリーを使用します:
@tutorial_1186_p
PUBLICはスキーマ、TESTはテーブル名です。カラム名のリスト (分離されたカラム) はオプションです。このケースでは、全てのカラムがインデックスです。インデックスはリードタイムに更新されます。インデックスを検索するには、次のクエリーを使用します:
@tutorial_1187_p
Javaアプリケーション内からインデックスを呼び出すことも可能です:
@tutorial_1187_h3
@tutorial_1188_h3
Luceneフルテキストサーチを使用する
@tutorial_1188_p
#To use the Lucene full text search, you need the Lucene library in the classpath. How his is done depends on the application; if you use the H2 Console, you can add the Lucene jar file to the environment variables H2DRIVERS or CLASSPATH. To initialize the Lucene full text search in a database, call:
@tutorial_1189_p
#You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using:
#To use the Lucene full text search, you need the Lucene library in the classpath. How his is done depends on the application; if you use the H2 Console, you can add the Lucene jar file to the environment variables H2DRIVERS or CLASSPATH. To initialize the Lucene full text search in a database, call:
@tutorial_1190_p
PUBLICはスキーマ、TESTはテーブル名です。カラム名のリスト (分離されたカラム) はオプションです。このケースでは、全てのカラムがインデックスです。インデックスはリードタイムに更新されます。インデックスを検索するには、次のクエリーを使用します:
#You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using: #PUBLICはスキーマ、TESTはテーブル名です。カラム名のリスト (分離されたカラム) はオプションです。このケースでは、全てのカラムがインデックスです。インデックスはリードタイムに更新されます。インデックスを検索するには、次のクエリーを使用します:
@tutorial_1191_p
PUBLICはスキーマ、TESTはテーブル名です。カラム名のリスト (分離されたカラム) はオプションです。このケースでは、全てのカラムがインデックスです。インデックスはリードタイムに更新されます。インデックスを検索するには、次のクエリーを使用します:
@tutorial_1192_p
Javaアプリケーション内からインデックスを呼び出すことも可能です:
@tutorial_1192_h2
@tutorial_1193_h2
#User-Defined Variables
@tutorial_1193_p
@tutorial_1194_p
#This database supports user-defined variables. Variables start with @ and can be used wherever expressions or parameters are used. Variables not persisted and session scoped, that means only visible for the session where they are defined. A value is usually assigned using the SET command:
@tutorial_1194_p
@tutorial_1195_p
#It is also possible to change a value using the SET() method. This is useful in queries:
@tutorial_1195_p
@tutorial_1196_p
#Variables that are not set evaluate to NULL. The data type of a user-defined variable is the data type of the value assigned to it, that means it is not necessary (or possible) to declare variable names before using them. There are no restrictions on the assigned values; large objects (LOBs) are supported as well.
@tutorial_1196_h2
@tutorial_1197_h2
#Date and Time
@tutorial_1197_p
@tutorial_1198_p
#Date, time and timestamp values support ISO 8601 formatting, including time zone:
@tutorial_1198_p
@tutorial_1199_p
#If the time zone is not set, the value is parsed using the current time zone setting of the system. Date and time information is stored in H2 database files in GMT (Greenwich Mean Time). If the database is opened using another system time zone, the date and time will change accordingly. If you want to move a database from one time zone to the other and don't want this to happen, you need to create a SQL script file using the SCRIPT command or Script tool, and then load the database using the RUNSCRIPT command or the RunScript tool in the new time zone.
h2/src/docsrc/textbase/_docs_en.properties
浏览文件 @ 755bd88a
......@@ -1415,7 +1415,7 @@ installation_1031_td=src
installation_1032_td=Source files
jaqu_1000_h1=JaQu
jaqu_1001_h2=What is JaQu
jaqu_1002_p=JaQu stands for Java Query and allows to access databases using pure Java. JaQu replaces SQL, JDBC, and O/R frameworks such as Hibernate. JaQu is something like LINQ for Java (LINQ stands for "language integrated query" and is a Microsoft .NET technology). The following JaQu code\:
jaqu_1002_p=JaQu stands for Java Query and allows to access databases using pure Java. JaQu provides a fluent interface (or internal DSL) for building SQL statements. JaQu replaces SQL, JDBC, and O/R frameworks such as Hibernate. JaQu is something like LINQ for Java (LINQ stands for "language integrated query" and is a Microsoft .NET technology). The following JaQu code\:
jaqu_1003_p=stands for the SQL statement\:
jaqu_1004_h2=Advantages and Differences to other Data Access Tools
jaqu_1005_p=Unlike SQL, JaQu can be easily integrated in Java applications. Because JaQu is pure Java, Javadoc and auto-complete are supported. Type checking is performed by the compiler. JaQu fully protects against SQL injection.
......@@ -1429,23 +1429,25 @@ jaqu_1012_h2=Current State
jaqu_1013_p=JaQu is not yet stable, and not part of the h2.jar file. However the source code is included in H2, under\:
jaqu_1014_li=src/test/org/h2/test/jaqu/* (samples and tests)
jaqu_1015_li=src/tools/org/h2/jaqu/* (framework)
jaqu_1016_h2=Requirements
jaqu_1017_p=JaQu requires Java 1.5. Annotations are not need. Currently, JaQu is only tested with the H2 database engine, however in theory it should work with any database that supports the JDBC API.
jaqu_1018_h2=Example Code
jaqu_1019_h2=Configuration
jaqu_1020_p=JaQu does not require any kind of configuration is you want to use the default mapping. To define table indices, or if you want to map a class to a table with a different name, or a field to a column with another name, create a function called 'define' in the data class. Example\:
jaqu_1021_p=The method 'define()' contains the mapping definition. It is called once when the class is used for the first time. Like annotations, the mapping is defined in the class itself. Unlike when using annotations, the compiler can check the syntax even for multi-column objects (multi-column indexes, multi-column primary keys and so on). This solution is very flexible because the definition is written in regular Java code\: Unlike when using annotations, your code can select the right configuration depending on the environment if required.
jaqu_1022_h2=Ideas
jaqu_1023_p=This project has just been started, and nothing is fixed yet. Some ideas for what to implement include\:
jaqu_1024_li=Provide API level compatibility with JPA (so that JaQu can be used as an extension of JPA).
jaqu_1025_li=Internally use a JPA implementation (for example Hibernate) instead of SQL directly.
jaqu_1026_li=Use PreparedStatements and cache them.
jaqu_1027_h2=Related Projects
jaqu_1028_a=JEQUEL\: Java Embedded QUEry Language
jaqu_1029_a=Quaere
jaqu_1030_a=Quaere (Alias implementation)
jaqu_1031_a=JoSQL
jaqu_1032_a=Google Group about adding LINQ features to Java
jaqu_1016_h2=Building the JaQu library
jaqu_1017_p=To create the JaQu jar file, run\: <code>build jarJaqu</code> . This will create the file <code>bin/h2jaqu.jar</code> .
jaqu_1018_h2=Requirements
jaqu_1019_p=JaQu requires Java 1.5. Annotations are not need. Currently, JaQu is only tested with the H2 database engine, however in theory it should work with any database that supports the JDBC API.
jaqu_1020_h2=Example Code
jaqu_1021_h2=Configuration
jaqu_1022_p=JaQu does not require any kind of configuration is you want to use the default mapping. To define table indices, or if you want to map a class to a table with a different name, or a field to a column with another name, create a function called 'define' in the data class. Example\:
jaqu_1023_p=The method 'define()' contains the mapping definition. It is called once when the class is used for the first time. Like annotations, the mapping is defined in the class itself. Unlike when using annotations, the compiler can check the syntax even for multi-column objects (multi-column indexes, multi-column primary keys and so on). This solution is very flexible because the definition is written in regular Java code\: Unlike when using annotations, your code can select the right configuration depending on the environment if required.
jaqu_1024_h2=Ideas
jaqu_1025_p=This project has just been started, and nothing is fixed yet. Some ideas for what to implement include\:
jaqu_1026_li=Provide API level compatibility with JPA (so that JaQu can be used as an extension of JPA).
jaqu_1027_li=Internally use a JPA implementation (for example Hibernate) instead of SQL directly.
jaqu_1028_li=Use PreparedStatements and cache them.
jaqu_1029_h2=Related Projects
jaqu_1030_a=JEQUEL\: Java Embedded QUEry Language
jaqu_1031_a=Quaere
jaqu_1032_a=Quaere (Alias implementation)
jaqu_1033_a=JoSQL
jaqu_1034_a=Google Group about adding LINQ features to Java
license_1000_h1=License
license_1001_h2=Summary and License FAQ
license_1002_p=H2 is dual licensed and available under a modified version of the MPL 1.1 ( <a href\="http\://www.mozilla.org/MPL">Mozilla Public License</a> ) or EPL 1.0 ( <a href\="http\://opensource.org/licenses/eclipse-1.0.php">Eclipse Public License</a> ). The changes are
......@@ -1805,405 +1807,413 @@ performance_1000_h1=Performance
performance_1001_a=Performance Comparison
performance_1002_a=PolePosition Benchmark
performance_1003_a=Application Profiling
performance_1004_a=Performance Tuning
performance_1005_h2=Performance Comparison
performance_1006_p=In most cases H2 is a lot faster than all other (open source and not open source) database engines. Please note this is mostly a single connection benchmark run on one computer.
performance_1007_h3=Embedded
performance_1008_th=Test Case
performance_1009_th=Unit
performance_1010_th=H2
performance_1011_th=HSQLDB
performance_1012_th=Derby
performance_1013_td=Simple\: Init
performance_1014_td=ms
performance_1015_td=719
performance_1016_td=1344
performance_1017_td=2906
performance_1018_td=Simple\: Query (random)
performance_1019_td=ms
performance_1020_td=328
performance_1004_a=Database Profiling
performance_1005_a=Performance Tuning
performance_1006_h2=Performance Comparison
performance_1007_p=In most cases H2 is a lot faster than all other (open source and not open source) database engines. Please note this is mostly a single connection benchmark run on one computer.
performance_1008_h3=Embedded
performance_1009_th=Test Case
performance_1010_th=Unit
performance_1011_th=H2
performance_1012_th=HSQLDB
performance_1013_th=Derby
performance_1014_td=Simple\: Init
performance_1015_td=ms
performance_1016_td=719
performance_1017_td=1344
performance_1018_td=2906
performance_1019_td=Simple\: Query (random)
performance_1020_td=ms
performance_1021_td=328
performance_1022_td=1578
performance_1023_td=Simple\: Query (sequential)
performance_1024_td=ms
performance_1025_td=250
performance_1022_td=328
performance_1023_td=1578
performance_1024_td=Simple\: Query (sequential)
performance_1025_td=ms
performance_1026_td=250
performance_1027_td=1484
performance_1028_td=Simple\: Update (random)
performance_1029_td=ms
performance_1030_td=688
performance_1031_td=1828
performance_1032_td=14922
performance_1033_td=Simple\: Delete (sequential)
performance_1034_td=ms
performance_1035_td=203
performance_1036_td=265
performance_1037_td=10235
performance_1038_td=Simple\: Memory Usage
performance_1039_td=MB
performance_1040_td=6
performance_1041_td=9
performance_1042_td=11
performance_1043_td=BenchA\: Init
performance_1044_td=ms
performance_1045_td=422
performance_1046_td=672
performance_1047_td=4328
performance_1048_td=BenchA\: Transactions
performance_1049_td=ms
performance_1050_td=6969
performance_1051_td=3531
performance_1052_td=16719
performance_1053_td=BenchA\: Memory Usage
performance_1054_td=MB
performance_1055_td=10
performance_1027_td=250
performance_1028_td=1484
performance_1029_td=Simple\: Update (random)
performance_1030_td=ms
performance_1031_td=688
performance_1032_td=1828
performance_1033_td=14922
performance_1034_td=Simple\: Delete (sequential)
performance_1035_td=ms
performance_1036_td=203
performance_1037_td=265
performance_1038_td=10235
performance_1039_td=Simple\: Memory Usage
performance_1040_td=MB
performance_1041_td=6
performance_1042_td=9
performance_1043_td=11
performance_1044_td=BenchA\: Init
performance_1045_td=ms
performance_1046_td=422
performance_1047_td=672
performance_1048_td=4328
performance_1049_td=BenchA\: Transactions
performance_1050_td=ms
performance_1051_td=6969
performance_1052_td=3531
performance_1053_td=16719
performance_1054_td=BenchA\: Memory Usage
performance_1055_td=MB
performance_1056_td=10
performance_1057_td=9
performance_1058_td=BenchB\: Init
performance_1059_td=ms
performance_1060_td=1703
performance_1061_td=3937
performance_1062_td=13844
performance_1063_td=BenchB\: Transactions
performance_1064_td=ms
performance_1065_td=2360
performance_1066_td=1328
performance_1067_td=5797
performance_1068_td=BenchB\: Memory Usage
performance_1069_td=MB
performance_1070_td=8
performance_1071_td=9
performance_1072_td=8
performance_1073_td=BenchC\: Init
performance_1074_td=ms
performance_1075_td=718
performance_1076_td=468
performance_1077_td=5328
performance_1078_td=BenchC\: Transactions
performance_1079_td=ms
performance_1080_td=2688
performance_1081_td=60828
performance_1082_td=7109
performance_1083_td=BenchC\: Memory Usage
performance_1084_td=MB
performance_1085_td=10
performance_1086_td=14
performance_1087_td=9
performance_1088_td=Executed Statements
performance_1089_td=\#
performance_1090_td=594255
performance_1057_td=10
performance_1058_td=9
performance_1059_td=BenchB\: Init
performance_1060_td=ms
performance_1061_td=1703
performance_1062_td=3937
performance_1063_td=13844
performance_1064_td=BenchB\: Transactions
performance_1065_td=ms
performance_1066_td=2360
performance_1067_td=1328
performance_1068_td=5797
performance_1069_td=BenchB\: Memory Usage
performance_1070_td=MB
performance_1071_td=8
performance_1072_td=9
performance_1073_td=8
performance_1074_td=BenchC\: Init
performance_1075_td=ms
performance_1076_td=718
performance_1077_td=468
performance_1078_td=5328
performance_1079_td=BenchC\: Transactions
performance_1080_td=ms
performance_1081_td=2688
performance_1082_td=60828
performance_1083_td=7109
performance_1084_td=BenchC\: Memory Usage
performance_1085_td=MB
performance_1086_td=10
performance_1087_td=14
performance_1088_td=9
performance_1089_td=Executed Statements
performance_1090_td=\#
performance_1091_td=594255
performance_1092_td=594255
performance_1093_td=Total Time
performance_1094_td=ms
performance_1095_td=17048
performance_1096_td=74779
performance_1097_td=84250
performance_1098_td=Statement per Second
performance_1099_td=\#
performance_1100_td=34857
performance_1101_td=7946
performance_1102_td=7053
performance_1103_h3=Client-Server
performance_1104_th=Test Case
performance_1105_th=Unit
performance_1106_th=H2
performance_1107_th=HSQLDB
performance_1108_th=Derby
performance_1109_th=PostgreSQL
performance_1110_th=MySQL
performance_1111_td=Simple\: Init
performance_1112_td=ms
performance_1113_td=2516
performance_1114_td=3109
performance_1115_td=7078
performance_1116_td=4625
performance_1117_td=2859
performance_1118_td=Simple\: Query (random)
performance_1119_td=ms
performance_1120_td=2890
performance_1121_td=2547
performance_1122_td=8843
performance_1123_td=7703
performance_1124_td=3203
performance_1125_td=Simple\: Query (sequential)
performance_1126_td=ms
performance_1127_td=2953
performance_1128_td=2407
performance_1129_td=8516
performance_1130_td=6953
performance_1131_td=3516
performance_1132_td=Simple\: Update (random)
performance_1133_td=ms
performance_1134_td=3141
performance_1135_td=3671
performance_1136_td=18125
performance_1137_td=7797
performance_1138_td=4687
performance_1139_td=Simple\: Delete (sequential)
performance_1140_td=ms
performance_1141_td=1000
performance_1142_td=1219
performance_1143_td=12891
performance_1144_td=3547
performance_1145_td=1938
performance_1146_td=Simple\: Memory Usage
performance_1147_td=MB
performance_1148_td=6
performance_1149_td=10
performance_1150_td=14
performance_1151_td=0
performance_1152_td=1
performance_1153_td=BenchA\: Init
performance_1154_td=ms
performance_1155_td=2266
performance_1156_td=2484
performance_1157_td=7797
performance_1158_td=4234
performance_1159_td=4703
performance_1160_td=BenchA\: Transactions
performance_1161_td=ms
performance_1162_td=11078
performance_1163_td=8875
performance_1164_td=26328
performance_1165_td=18641
performance_1166_td=11187
performance_1167_td=BenchA\: Memory Usage
performance_1168_td=MB
performance_1169_td=8
performance_1170_td=13
performance_1171_td=10
performance_1172_td=0
performance_1173_td=1
performance_1174_td=BenchB\: Init
performance_1175_td=ms
performance_1176_td=8422
performance_1177_td=12531
performance_1178_td=27734
performance_1179_td=18609
performance_1180_td=12312
performance_1181_td=BenchB\: Transactions
performance_1182_td=ms
performance_1183_td=4125
performance_1184_td=3344
performance_1185_td=7875
performance_1186_td=7922
performance_1187_td=3266
performance_1188_td=BenchB\: Memory Usage
performance_1189_td=MB
performance_1190_td=9
performance_1191_td=10
performance_1192_td=8
performance_1193_td=0
performance_1194_td=1
performance_1195_td=BenchC\: Init
performance_1196_td=ms
performance_1197_td=1781
performance_1198_td=1609
performance_1199_td=6797
performance_1200_td=2453
performance_1201_td=3328
performance_1202_td=BenchC\: Transactions
performance_1203_td=ms
performance_1204_td=8453
performance_1205_td=62469
performance_1206_td=19859
performance_1207_td=11516
performance_1208_td=7062
performance_1209_td=BenchC\: Memory Usage
performance_1210_td=MB
performance_1211_td=10
performance_1212_td=15
performance_1213_td=9
performance_1214_td=0
performance_1215_td=1
performance_1216_td=Executed Statements
performance_1217_td=\#
performance_1218_td=594255
performance_1093_td=594255
performance_1094_td=Total Time
performance_1095_td=ms
performance_1096_td=17048
performance_1097_td=74779
performance_1098_td=84250
performance_1099_td=Statement per Second
performance_1100_td=\#
performance_1101_td=34857
performance_1102_td=7946
performance_1103_td=7053
performance_1104_h3=Client-Server
performance_1105_th=Test Case
performance_1106_th=Unit
performance_1107_th=H2
performance_1108_th=HSQLDB
performance_1109_th=Derby
performance_1110_th=PostgreSQL
performance_1111_th=MySQL
performance_1112_td=Simple\: Init
performance_1113_td=ms
performance_1114_td=2516
performance_1115_td=3109
performance_1116_td=7078
performance_1117_td=4625
performance_1118_td=2859
performance_1119_td=Simple\: Query (random)
performance_1120_td=ms
performance_1121_td=2890
performance_1122_td=2547
performance_1123_td=8843
performance_1124_td=7703
performance_1125_td=3203
performance_1126_td=Simple\: Query (sequential)
performance_1127_td=ms
performance_1128_td=2953
performance_1129_td=2407
performance_1130_td=8516
performance_1131_td=6953
performance_1132_td=3516
performance_1133_td=Simple\: Update (random)
performance_1134_td=ms
performance_1135_td=3141
performance_1136_td=3671
performance_1137_td=18125
performance_1138_td=7797
performance_1139_td=4687
performance_1140_td=Simple\: Delete (sequential)
performance_1141_td=ms
performance_1142_td=1000
performance_1143_td=1219
performance_1144_td=12891
performance_1145_td=3547
performance_1146_td=1938
performance_1147_td=Simple\: Memory Usage
performance_1148_td=MB
performance_1149_td=6
performance_1150_td=10
performance_1151_td=14
performance_1152_td=0
performance_1153_td=1
performance_1154_td=BenchA\: Init
performance_1155_td=ms
performance_1156_td=2266
performance_1157_td=2484
performance_1158_td=7797
performance_1159_td=4234
performance_1160_td=4703
performance_1161_td=BenchA\: Transactions
performance_1162_td=ms
performance_1163_td=11078
performance_1164_td=8875
performance_1165_td=26328
performance_1166_td=18641
performance_1167_td=11187
performance_1168_td=BenchA\: Memory Usage
performance_1169_td=MB
performance_1170_td=8
performance_1171_td=13
performance_1172_td=10
performance_1173_td=0
performance_1174_td=1
performance_1175_td=BenchB\: Init
performance_1176_td=ms
performance_1177_td=8422
performance_1178_td=12531
performance_1179_td=27734
performance_1180_td=18609
performance_1181_td=12312
performance_1182_td=BenchB\: Transactions
performance_1183_td=ms
performance_1184_td=4125
performance_1185_td=3344
performance_1186_td=7875
performance_1187_td=7922
performance_1188_td=3266
performance_1189_td=BenchB\: Memory Usage
performance_1190_td=MB
performance_1191_td=9
performance_1192_td=10
performance_1193_td=8
performance_1194_td=0
performance_1195_td=1
performance_1196_td=BenchC\: Init
performance_1197_td=ms
performance_1198_td=1781
performance_1199_td=1609
performance_1200_td=6797
performance_1201_td=2453
performance_1202_td=3328
performance_1203_td=BenchC\: Transactions
performance_1204_td=ms
performance_1205_td=8453
performance_1206_td=62469
performance_1207_td=19859
performance_1208_td=11516
performance_1209_td=7062
performance_1210_td=BenchC\: Memory Usage
performance_1211_td=MB
performance_1212_td=10
performance_1213_td=15
performance_1214_td=9
performance_1215_td=0
performance_1216_td=1
performance_1217_td=Executed Statements
performance_1218_td=\#
performance_1219_td=594255
performance_1220_td=594255
performance_1221_td=594255
performance_1222_td=594255
performance_1223_td=Total Time
performance_1224_td=ms
performance_1225_td=48625
performance_1226_td=104265
performance_1227_td=151843
performance_1228_td=94000
performance_1229_td=58061
performance_1230_td=Statement per Second
performance_1231_td=\#
performance_1232_td=12221
performance_1233_td=5699
performance_1234_td=3913
performance_1235_td=6321
performance_1236_td=10235
performance_1237_h3=Benchmark Results and Comments
performance_1238_h4=H2
performance_1239_p=Version 1.0.67 (2008-02-22) was used for the test. For simpler operations, the performance of H2 is about the same as for HSQLDB. For more complex queries, the query optimizer is very important. However H2 is not very fast in every case, certain kind of queries may still be slow. One situation where is H2 is slow is large result sets, because they are buffered to disk if more than a certain number of records are returned. The advantage of buffering is, there is no limit on the result set size. The open/close time is almost fixed, because of the file locking protocol\: The engine waits 20 ms after opening a database to ensure the database files are not opened by another process.
performance_1240_h4=HSQLDB
performance_1241_p=Version 1.8.0.8 was used for the test. Cached tables are used in this test (hsqldb.default_table_type\=cached), and the write delay is 1 second (SET WRITE_DELAY 1). HSQLDB is fast when using simple operations. HSQLDB is very slow in the last test (BenchC\: Transactions), probably because is has a bad query optimizer. One query where HSQLDB is slow is a two-table join\:
performance_1242_p=The PolePosition benchmark also shows that the query optimizer does not do a very good job for some queries. A disadvantage in HSQLDB is the slow startup / shutdown time (currently not listed) when using bigger databases. The reason is, a backup of the database is created whenever the database is opened or closed.
performance_1243_h4=Derby
performance_1244_p=Version 10.3.1.4 was used for the test. Derby is clearly the slowest embedded database in this test. This seems to be a structural problem, because all operations are really slow. It will not be easy for the developers of Derby to improve the performance to a reasonable level. A few problems have been identified\: Leaving autocommit on is a problem for Derby. If it is switched off during the whole test, the results are about 20% better for Derby.
performance_1245_h4=PostgreSQL
performance_1246_p=Version 8.1.4 was used for the test. The following options where changed in postgresql.conf\: fsync \= off, commit_delay \= 1000. PostgreSQL is run in server mode. It looks like the base performance is slower than MySQL, the reason could be the network layer. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
performance_1247_h4=MySQL
performance_1248_p=Version 5.0.22 was used for the test. MySQL was run with the InnoDB backend. The setting innodb_flush_log_at_trx_commit (found in the my.ini file) was set to 0. Otherwise (and by default), MySQL is really slow (around 140 statements per second in this test) because it tries to flush the data to disk for each commit. For small transactions (when autocommit is on) this is really slow. But many use cases use small or relatively small transactions. Too bad this setting is not listed in the configuration wizard, and it always overwritten when using the wizard. You need to change this setting manually in the file my.ini, and then restart the service. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
performance_1249_h4=Firebird
performance_1250_p=Firebird 1.5 (default installation) was tested, but the results are not published currently. It is possible to run the performance test with the Firebird database, and any information on how to configure Firebird for higher performance are welcome.
performance_1251_h4=Why Oracle / MS SQL Server / DB2 are Not Listed
performance_1252_p=The license of these databases does not allow to publish benchmark results. This doesn't mean that they are fast. They are in fact quite slow, and need a lot of memory. But you will need to test this yourself. SQLite was not tested because the JDBC driver doesn't support transactions.
performance_1253_h3=About this Benchmark
performance_1254_h4=Number of Connections
performance_1255_p=This is mostly a single-connection benchmark. BenchB uses multiple connections; the other tests use one connection.
performance_1256_h4=Real-World Tests
performance_1257_p=Good benchmarks emulate real-world use cases. This benchmark includes 3 test cases\: A simple test case with one table and many small updates / deletes. BenchA is similar to the TPC-A test, but single connection / single threaded (see also\: www.tpc.org). BenchB is similar to the TPC-B test, using multiple connections (one thread per connection). BenchC is similar to the TPC-C test, but single connection / single threaded.
performance_1258_h4=Comparing Embedded with Server Databases
performance_1259_p=This is mainly a benchmark for embedded databases (where the application runs in the same virtual machine than the database engine). However MySQL and PostgreSQL are not Java databases and cannot be embedded into a Java application. For the Java databases, both embedded and server modes are tested.
performance_1260_h4=Test Platform
performance_1261_p=This test is run on Windows XP with the virus scanner switched off. The VM used is Sun JDK 1.5.
performance_1262_h4=Multiple Runs
performance_1263_p=When a Java benchmark is run first, the code is not fully compiled and therefore runs slower than when running multiple times. A benchmark should always run the same test multiple times and ignore the first run(s). This benchmark runs three times, but only the last run is measured.
performance_1264_h4=Memory Usage
performance_1265_p=It is not enough to measure the time taken, the memory usage is important as well. Performance can be improved in databases by using a bigger in-memory cache, but there is only a limited amount of memory available on the system. HSQLDB tables are kept fully in memory by default; this benchmark uses 'disk based' tables for all databases. Unfortunately, it is not so easy to calculate the memory usage of PostgreSQL and MySQL, because they run in a different process than the test. This benchmark currently does not print memory usage of those databases.
performance_1266_h4=Delayed Operations
performance_1267_p=Some databases delay some operations (for example flushing the buffers) until after the benchmark is run. This benchmark waits between each database tested, and each database runs in a different process (sequentially).
performance_1268_h4=Transaction Commit / Durability
performance_1269_p=Durability means transaction committed to the database will not be lost. Some databases (for example MySQL) try to enforce this by default by calling fsync() to flush the buffers, but most hard drives don't actually flush all data. Calling fsync() slows down transaction commit a lot, but doesn't always make data durable. When comparing the results, it is important to think about the effect. Many database suggest to 'batch' operations when possible. This benchmark switches off autocommit when loading the data, and calls commit after each 1000 inserts. However many applications need 'short' transactions at runtime (a commit after each update). This benchmark commits after each update / delete in the simple benchmark, and after each business transaction in the other benchmarks. For databases that support delayed commits, a delay of one second is used.
performance_1270_h4=Using Prepared Statements
performance_1271_p=Wherever possible, the test cases use prepared statements.
performance_1272_h4=Currently Not Tested\: Startup Time
performance_1273_p=The startup time of a database engine is important as well for embedded use. This time is not measured currently. Also, not tested is the time used to create a database and open an existing database. Here, one (wrapper) connection is opened at the start, and for each step a new connection is opened and then closed. That means the Open/Close time listed is for opening a connection if the database is already in use.
performance_1274_h2=PolePosition Benchmark
performance_1275_p=The PolePosition is an open source benchmark. The algorithms are all quite simple. It was developed / sponsored by db4o.
performance_1276_th=Test Case
performance_1277_th=Unit
performance_1278_th=H2
performance_1279_th=HSQLDB
performance_1280_th=MySQL
performance_1281_td=Melbourne write
performance_1282_td=ms
performance_1283_td=369
performance_1284_td=249
performance_1285_td=2022
performance_1286_td=Melbourne read
performance_1287_td=ms
performance_1288_td=47
performance_1289_td=49
performance_1290_td=93
performance_1291_td=Melbourne read_hot
performance_1292_td=ms
performance_1293_td=24
performance_1294_td=43
performance_1295_td=95
performance_1296_td=Melbourne delete
performance_1297_td=ms
performance_1298_td=147
performance_1299_td=133
performance_1300_td=176
performance_1301_td=Sepang write
performance_1302_td=ms
performance_1303_td=965
performance_1304_td=1201
performance_1305_td=3213
performance_1306_td=Sepang read
performance_1307_td=ms
performance_1308_td=765
performance_1309_td=948
performance_1310_td=3455
performance_1311_td=Sepang read_hot
performance_1312_td=ms
performance_1313_td=789
performance_1314_td=859
performance_1315_td=3563
performance_1316_td=Sepang delete
performance_1317_td=ms
performance_1318_td=1384
performance_1319_td=1596
performance_1320_td=6214
performance_1321_td=Bahrain write
performance_1322_td=ms
performance_1323_td=1186
performance_1324_td=1387
performance_1325_td=6904
performance_1326_td=Bahrain query_indexed_string
performance_1327_td=ms
performance_1328_td=336
performance_1329_td=170
performance_1330_td=693
performance_1331_td=Bahrain query_string
performance_1332_td=ms
performance_1333_td=18064
performance_1334_td=39703
performance_1335_td=41243
performance_1336_td=Bahrain query_indexed_int
performance_1337_td=ms
performance_1338_td=104
performance_1339_td=134
performance_1340_td=678
performance_1341_td=Bahrain update
performance_1342_td=ms
performance_1343_td=191
performance_1344_td=87
performance_1345_td=159
performance_1346_td=Bahrain delete
performance_1347_td=ms
performance_1348_td=1215
performance_1349_td=729
performance_1350_td=6812
performance_1351_td=Imola retrieve
performance_1352_td=ms
performance_1353_td=198
performance_1354_td=194
performance_1355_td=4036
performance_1356_td=Barcelona write
performance_1357_td=ms
performance_1358_td=413
performance_1359_td=832
performance_1360_td=3191
performance_1361_td=Barcelona read
performance_1362_td=ms
performance_1363_td=119
performance_1364_td=160
performance_1365_td=1177
performance_1366_td=Barcelona query
performance_1367_td=ms
performance_1368_td=20
performance_1369_td=5169
performance_1370_td=101
performance_1371_td=Barcelona delete
performance_1372_td=ms
performance_1373_td=388
performance_1374_td=319
performance_1375_td=3287
performance_1376_td=Total
performance_1377_td=ms
performance_1378_td=26724
performance_1379_td=53962
performance_1380_td=87112
performance_1381_h2=Application Profiling
performance_1382_h3=Analyze First
performance_1383_p=Before trying to optimize the performance, it is important to know where the time is actually spent. The same is true for memory problems. Premature or 'blind' optimization should be avoided, as it is not an efficient way to solve the problem. There are various ways to analyze the application. In some situations it is possible to compare two implementations and use System.currentTimeMillis() to find out which one is faster. But this does not work for complex applications with many modules, and for memory problems. A very good tool to measure both the memory and the CPU is the <a href\="http\://www.yourkit.com">YourKit Java Profiler</a> . This tool is also used to optimize the performance and memory footprint of this database engine.
performance_1384_h2=Database Performance Tuning
performance_1385_h3=Virus Scanners
performance_1386_p=Some virus scanners scan files every time they are accessed. It is very important for performance that database files are not scanned for viruses. The database engine does never interprets the data stored in the files as programs, that means even if somebody would store a virus in a database file, this would be harmless (when the virus does not run, it cannot spread). Some virus scanners allow excluding file endings. Make sure files ending with .db are not scanned.
performance_1387_h3=Using the Trace Options
performance_1388_p=If the main performance hot spots are in the database engine, in many cases the performance can be optimized by creating additional indexes, or changing the schema. Sometimes the application does not directly generate the SQL statements, for example if an O/R mapping tool is used. To view the SQL statements and JDBC API calls, you can use the trace options. For more information, see <a href\="features.html\#trace_options">Using the Trace Options</a> .
performance_1389_h3=Index Usage
performance_1390_p=This database uses indexes to improve the performance of SELECT, UPDATE and DELETE statements. If a column is used in the WHERE clause of a query, and if an index exists on this column, then the index can be used. Multi-column indexes are used if all or the first columns of the index are used. Both equality lookup and range scans are supported. Indexes are not used to order result sets\: The results are sorted in memory if required. Indexes are created automatically for primary key and unique constraints. Indexes are also created for foreign key constraints, if required. For other columns, indexes need to be created manually using the CREATE INDEX statement.
performance_1391_h3=Optimizer
performance_1392_p=This database uses a cost based optimizer. For simple and queries and queries with medium complexity (less than 7 tables in the join), the expected cost (running time) of all possible plans is calculated, and the plan with the lowest cost is used. For more complex queries, the algorithm first tries all possible combinations for the first few tables, and the remaining tables added using a greedy algorithm (this works well for most joins). Afterwards a genetic algorithm is used to test at most 2000 distinct plans. Only left-deep plans are evaluated.
performance_1393_h3=Expression Optimization
performance_1394_p=After the statement is parsed, all expressions are simplified automatically if possible. Operations are evaluated only once if all parameters are constant. Functions are also optimized, but only if the function is constant (always returns the same result for the same parameter values). If the WHERE clause is always false, then the table is not accessed at all.
performance_1395_h3=COUNT(*) Optimization
performance_1396_p=If the query only counts all rows of a table, then the data is not accessed. However, this is only possible if no WHERE clause is used, that means it only works for queries of the form SELECT COUNT(*) FROM table.
performance_1397_h3=Updating Optimizer Statistics / Column Selectivity
performance_1398_p=When executing a query, at most one index per joined table can be used. If the same table is joined multiple times, for each join only one index is used. Example\: for the query SELECT * FROM TEST T1, TEST T2 WHERE T1.NAME\='A' AND T2.ID\=T1.ID, two index can be used, in this case the index on NAME for T1 and the index on ID for T2.
performance_1399_p=If a table has multiple indexes, sometimes more than one index could be used. Example\: if there is a table TEST(ID, NAME, FIRSTNAME) and an index on each column, then two indexes could be used for the query SELECT * FROM TEST WHERE NAME\='A' AND FIRSTNAME\='B', the index on NAME or the index on FIRSTNAME. It is not possible to use both indexes at the same time. Which index is used depends on the selectivity of the column. The selectivity describes the 'uniqueness' of values in a column. A selectivity of 100 means each value appears only once, and a selectivity of 1 means the same value appears in many or most rows. For the query above, the index on NAME should be used if the table contains more distinct names than first names.
performance_1400_p=The SQL statement ANALYZE can be used to automatically estimate the selectivity of the columns in the tables. This command should be run from time to time to improve the query plans generated by the optimizer.
performance_1401_h3=Optimization Examples
performance_1402_p=See <code>src/test/org/h2/samples/optimizations.sql</code> for a few examples of queries that benefit from special optimizations built into the database.
performance_1223_td=594255
performance_1224_td=Total Time
performance_1225_td=ms
performance_1226_td=48625
performance_1227_td=104265
performance_1228_td=151843
performance_1229_td=94000
performance_1230_td=58061
performance_1231_td=Statement per Second
performance_1232_td=\#
performance_1233_td=12221
performance_1234_td=5699
performance_1235_td=3913
performance_1236_td=6321
performance_1237_td=10235
performance_1238_h3=Benchmark Results and Comments
performance_1239_h4=H2
performance_1240_p=Version 1.0.67 (2008-02-22) was used for the test. For simpler operations, the performance of H2 is about the same as for HSQLDB. For more complex queries, the query optimizer is very important. However H2 is not very fast in every case, certain kind of queries may still be slow. One situation where is H2 is slow is large result sets, because they are buffered to disk if more than a certain number of records are returned. The advantage of buffering is, there is no limit on the result set size. The open/close time is almost fixed, because of the file locking protocol\: The engine waits 20 ms after opening a database to ensure the database files are not opened by another process.
performance_1241_h4=HSQLDB
performance_1242_p=Version 1.8.0.8 was used for the test. Cached tables are used in this test (hsqldb.default_table_type\=cached), and the write delay is 1 second (SET WRITE_DELAY 1). HSQLDB is fast when using simple operations. HSQLDB is very slow in the last test (BenchC\: Transactions), probably because is has a bad query optimizer. One query where HSQLDB is slow is a two-table join\:
performance_1243_p=The PolePosition benchmark also shows that the query optimizer does not do a very good job for some queries. A disadvantage in HSQLDB is the slow startup / shutdown time (currently not listed) when using bigger databases. The reason is, a backup of the database is created whenever the database is opened or closed.
performance_1244_h4=Derby
performance_1245_p=Version 10.3.1.4 was used for the test. Derby is clearly the slowest embedded database in this test. This seems to be a structural problem, because all operations are really slow. It will not be easy for the developers of Derby to improve the performance to a reasonable level. A few problems have been identified\: Leaving autocommit on is a problem for Derby. If it is switched off during the whole test, the results are about 20% better for Derby.
performance_1246_h4=PostgreSQL
performance_1247_p=Version 8.1.4 was used for the test. The following options where changed in postgresql.conf\: fsync \= off, commit_delay \= 1000. PostgreSQL is run in server mode. It looks like the base performance is slower than MySQL, the reason could be the network layer. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
performance_1248_h4=MySQL
performance_1249_p=Version 5.0.22 was used for the test. MySQL was run with the InnoDB backend. The setting innodb_flush_log_at_trx_commit (found in the my.ini file) was set to 0. Otherwise (and by default), MySQL is really slow (around 140 statements per second in this test) because it tries to flush the data to disk for each commit. For small transactions (when autocommit is on) this is really slow. But many use cases use small or relatively small transactions. Too bad this setting is not listed in the configuration wizard, and it always overwritten when using the wizard. You need to change this setting manually in the file my.ini, and then restart the service. The memory usage number is incorrect, because only the memory usage of the JDBC driver is measured.
performance_1250_h4=Firebird
performance_1251_p=Firebird 1.5 (default installation) was tested, but the results are not published currently. It is possible to run the performance test with the Firebird database, and any information on how to configure Firebird for higher performance are welcome.
performance_1252_h4=Why Oracle / MS SQL Server / DB2 are Not Listed
performance_1253_p=The license of these databases does not allow to publish benchmark results. This doesn't mean that they are fast. They are in fact quite slow, and need a lot of memory. But you will need to test this yourself. SQLite was not tested because the JDBC driver doesn't support transactions.
performance_1254_h3=About this Benchmark
performance_1255_h4=Number of Connections
performance_1256_p=This is mostly a single-connection benchmark. BenchB uses multiple connections; the other tests use one connection.
performance_1257_h4=Real-World Tests
performance_1258_p=Good benchmarks emulate real-world use cases. This benchmark includes 3 test cases\: A simple test case with one table and many small updates / deletes. BenchA is similar to the TPC-A test, but single connection / single threaded (see also\: www.tpc.org). BenchB is similar to the TPC-B test, using multiple connections (one thread per connection). BenchC is similar to the TPC-C test, but single connection / single threaded.
performance_1259_h4=Comparing Embedded with Server Databases
performance_1260_p=This is mainly a benchmark for embedded databases (where the application runs in the same virtual machine than the database engine). However MySQL and PostgreSQL are not Java databases and cannot be embedded into a Java application. For the Java databases, both embedded and server modes are tested.
performance_1261_h4=Test Platform
performance_1262_p=This test is run on Windows XP with the virus scanner switched off. The VM used is Sun JDK 1.5.
performance_1263_h4=Multiple Runs
performance_1264_p=When a Java benchmark is run first, the code is not fully compiled and therefore runs slower than when running multiple times. A benchmark should always run the same test multiple times and ignore the first run(s). This benchmark runs three times, but only the last run is measured.
performance_1265_h4=Memory Usage
performance_1266_p=It is not enough to measure the time taken, the memory usage is important as well. Performance can be improved in databases by using a bigger in-memory cache, but there is only a limited amount of memory available on the system. HSQLDB tables are kept fully in memory by default; this benchmark uses 'disk based' tables for all databases. Unfortunately, it is not so easy to calculate the memory usage of PostgreSQL and MySQL, because they run in a different process than the test. This benchmark currently does not print memory usage of those databases.
performance_1267_h4=Delayed Operations
performance_1268_p=Some databases delay some operations (for example flushing the buffers) until after the benchmark is run. This benchmark waits between each database tested, and each database runs in a different process (sequentially).
performance_1269_h4=Transaction Commit / Durability
performance_1270_p=Durability means transaction committed to the database will not be lost. Some databases (for example MySQL) try to enforce this by default by calling fsync() to flush the buffers, but most hard drives don't actually flush all data. Calling fsync() slows down transaction commit a lot, but doesn't always make data durable. When comparing the results, it is important to think about the effect. Many database suggest to 'batch' operations when possible. This benchmark switches off autocommit when loading the data, and calls commit after each 1000 inserts. However many applications need 'short' transactions at runtime (a commit after each update). This benchmark commits after each update / delete in the simple benchmark, and after each business transaction in the other benchmarks. For databases that support delayed commits, a delay of one second is used.
performance_1271_h4=Using Prepared Statements
performance_1272_p=Wherever possible, the test cases use prepared statements.
performance_1273_h4=Currently Not Tested\: Startup Time
performance_1274_p=The startup time of a database engine is important as well for embedded use. This time is not measured currently. Also, not tested is the time used to create a database and open an existing database. Here, one (wrapper) connection is opened at the start, and for each step a new connection is opened and then closed. That means the Open/Close time listed is for opening a connection if the database is already in use.
performance_1275_h2=PolePosition Benchmark
performance_1276_p=The PolePosition is an open source benchmark. The algorithms are all quite simple. It was developed / sponsored by db4o.
performance_1277_th=Test Case
performance_1278_th=Unit
performance_1279_th=H2
performance_1280_th=HSQLDB
performance_1281_th=MySQL
performance_1282_td=Melbourne write
performance_1283_td=ms
performance_1284_td=369
performance_1285_td=249
performance_1286_td=2022
performance_1287_td=Melbourne read
performance_1288_td=ms
performance_1289_td=47
performance_1290_td=49
performance_1291_td=93
performance_1292_td=Melbourne read_hot
performance_1293_td=ms
performance_1294_td=24
performance_1295_td=43
performance_1296_td=95
performance_1297_td=Melbourne delete
performance_1298_td=ms
performance_1299_td=147
performance_1300_td=133
performance_1301_td=176
performance_1302_td=Sepang write
performance_1303_td=ms
performance_1304_td=965
performance_1305_td=1201
performance_1306_td=3213
performance_1307_td=Sepang read
performance_1308_td=ms
performance_1309_td=765
performance_1310_td=948
performance_1311_td=3455
performance_1312_td=Sepang read_hot
performance_1313_td=ms
performance_1314_td=789
performance_1315_td=859
performance_1316_td=3563
performance_1317_td=Sepang delete
performance_1318_td=ms
performance_1319_td=1384
performance_1320_td=1596
performance_1321_td=6214
performance_1322_td=Bahrain write
performance_1323_td=ms
performance_1324_td=1186
performance_1325_td=1387
performance_1326_td=6904
performance_1327_td=Bahrain query_indexed_string
performance_1328_td=ms
performance_1329_td=336
performance_1330_td=170
performance_1331_td=693
performance_1332_td=Bahrain query_string
performance_1333_td=ms
performance_1334_td=18064
performance_1335_td=39703
performance_1336_td=41243
performance_1337_td=Bahrain query_indexed_int
performance_1338_td=ms
performance_1339_td=104
performance_1340_td=134
performance_1341_td=678
performance_1342_td=Bahrain update
performance_1343_td=ms
performance_1344_td=191
performance_1345_td=87
performance_1346_td=159
performance_1347_td=Bahrain delete
performance_1348_td=ms
performance_1349_td=1215
performance_1350_td=729
performance_1351_td=6812
performance_1352_td=Imola retrieve
performance_1353_td=ms
performance_1354_td=198
performance_1355_td=194
performance_1356_td=4036
performance_1357_td=Barcelona write
performance_1358_td=ms
performance_1359_td=413
performance_1360_td=832
performance_1361_td=3191
performance_1362_td=Barcelona read
performance_1363_td=ms
performance_1364_td=119
performance_1365_td=160
performance_1366_td=1177
performance_1367_td=Barcelona query
performance_1368_td=ms
performance_1369_td=20
performance_1370_td=5169
performance_1371_td=101
performance_1372_td=Barcelona delete
performance_1373_td=ms
performance_1374_td=388
performance_1375_td=319
performance_1376_td=3287
performance_1377_td=Total
performance_1378_td=ms
performance_1379_td=26724
performance_1380_td=53962
performance_1381_td=87112
performance_1382_h2=Application Profiling
performance_1383_h3=Analyze First
performance_1384_p=Before trying to optimize the performance, it is important to know where the time is actually spent. The same is true for memory problems. Premature or 'blind' optimization should be avoided, as it is not an efficient way to solve the problem. There are various ways to analyze the application. In some situations it is possible to compare two implementations and use System.currentTimeMillis() to find out which one is faster. But this does not work for complex applications with many modules, and for memory problems.
performance_1385_p=A very good tool to measure both the memory and the CPU is the <a href\="http\://www.yourkit.com">YourKit Java Profiler</a> . This tool is also used to optimize the performance and memory footprint of this database engine.
performance_1386_p=A simple way to profile an application is to use the built-in profiling tool of java. Example\:
performance_1387_p=Unfortunately, it is only possible to profile the application from start to end.
performance_1388_h2=Database Profiling
performance_1389_p=The ConvertTraceFile tool generates SQL statement statistics at the end of the SQL script file. The format used is similar to the profiling data generated when using java -Xrunhprof. As an example, execute the the following script using the H2 Console\:
performance_1390_p=Now convert the .trace.db file using the ConvertTraceFile tool\:
performance_1391_p=The generated file <code>test.sql</code> will contain the SQL statements as well as the following profiling data (results vary)\:
performance_1392_h2=Database Performance Tuning
performance_1393_h3=Virus Scanners
performance_1394_p=Some virus scanners scan files every time they are accessed. It is very important for performance that database files are not scanned for viruses. The database engine does never interprets the data stored in the files as programs, that means even if somebody would store a virus in a database file, this would be harmless (when the virus does not run, it cannot spread). Some virus scanners allow excluding file endings. Make sure files ending with .db are not scanned.
performance_1395_h3=Using the Trace Options
performance_1396_p=If the main performance hot spots are in the database engine, in many cases the performance can be optimized by creating additional indexes, or changing the schema. Sometimes the application does not directly generate the SQL statements, for example if an O/R mapping tool is used. To view the SQL statements and JDBC API calls, you can use the trace options. For more information, see <a href\="features.html\#trace_options">Using the Trace Options</a> .
performance_1397_h3=Index Usage
performance_1398_p=This database uses indexes to improve the performance of SELECT, UPDATE and DELETE statements. If a column is used in the WHERE clause of a query, and if an index exists on this column, then the index can be used. Multi-column indexes are used if all or the first columns of the index are used. Both equality lookup and range scans are supported. Indexes are not used to order result sets\: The results are sorted in memory if required. Indexes are created automatically for primary key and unique constraints. Indexes are also created for foreign key constraints, if required. For other columns, indexes need to be created manually using the CREATE INDEX statement.
performance_1399_h3=Optimizer
performance_1400_p=This database uses a cost based optimizer. For simple and queries and queries with medium complexity (less than 7 tables in the join), the expected cost (running time) of all possible plans is calculated, and the plan with the lowest cost is used. For more complex queries, the algorithm first tries all possible combinations for the first few tables, and the remaining tables added using a greedy algorithm (this works well for most joins). Afterwards a genetic algorithm is used to test at most 2000 distinct plans. Only left-deep plans are evaluated.
performance_1401_h3=Expression Optimization
performance_1402_p=After the statement is parsed, all expressions are simplified automatically if possible. Operations are evaluated only once if all parameters are constant. Functions are also optimized, but only if the function is constant (always returns the same result for the same parameter values). If the WHERE clause is always false, then the table is not accessed at all.
performance_1403_h3=COUNT(*) Optimization
performance_1404_p=If the query only counts all rows of a table, then the data is not accessed. However, this is only possible if no WHERE clause is used, that means it only works for queries of the form SELECT COUNT(*) FROM table.
performance_1405_h3=Updating Optimizer Statistics / Column Selectivity
performance_1406_p=When executing a query, at most one index per joined table can be used. If the same table is joined multiple times, for each join only one index is used. Example\: for the query SELECT * FROM TEST T1, TEST T2 WHERE T1.NAME\='A' AND T2.ID\=T1.ID, two index can be used, in this case the index on NAME for T1 and the index on ID for T2.
performance_1407_p=If a table has multiple indexes, sometimes more than one index could be used. Example\: if there is a table TEST(ID, NAME, FIRSTNAME) and an index on each column, then two indexes could be used for the query SELECT * FROM TEST WHERE NAME\='A' AND FIRSTNAME\='B', the index on NAME or the index on FIRSTNAME. It is not possible to use both indexes at the same time. Which index is used depends on the selectivity of the column. The selectivity describes the 'uniqueness' of values in a column. A selectivity of 100 means each value appears only once, and a selectivity of 1 means the same value appears in many or most rows. For the query above, the index on NAME should be used if the table contains more distinct names than first names.
performance_1408_p=The SQL statement ANALYZE can be used to automatically estimate the selectivity of the columns in the tables. This command should be run from time to time to improve the query plans generated by the optimizer.
performance_1409_h3=Optimization Examples
performance_1410_p=See <code>src/test/org/h2/samples/optimizations.sql</code> for a few examples of queries that benefit from special optimizations built into the database.
quickstart_1000_h1=Quickstart
quickstart_1001_a=Embedding H2 in an Application
quickstart_1002_a=The H2 Console Application
......@@ -2460,134 +2470,135 @@ roadmap_1220_li=Allow execution time prepare for SELECT * FROM CSVREAD(?, 'colum
roadmap_1221_li=Support multiple directories (on different hard drives) for the same database
roadmap_1222_li=Server protocol\: use challenge response authentication, but client sends hash(user+password) encrypted with response
roadmap_1223_li=Support EXEC[UTE] (doesn't return a result set, compatible to MS SQL Server)
roadmap_1224_li=GROUP BY and DISTINCT\: support large groups (buffer to disk), do not keep large sets in memory
roadmap_1225_li=Support native XML data type
roadmap_1226_li=Support triggers with a string property or option\: SpringTrigger, OSGITrigger
roadmap_1227_li=Clustering\: adding a node should be very fast and without interrupting clients (very short lock)
roadmap_1228_li=Support materialized views (using triggers)
roadmap_1229_li=Store dates in local time zone (portability of database files)
roadmap_1230_li=Ability to resize the cache array when resizing the cache
roadmap_1231_li=Time based cache writing (one second after writing the log)
roadmap_1232_li=Check state of H2 driver for DDLUtils\: https\://issues.apache.org/jira/browse/DDLUTILS-185
roadmap_1233_li=Index usage for REGEXP LIKE.
roadmap_1234_li=Add a role DBA (like ADMIN).
roadmap_1235_li=Better support multiple processors for in-memory databases.
roadmap_1236_li=Access rights\: remember the owner of an object. COMMENT\: allow owner of object to change it.
roadmap_1237_li=Implement INSTEAD OF trigger.
roadmap_1238_li=Access rights\: Finer grained access control (grant access for specific functions)
roadmap_1239_li=Support N'text'
roadmap_1240_li=Support SCOPE_IDENTITY() to avoid problems when inserting rows in a trigger
roadmap_1241_li=Set a connection read only (Connection.setReadOnly)
roadmap_1242_li=In MySQL mode, for AUTO_INCREMENT columns, don't set the primary key
roadmap_1243_li=Use JDK 1.4 file locking to create the lock file (but not yet by default); writing a system property to detect concurrent access from the same VM (different classloaders).
roadmap_1244_li=Support compatibility for jdbc\:hsqldb\:res\:
roadmap_1245_li=In the MySQL and PostgreSQL, use lower case identifiers by default (DatabaseMetaData.storesLowerCaseIdentifiers \= true)
roadmap_1246_li=Provide a simple, lightweight O/R mapping tool
roadmap_1247_li=Provide an Java SQL builder with standard and H2 syntax
roadmap_1248_li=Trace\: write OS, file system, JVM,... when opening the database
roadmap_1249_li=Support indexes for views (probably requires materialized views)
roadmap_1250_li=Document SET SEARCH_PATH, BEGIN, EXECUTE, parameters
roadmap_1251_li=Browser\: use Desktop.isDesktopSupported and browse when using JDK 1.6
roadmap_1252_li=Server\: use one listener (detect if the request comes from an PG or TCP client)
roadmap_1253_li=Store dates as 'local'. Existing files use GMT. Use escape syntax for compatibility.
roadmap_1254_li=Support data type INTERVAL
roadmap_1255_li=NATURAL JOIN\: MySQL and PostgreSQL don't repeat columns when using SELECT * ...
roadmap_1256_li=Optimize SELECT MIN(ID), MAX(ID), COUNT(*) FROM TEST WHERE ID BETWEEN 100 AND 200
roadmap_1257_li=Support Oracle functions\: TRUNC, NVL2, TO_CHAR, TO_DATE, TO_NUMBER
roadmap_1258_li=Sequence\: PostgreSQL compatibility (rename, create) (http\://www.postgresql.org/docs/8.2/static/sql-altersequence.html)
roadmap_1259_li=DISTINCT\: Support large result sets by sorting on all columns (additionally) and then removing duplicates.
roadmap_1260_li=File system that writes to two file systems (replicating file system)
roadmap_1261_li=File system with a background writer thread; test if this is faster
roadmap_1262_li=FTP access to a database (.csv for a table, a directory for a schema, a file for a lob, a script.sql file).
roadmap_1263_li=LIMIT and OFFSET for GROUP_CONCAT
roadmap_1264_li=Support triggers for INFORMATION_SCHEMA tables (to better support PostgreSQL catalog\: rebuild after creating new tables)
roadmap_1265_li=Better document the source code
roadmap_1266_li=Support select * from dual a left join dual b on b.x\=(select max(x) from dual)
roadmap_1267_li=Optimization\: don't lock when the database is read-only
roadmap_1268_li=Integrate spatial functions from http\://geosysin.iict.ch/irstv-trac/wiki/H2spatial/Download
roadmap_1269_li=Support COSH, SINH, and TANH functions
roadmap_1270_li=Native search\: support "phrase search", wildcard search (* and ?), case-insensitive search, boolean operators, and grouping
roadmap_1271_li=Improve documentation of access rights
roadmap_1272_li=Support ENUM data type (see MySQL, PostgreSQL, MS SQL Server, maybe others)
roadmap_1273_li=Command line option for the H2 Console and TCP configuration (which .h2.server.properties and .h2.keystore to use)
roadmap_1274_li=Support a schema name for Java functions
roadmap_1275_li=Remember the domain of a column
roadmap_1276_li=Support Jackcess (MS Access databases)
roadmap_1277_li=Built-in methods to write large objects (BLOB and CLOB)\: FILE_WRITE('test.txt', 'Hello World')
roadmap_1278_li=Change package name in version 2.0\: org.h2database
roadmap_1279_li=MVCC\: support transactionally consistent backups using SCRIPT
roadmap_1280_li=Improve time to open large databases (see mail 'init time for distributed setup')
roadmap_1281_li=Use ARRAY for fulltext search return value, at least internally in the native implementation (and as an option for the user)
roadmap_1282_li=Move Maven 2 repository from hsql.sf.net to h2database.sf.net
roadmap_1283_li=Java 1.5 tool\: JdbcUtils.closeSilently(s1, s2,...)
roadmap_1284_li=Javadoc\: document design patterns used
roadmap_1285_li=Triggers for metadata tables; use for PostgreSQL catalog
roadmap_1286_li=Does the FTP server has problems with multithreading?
roadmap_1287_li=Write an article about SQLInjection (h2\\src\\docsrc\\html\\images\\SQLInjection.txt)
roadmap_1288_li=Convert SQL-injection-2.txt to html document, include SQLInjection.java sample
roadmap_1289_li=Send SQL Injection solution proposal to MySQL, Derby, HSQLDB,...
roadmap_1290_li=Improve LOB in directories performance
roadmap_1291_li=Optimize OR conditions\: convert them to IN(...) if possible.
roadmap_1292_li=Web site design\: http\://www.igniterealtime.org/projects/openfire/index.jsp
roadmap_1293_li=HSQLDB compatibility\: Openfire server uses\: CREATE SCHEMA PUBLIC AUTHORIZATION DBA; CREATE USER SA PASSWORD ""; GRANT DBA TO SA; SET SCHEMA PUBLIC
roadmap_1294_li=Web site\: Rename Performance to Comparison [/Compatibility], move Comparison to Other Database Engines to Comparison, move Products that Work with H2 to Comparison, move Performance Tuning to Advanced Topics
roadmap_1295_li=Translation\: use ?? in help.csv
roadmap_1296_li=Translated .pdf
roadmap_1297_li=Cluster\: hot deploy (adding a node on runtime)
roadmap_1298_li=Test with PostgreSQL Version 8.2
roadmap_1299_li=Website\: Don't use frames.
roadmap_1300_li=Try again with Lobo browser (pure Java)
roadmap_1301_li=Recovery tool\: bad blocks should be converted to INSERT INTO SYSTEM_ERRORS(...), and things should go into the .trace.db file
roadmap_1302_li=RECOVER\=2 to backup the database, run recovery, open the database
roadmap_1303_li=Recovery should work with encrypted databases
roadmap_1304_li=Corruption\: new error code, add help
roadmap_1305_li=Space reuse\: after init, scan all storages and free those that don't belong to a live database object
roadmap_1306_li=SysProperties\: change everything to H2_...
roadmap_1307_li=Use FilterIn / FilterOut putStream?
roadmap_1308_li=Access rights\: add missing features (users should be 'owner' of objects; missing rights for sequences; dropping objects)
roadmap_1309_li=Support NOCACHE table option (Oracle)
roadmap_1310_li=Index usage for UPDATE ... WHERE .. IN (SELECT...)
roadmap_1311_li=Add regular javadocs (using the default doclet, but another css) to the homepage.
roadmap_1312_li=The database should be kept open for a longer time when using the server mode.
roadmap_1313_li=Javadocs\: for each tool, add a copy &amp; paste sample in the class level.
roadmap_1314_li=Javadocs\: add @author tags.
roadmap_1315_li=Fluent API for tools\: Server.createTcpServer().setPort(9081).setPassword(password).start();
roadmap_1316_li=MySQL compatibility\: real SQL statements for SHOW TABLES, DESCRIBE TEST (then remove from Shell)
roadmap_1317_li=Use a default delay of 1 second before closing a database.
roadmap_1318_li=Maven\: upload source code and javadocs as well.
roadmap_1319_li=Write (log) to system table before adding to internal data structures.
roadmap_1320_li=Support very large deletes and updates.
roadmap_1321_li=Doclet (javadocs)\: constructors are not listed.
roadmap_1322_li=Support direct lookup for MIN and MAX when using WHERE (see todo.txt / Direct Lookup).
roadmap_1323_li=Support other array types (String[], double[]) in PreparedStatement.setObject(int, Object);
roadmap_1324_li=MVCC should not be memory bound (uncommitted data is kept in memory in the delta index; maybe using a regular btree index solves the problem).
roadmap_1325_li=Support CREATE TEMPORARY LINKED TABLE.
roadmap_1326_li=MySQL compatibility\: SELECT @variable \:\= x FROM SYSTEM_RANGE(1, 50);
roadmap_1327_li=Oracle compatibility\: support NLS_DATE_FORMAT.
roadmap_1328_li=Support flashback queries as in Oracle.
roadmap_1329_li=Import / Export of fixed with text files.
roadmap_1330_li=Support for OUT parameters in user-defined procedures.
roadmap_1331_li=Support getGeneratedKeys to return multiple rows when used with batch updates. This is supported by MySQL, but not Derby. Both PostgreSQL and HSQLDB don't support getGeneratedKeys. Also support it when using INSERT ... SELECT.
roadmap_1332_li=HSQLDB compatibility\: automatic data type for SUM if value is the value is too big (by default use the same type as the data).
roadmap_1333_li=Improve the optimizer to select the right index for special cases\: where id between 2 and 4 and booleanColumn
roadmap_1334_li=Enable warning for 'Local variable declaration hides another field or variable'.
roadmap_1335_li=Linked tables\: make hidden columns available (Oracle\: rowid and ora_rowscn columns).
roadmap_1336_li=Support merge join.
roadmap_1337_li=H2 Console\: in-place autocomplete (need to merge query and result frame, use div).
roadmap_1338_li=MySQL compatibility\: update test1 t1, test2 t2 set t1.id \= t2.id where t1.id \= t2.id;
roadmap_1339_li=Oracle\: support DECODE method (convert to CASE WHEN).
roadmap_1340_li=Support large databases\: split LOB (BLOB, CLOB) to multiple directories / disks (similar to tablespaces).
roadmap_1341_li=Support to assign a primary key index a user defined name.
roadmap_1342_li=Cluster\: Add feature to make sure cluster nodes can not get out of sync (for example by stopping one process).
roadmap_1343_li=H2 Console\: support configuration option for fixed width (monospace) font.
roadmap_1344_li=Native fulltext search\: support analyzers (specially for Chinese, Japanese).
roadmap_1345_li=Automatically compact databases from time to time (as a background process).
roadmap_1346_li=Support GRANT SELECT, UPDATE ON *.
roadmap_1347_li=Test Eclipse DTP.
roadmap_1348_li=Support JMX\: Create an MBean for each database and server (support JConsole).
roadmap_1349_h2=Not Planned
roadmap_1350_li=HSQLDB (did) support this\: select id i from test where i>0 (other databases don't). Supporting it may break compatibility.
roadmap_1351_li=String.intern (so that Strings can be compared with \=\=) will not be used because some VMs have problems when used extensively.
roadmap_1224_li=Support native XML data type
roadmap_1225_li=Support triggers with a string property or option\: SpringTrigger, OSGITrigger
roadmap_1226_li=Clustering\: adding a node should be very fast and without interrupting clients (very short lock)
roadmap_1227_li=Support materialized views (using triggers)
roadmap_1228_li=Store dates in local time zone (portability of database files)
roadmap_1229_li=Ability to resize the cache array when resizing the cache
roadmap_1230_li=Time based cache writing (one second after writing the log)
roadmap_1231_li=Check state of H2 driver for DDLUtils\: https\://issues.apache.org/jira/browse/DDLUTILS-185
roadmap_1232_li=Index usage for REGEXP LIKE.
roadmap_1233_li=Add a role DBA (like ADMIN).
roadmap_1234_li=Better support multiple processors for in-memory databases.
roadmap_1235_li=Access rights\: remember the owner of an object. COMMENT\: allow owner of object to change it.
roadmap_1236_li=Implement INSTEAD OF trigger.
roadmap_1237_li=Access rights\: Finer grained access control (grant access for specific functions)
roadmap_1238_li=Support N'text'
roadmap_1239_li=Support SCOPE_IDENTITY() to avoid problems when inserting rows in a trigger
roadmap_1240_li=Set a connection read only (Connection.setReadOnly)
roadmap_1241_li=In MySQL mode, for AUTO_INCREMENT columns, don't set the primary key
roadmap_1242_li=Use JDK 1.4 file locking to create the lock file (but not yet by default); writing a system property to detect concurrent access from the same VM (different classloaders).
roadmap_1243_li=Support compatibility for jdbc\:hsqldb\:res\:
roadmap_1244_li=In the MySQL and PostgreSQL, use lower case identifiers by default (DatabaseMetaData.storesLowerCaseIdentifiers \= true)
roadmap_1245_li=Provide a simple, lightweight O/R mapping tool
roadmap_1246_li=Provide an Java SQL builder with standard and H2 syntax
roadmap_1247_li=Trace\: write OS, file system, JVM,... when opening the database
roadmap_1248_li=Support indexes for views (probably requires materialized views)
roadmap_1249_li=Document SET SEARCH_PATH, BEGIN, EXECUTE, parameters
roadmap_1250_li=Browser\: use Desktop.isDesktopSupported and browse when using JDK 1.6
roadmap_1251_li=Server\: use one listener (detect if the request comes from an PG or TCP client)
roadmap_1252_li=Store dates as 'local'. Existing files use GMT. Use escape syntax for compatibility.
roadmap_1253_li=Support data type INTERVAL
roadmap_1254_li=NATURAL JOIN\: MySQL and PostgreSQL don't repeat columns when using SELECT * ...
roadmap_1255_li=Optimize SELECT MIN(ID), MAX(ID), COUNT(*) FROM TEST WHERE ID BETWEEN 100 AND 200
roadmap_1256_li=Support Oracle functions\: TRUNC, NVL2, TO_CHAR, TO_DATE, TO_NUMBER
roadmap_1257_li=Sequence\: PostgreSQL compatibility (rename, create) (http\://www.postgresql.org/docs/8.2/static/sql-altersequence.html)
roadmap_1258_li=DISTINCT\: Support large result sets by sorting on all columns (additionally) and then removing duplicates.
roadmap_1259_li=File system that writes to two file systems (replicating file system)
roadmap_1260_li=File system with a background writer thread; test if this is faster
roadmap_1261_li=FTP access to a database (.csv for a table, a directory for a schema, a file for a lob, a script.sql file).
roadmap_1262_li=LIMIT and OFFSET for GROUP_CONCAT
roadmap_1263_li=Support triggers for INFORMATION_SCHEMA tables (to better support PostgreSQL catalog\: rebuild after creating new tables)
roadmap_1264_li=Better document the source code
roadmap_1265_li=Support select * from dual a left join dual b on b.x\=(select max(x) from dual)
roadmap_1266_li=Optimization\: don't lock when the database is read-only
roadmap_1267_li=Integrate spatial functions from http\://geosysin.iict.ch/irstv-trac/wiki/H2spatial/Download
roadmap_1268_li=Support COSH, SINH, and TANH functions
roadmap_1269_li=Native search\: support "phrase search", wildcard search (* and ?), case-insensitive search, boolean operators, and grouping
roadmap_1270_li=Improve documentation of access rights
roadmap_1271_li=Support ENUM data type (see MySQL, PostgreSQL, MS SQL Server, maybe others)
roadmap_1272_li=Command line option for the H2 Console and TCP configuration (which .h2.server.properties and .h2.keystore to use)
roadmap_1273_li=Support a schema name for Java functions
roadmap_1274_li=Remember the domain of a column
roadmap_1275_li=Support Jackcess (MS Access databases)
roadmap_1276_li=Built-in methods to write large objects (BLOB and CLOB)\: FILE_WRITE('test.txt', 'Hello World')
roadmap_1277_li=Change package name in version 2.0\: org.h2database
roadmap_1278_li=MVCC\: support transactionally consistent backups using SCRIPT
roadmap_1279_li=Improve time to open large databases (see mail 'init time for distributed setup')
roadmap_1280_li=Use ARRAY for fulltext search return value, at least internally in the native implementation (and as an option for the user)
roadmap_1281_li=Move Maven 2 repository from hsql.sf.net to h2database.sf.net
roadmap_1282_li=Java 1.5 tool\: JdbcUtils.closeSilently(s1, s2,...)
roadmap_1283_li=Javadoc\: document design patterns used
roadmap_1284_li=Triggers for metadata tables; use for PostgreSQL catalog
roadmap_1285_li=Does the FTP server has problems with multithreading?
roadmap_1286_li=Write an article about SQLInjection (h2\\src\\docsrc\\html\\images\\SQLInjection.txt)
roadmap_1287_li=Convert SQL-injection-2.txt to html document, include SQLInjection.java sample
roadmap_1288_li=Send SQL Injection solution proposal to MySQL, Derby, HSQLDB,...
roadmap_1289_li=Improve LOB in directories performance
roadmap_1290_li=Optimize OR conditions\: convert them to IN(...) if possible.
roadmap_1291_li=Web site design\: http\://www.igniterealtime.org/projects/openfire/index.jsp
roadmap_1292_li=HSQLDB compatibility\: Openfire server uses\: CREATE SCHEMA PUBLIC AUTHORIZATION DBA; CREATE USER SA PASSWORD ""; GRANT DBA TO SA; SET SCHEMA PUBLIC
roadmap_1293_li=Web site\: Rename Performance to Comparison [/Compatibility], move Comparison to Other Database Engines to Comparison, move Products that Work with H2 to Comparison, move Performance Tuning to Advanced Topics
roadmap_1294_li=Translation\: use ?? in help.csv
roadmap_1295_li=Translated .pdf
roadmap_1296_li=Cluster\: hot deploy (adding a node on runtime)
roadmap_1297_li=Test with PostgreSQL Version 8.2
roadmap_1298_li=Website\: Don't use frames.
roadmap_1299_li=Try again with Lobo browser (pure Java)
roadmap_1300_li=Recovery tool\: bad blocks should be converted to INSERT INTO SYSTEM_ERRORS(...), and things should go into the .trace.db file
roadmap_1301_li=RECOVER\=2 to backup the database, run recovery, open the database
roadmap_1302_li=Recovery should work with encrypted databases
roadmap_1303_li=Corruption\: new error code, add help
roadmap_1304_li=Space reuse\: after init, scan all storages and free those that don't belong to a live database object
roadmap_1305_li=SysProperties\: change everything to H2_...
roadmap_1306_li=Use FilterIn / FilterOut putStream?
roadmap_1307_li=Access rights\: add missing features (users should be 'owner' of objects; missing rights for sequences; dropping objects)
roadmap_1308_li=Support NOCACHE table option (Oracle)
roadmap_1309_li=Index usage for UPDATE ... WHERE .. IN (SELECT...)
roadmap_1310_li=Add regular javadocs (using the default doclet, but another css) to the homepage.
roadmap_1311_li=The database should be kept open for a longer time when using the server mode.
roadmap_1312_li=Javadocs\: for each tool, add a copy &amp; paste sample in the class level.
roadmap_1313_li=Javadocs\: add @author tags.
roadmap_1314_li=Fluent API for tools\: Server.createTcpServer().setPort(9081).setPassword(password).start();
roadmap_1315_li=MySQL compatibility\: real SQL statements for SHOW TABLES, DESCRIBE TEST (then remove from Shell)
roadmap_1316_li=Use a default delay of 1 second before closing a database.
roadmap_1317_li=Maven\: upload source code and javadocs as well.
roadmap_1318_li=Write (log) to system table before adding to internal data structures.
roadmap_1319_li=Support very large deletes and updates.
roadmap_1320_li=Doclet (javadocs)\: constructors are not listed.
roadmap_1321_li=Support direct lookup for MIN and MAX when using WHERE (see todo.txt / Direct Lookup).
roadmap_1322_li=Support other array types (String[], double[]) in PreparedStatement.setObject(int, Object);
roadmap_1323_li=MVCC should not be memory bound (uncommitted data is kept in memory in the delta index; maybe using a regular btree index solves the problem).
roadmap_1324_li=Support CREATE TEMPORARY LINKED TABLE.
roadmap_1325_li=MySQL compatibility\: SELECT @variable \:\= x FROM SYSTEM_RANGE(1, 50);
roadmap_1326_li=Oracle compatibility\: support NLS_DATE_FORMAT.
roadmap_1327_li=Support flashback queries as in Oracle.
roadmap_1328_li=Import / Export of fixed with text files.
roadmap_1329_li=Support for OUT parameters in user-defined procedures.
roadmap_1330_li=Support getGeneratedKeys to return multiple rows when used with batch updates. This is supported by MySQL, but not Derby. Both PostgreSQL and HSQLDB don't support getGeneratedKeys. Also support it when using INSERT ... SELECT.
roadmap_1331_li=HSQLDB compatibility\: automatic data type for SUM if value is the value is too big (by default use the same type as the data).
roadmap_1332_li=Improve the optimizer to select the right index for special cases\: where id between 2 and 4 and booleanColumn
roadmap_1333_li=Enable warning for 'Local variable declaration hides another field or variable'.
roadmap_1334_li=Linked tables\: make hidden columns available (Oracle\: rowid and ora_rowscn columns).
roadmap_1335_li=Support merge join.
roadmap_1336_li=H2 Console\: in-place autocomplete (need to merge query and result frame, use div).
roadmap_1337_li=MySQL compatibility\: update test1 t1, test2 t2 set t1.id \= t2.id where t1.id \= t2.id;
roadmap_1338_li=Oracle\: support DECODE method (convert to CASE WHEN).
roadmap_1339_li=Support large databases\: split LOB (BLOB, CLOB) to multiple directories / disks (similar to tablespaces).
roadmap_1340_li=Support to assign a primary key index a user defined name.
roadmap_1341_li=Cluster\: Add feature to make sure cluster nodes can not get out of sync (for example by stopping one process).
roadmap_1342_li=H2 Console\: support configuration option for fixed width (monospace) font.
roadmap_1343_li=Native fulltext search\: support analyzers (specially for Chinese, Japanese).
roadmap_1344_li=Automatically compact databases from time to time (as a background process).
roadmap_1345_li=Support GRANT SELECT, UPDATE ON *.
roadmap_1346_li=Test Eclipse DTP.
roadmap_1347_li=Support JMX\: Create an MBean for each database and server (support JConsole).
roadmap_1348_li=H2 Console\: autocomplete\: keep the previous setting
roadmap_1349_li=executeBatch\: option to stop at the first failed statement.
roadmap_1350_h2=Not Planned
roadmap_1351_li=HSQLDB (did) support this\: select id i from test where i>0 (other databases don't). Supporting it may break compatibility.
roadmap_1352_li=String.intern (so that Strings can be compared with \=\=) will not be used because some VMs have problems when used extensively.
search_1000_b=Search\:
search_1001_td=Highlight keyword(s)
search_1002_a=Home
......@@ -2724,102 +2735,103 @@ tutorial_1096_p=The server mode is similar, but it allows you to run the server
tutorial_1097_h3=Using a Servlet Listener to Start and Stop a Database
tutorial_1098_p=Add the h2.jar file your web application, and add the following snippet to your web.xml file (after context-param and before filter)\:
tutorial_1099_p=For details on how to access the database, see the code DbStarter.java
tutorial_1100_h2=CSV (Comma Separated Values) Support
tutorial_1101_p=The CSV file support can be used inside the database using the functions CSVREAD and CSVWRITE, and the CSV library can be used outside the database as a standalone tool.
tutorial_1102_h3=Writing a CSV File from Within a Database
tutorial_1103_p=The built-in function CSVWRITE can be used to create a CSV file from a query. Example\:
tutorial_1104_h3=Reading a CSV File from Within a Database
tutorial_1105_p=A CSV file can be read using the function CSVREAD. Example\:
tutorial_1106_h3=Writing a CSV File from a Java Application
tutorial_1107_p=The CSV tool can be used in a Java application even when not using a database at all. Example\:
tutorial_1108_h3=Reading a CSV File from a Java Application
tutorial_1109_p=It is possible to read a CSV file without opening a database. Example\:
tutorial_1110_h2=Upgrade, Backup, and Restore
tutorial_1111_h3=Database Upgrade
tutorial_1112_p=The recommended way to upgrade from one version of the database engine to the next version is to create a backup of the database (in the form of a SQL script) using the old engine, and then execute the SQL script using the new engine.
tutorial_1113_h3=Backup using the Script Tool
tutorial_1114_p=There are different ways to backup a database. For example, it is possible to copy the database files. However, this is not recommended while the database is in use. Also, the database files are not human readable and quite large. The recommended way to backup a database is to create a compressed SQL script file. This can be done using the Script tool\:
tutorial_1115_p=It is also possible to use the SQL command SCRIPT to create the backup of the database. For more information about the options, see the SQL command SCRIPT. The backup can be done remotely, however the file will be created on the server side. The built in FTP server could be used to retrieve the file from the server.
tutorial_1116_h3=Restore from a Script
tutorial_1117_p=To restore a database from a SQL script file, you can use the RunScript tool\:
tutorial_1118_p=For more information about the options, see the SQL command RUNSCRIPT. The restore can be done remotely, however the file needs to be on the server side. The built in FTP server could be used to copy the file to the server. It is also possible to use the SQL command RUNSCRIPT to execute a SQL script. SQL script files may contain references to other script files, in the form of RUNSCRIPT commands. However, when using the server mode, the references script files need to be available on the server side.
tutorial_1119_h3=Online Backup
tutorial_1120_p=The BACKUP SQL statement and the Backup tool both create a zip file with all database files. However, the contents of this file are not human readable. Other than the SCRIPT statement, the BACKUP statement does not lock the database objects, and therefore does not block other users. The resulting backup is transactionally consistent\:
tutorial_1121_p=The Backup tool (org.h2.tools.Backup) can not be used to create a online backup; the database must not be in use while running this program.
tutorial_1122_h2=Command Line Tools
tutorial_1123_p=This database comes with a number of command line tools. To get more information about a tool, start it with the parameter '-?', for example\:
tutorial_1124_p=The command line tools are\:
tutorial_1125_b=Backup
tutorial_1126_li=creates a backup of a database.
tutorial_1127_b=ChangeFileEncryption
tutorial_1128_li=allows changing the file encryption password or algorithm of a database.
tutorial_1129_b=Console
tutorial_1130_li=starts the browser based H2 Console.
tutorial_1131_b=ConvertTraceFile
tutorial_1132_li=converts a .trace.db file to a Java application and SQL script.
tutorial_1133_b=CreateCluster
tutorial_1134_li=creates a cluster from a standalone database.
tutorial_1135_b=DeleteDbFiles
tutorial_1136_li=deletes all files belonging to a database.
tutorial_1137_b=Script
tutorial_1138_li=allows converting a database to a SQL script for backup or migration.
tutorial_1139_b=Recover
tutorial_1140_li=helps recovering a corrupted database.
tutorial_1141_b=Restore
tutorial_1142_li=restores a backup of a database.
tutorial_1143_b=RunScript
tutorial_1144_li=runs a SQL script against a database.
tutorial_1145_b=Server
tutorial_1146_li=is used in the server mode to start a H2 server.
tutorial_1147_b=Shell
tutorial_1148_li=is a command line database tool.
tutorial_1149_p=The tools can also be called from an application by calling the main or another public methods. For details, see the Javadoc documentation.
tutorial_1150_h2=Using OpenOffice Base
tutorial_1151_p=OpenOffice.org Base supports database access over the JDBC API. To connect to a H2 database using OpenOffice Base, you first need to add the JDBC driver to OpenOffice. The steps to connect to a H2 database are\:
tutorial_1152_li=Start OpenOffice Writer, go to [Tools], [Options]
tutorial_1153_li=Make sure you have selected a Java runtime environment in OpenOffice.org / Java
tutorial_1154_li=Click [Class Path...], [Add Archive...]
tutorial_1155_li=Select your h2.jar (location is up to you, could be wherever you choose)
tutorial_1156_li=Click [OK] (as much as needed), stop OpenOffice (including the Quickstarter)
tutorial_1157_li=Start OpenOffice Base
tutorial_1158_li=Connect to an existing database; select JDBC; [Next]
tutorial_1159_li=Example datasource URL\: jdbc\:h2\:~/test
tutorial_1160_li=JDBC driver class\: org.h2.Driver
tutorial_1161_p=Now you can access the database stored in the current users home directory.
tutorial_1162_p=To use H2 in NeoOffice (OpenOffice without X11)\:
tutorial_1163_li=In NeoOffice, go to [NeoOffice], [Preferences]
tutorial_1164_li=Look for the page under [NeoOffice], [Java]
tutorial_1165_li=Click [Classpath], [Add Archive...]
tutorial_1166_li=Select your h2.jar (location is up to you, could be wherever you choose)
tutorial_1167_li=Click [OK] (as much as needed), restart NeoOffice.
tutorial_1168_p=Now, when creating a new database using the "Database Wizard"\:
tutorial_1169_li=Select "connect to existing database" and the type "jdbc". Click next.
tutorial_1170_li=Enter your h2 database URL. The normal behavior of H2 is that a new db is created if it doesn't exist.
tutorial_1171_li=Next step - up to you... you can just click finish and start working.
tutorial_1172_p=Another solution to use H2 in NeoOffice is\:
tutorial_1173_li=Package the h2 jar within an extension package
tutorial_1174_li=Install it as a Java extension in NeoOffice
tutorial_1175_p=This can be done by create it using the NetBeans OpenOffice plugin. See also <a href\="http\://wiki.services.openoffice.org/wiki/Extensions_development_java">Extensions Development</a> .
tutorial_1176_h2=Java Web Start / JNLP
tutorial_1177_p=When using Java Web Start / JNLP (Java Network Launch Protocol), permissions tags must be set in the .jnlp file, and the application .jar file must be signed. Otherwise, when trying to write to the file system, the following exception will occur\: java.security.AccessControlException\: access denied (java.io.FilePermission ... read). Example permission tags\:
tutorial_1178_h2=Using a Connection Pool
tutorial_1179_p=For many databases, opening a connection is slow, and it is a good idea to use a connection pool to re-use connections. For H2 however opening a connection usually is fast if the database is already open. Using a connection pool for H2 actually slows down the process a bit, except if file encryption is used (in this case opening a connection is about half as fast as using a connection pool). A simple connection pool is included in H2. It is based on the <a href\="http\://www.source-code.biz/snippets/java/8.htm">Mini Connection Pool Manager</a> from Christian d'Heureuse. There are other, more complex connection pools available, for example <a href\="http\://jakarta.apache.org/commons/dbcp/">DBCP</a> . The build-in connection pool is used as follows\:
tutorial_1180_h2=Fulltext Search
tutorial_1181_p=H2 supports Lucene full text search and native full text search implementation.
tutorial_1182_h3=Using the Native Full Text Search
tutorial_1183_p=To initialize, call\:
tutorial_1184_p=You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using\:
tutorial_1185_p=PUBLIC is the schema, TEST is the table name. The list of column names (column separated) is optional, in this case all columns are indexed. The index is updated in read time. To search the index, use the following query\:
tutorial_1186_p=You can also call the index from within a Java application\:
tutorial_1187_h3=Using the Lucene Fulltext Search
tutorial_1188_p=To use the Lucene full text search, you need the Lucene library in the classpath. How his is done depends on the application; if you use the H2 Console, you can add the Lucene jar file to the environment variables H2DRIVERS or CLASSPATH. To initialize the Lucene full text search in a database, call\:
tutorial_1189_p=You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using\:
tutorial_1190_p=PUBLIC is the schema, TEST is the table name. The list of column names (column separated) is optional, in this case all columns are indexed. The index is updated in read time. To search the index, use the following query\:
tutorial_1191_p=You can also call the index from within a Java application\:
tutorial_1192_h2=User-Defined Variables
tutorial_1193_p=This database supports user-defined variables. Variables start with @ and can be used wherever expressions or parameters are used. Variables not persisted and session scoped, that means only visible for the session where they are defined. A value is usually assigned using the SET command\:
tutorial_1194_p=It is also possible to change a value using the SET() method. This is useful in queries\:
tutorial_1195_p=Variables that are not set evaluate to NULL. The data type of a user-defined variable is the data type of the value assigned to it, that means it is not necessary (or possible) to declare variable names before using them. There are no restrictions on the assigned values; large objects (LOBs) are supported as well.
tutorial_1196_h2=Date and Time
tutorial_1197_p=Date, time and timestamp values support ISO 8601 formatting, including time zone\:
tutorial_1198_p=If the time zone is not set, the value is parsed using the current time zone setting of the system. Date and time information is stored in H2 database files in GMT (Greenwich Mean Time). If the database is opened using another system time zone, the date and time will change accordingly. If you want to move a database from one time zone to the other and don't want this to happen, you need to create a SQL script file using the SCRIPT command or Script tool, and then load the database using the RUNSCRIPT command or the RunScript tool in the new time zone.
tutorial_1100_p=By default the DbStarter listener opens a connection using the database URL jdbc\:h2\:~/test and user name and password 'sa'. It can also start the TCP server, however this is disabled by default. To enable it, use the db.tcpServer parameter in web.xml. Here is the complete list of options. These options are set just after the display-name and description tag, but before any listener and filter tags\:
tutorial_1101_h2=CSV (Comma Separated Values) Support
tutorial_1102_p=The CSV file support can be used inside the database using the functions CSVREAD and CSVWRITE, and the CSV library can be used outside the database as a standalone tool.
tutorial_1103_h3=Writing a CSV File from Within a Database
tutorial_1104_p=The built-in function CSVWRITE can be used to create a CSV file from a query. Example\:
tutorial_1105_h3=Reading a CSV File from Within a Database
tutorial_1106_p=A CSV file can be read using the function CSVREAD. Example\:
tutorial_1107_h3=Writing a CSV File from a Java Application
tutorial_1108_p=The CSV tool can be used in a Java application even when not using a database at all. Example\:
tutorial_1109_h3=Reading a CSV File from a Java Application
tutorial_1110_p=It is possible to read a CSV file without opening a database. Example\:
tutorial_1111_h2=Upgrade, Backup, and Restore
tutorial_1112_h3=Database Upgrade
tutorial_1113_p=The recommended way to upgrade from one version of the database engine to the next version is to create a backup of the database (in the form of a SQL script) using the old engine, and then execute the SQL script using the new engine.
tutorial_1114_h3=Backup using the Script Tool
tutorial_1115_p=There are different ways to backup a database. For example, it is possible to copy the database files. However, this is not recommended while the database is in use. Also, the database files are not human readable and quite large. The recommended way to backup a database is to create a compressed SQL script file. This can be done using the Script tool\:
tutorial_1116_p=It is also possible to use the SQL command SCRIPT to create the backup of the database. For more information about the options, see the SQL command SCRIPT. The backup can be done remotely, however the file will be created on the server side. The built in FTP server could be used to retrieve the file from the server.
tutorial_1117_h3=Restore from a Script
tutorial_1118_p=To restore a database from a SQL script file, you can use the RunScript tool\:
tutorial_1119_p=For more information about the options, see the SQL command RUNSCRIPT. The restore can be done remotely, however the file needs to be on the server side. The built in FTP server could be used to copy the file to the server. It is also possible to use the SQL command RUNSCRIPT to execute a SQL script. SQL script files may contain references to other script files, in the form of RUNSCRIPT commands. However, when using the server mode, the references script files need to be available on the server side.
tutorial_1120_h3=Online Backup
tutorial_1121_p=The BACKUP SQL statement and the Backup tool both create a zip file with all database files. However, the contents of this file are not human readable. Other than the SCRIPT statement, the BACKUP statement does not lock the database objects, and therefore does not block other users. The resulting backup is transactionally consistent\:
tutorial_1122_p=The Backup tool (org.h2.tools.Backup) can not be used to create a online backup; the database must not be in use while running this program.
tutorial_1123_h2=Command Line Tools
tutorial_1124_p=This database comes with a number of command line tools. To get more information about a tool, start it with the parameter '-?', for example\:
tutorial_1125_p=The command line tools are\:
tutorial_1126_b=Backup
tutorial_1127_li=creates a backup of a database.
tutorial_1128_b=ChangeFileEncryption
tutorial_1129_li=allows changing the file encryption password or algorithm of a database.
tutorial_1130_b=Console
tutorial_1131_li=starts the browser based H2 Console.
tutorial_1132_b=ConvertTraceFile
tutorial_1133_li=converts a .trace.db file to a Java application and SQL script.
tutorial_1134_b=CreateCluster
tutorial_1135_li=creates a cluster from a standalone database.
tutorial_1136_b=DeleteDbFiles
tutorial_1137_li=deletes all files belonging to a database.
tutorial_1138_b=Script
tutorial_1139_li=allows converting a database to a SQL script for backup or migration.
tutorial_1140_b=Recover
tutorial_1141_li=helps recovering a corrupted database.
tutorial_1142_b=Restore
tutorial_1143_li=restores a backup of a database.
tutorial_1144_b=RunScript
tutorial_1145_li=runs a SQL script against a database.
tutorial_1146_b=Server
tutorial_1147_li=is used in the server mode to start a H2 server.
tutorial_1148_b=Shell
tutorial_1149_li=is a command line database tool.
tutorial_1150_p=The tools can also be called from an application by calling the main or another public methods. For details, see the Javadoc documentation.
tutorial_1151_h2=Using OpenOffice Base
tutorial_1152_p=OpenOffice.org Base supports database access over the JDBC API. To connect to a H2 database using OpenOffice Base, you first need to add the JDBC driver to OpenOffice. The steps to connect to a H2 database are\:
tutorial_1153_li=Start OpenOffice Writer, go to [Tools], [Options]
tutorial_1154_li=Make sure you have selected a Java runtime environment in OpenOffice.org / Java
tutorial_1155_li=Click [Class Path...], [Add Archive...]
tutorial_1156_li=Select your h2.jar (location is up to you, could be wherever you choose)
tutorial_1157_li=Click [OK] (as much as needed), stop OpenOffice (including the Quickstarter)
tutorial_1158_li=Start OpenOffice Base
tutorial_1159_li=Connect to an existing database; select JDBC; [Next]
tutorial_1160_li=Example datasource URL\: jdbc\:h2\:~/test
tutorial_1161_li=JDBC driver class\: org.h2.Driver
tutorial_1162_p=Now you can access the database stored in the current users home directory.
tutorial_1163_p=To use H2 in NeoOffice (OpenOffice without X11)\:
tutorial_1164_li=In NeoOffice, go to [NeoOffice], [Preferences]
tutorial_1165_li=Look for the page under [NeoOffice], [Java]
tutorial_1166_li=Click [Classpath], [Add Archive...]
tutorial_1167_li=Select your h2.jar (location is up to you, could be wherever you choose)
tutorial_1168_li=Click [OK] (as much as needed), restart NeoOffice.
tutorial_1169_p=Now, when creating a new database using the "Database Wizard"\:
tutorial_1170_li=Select "connect to existing database" and the type "jdbc". Click next.
tutorial_1171_li=Enter your h2 database URL. The normal behavior of H2 is that a new db is created if it doesn't exist.
tutorial_1172_li=Next step - up to you... you can just click finish and start working.
tutorial_1173_p=Another solution to use H2 in NeoOffice is\:
tutorial_1174_li=Package the h2 jar within an extension package
tutorial_1175_li=Install it as a Java extension in NeoOffice
tutorial_1176_p=This can be done by create it using the NetBeans OpenOffice plugin. See also <a href\="http\://wiki.services.openoffice.org/wiki/Extensions_development_java">Extensions Development</a> .
tutorial_1177_h2=Java Web Start / JNLP
tutorial_1178_p=When using Java Web Start / JNLP (Java Network Launch Protocol), permissions tags must be set in the .jnlp file, and the application .jar file must be signed. Otherwise, when trying to write to the file system, the following exception will occur\: java.security.AccessControlException\: access denied (java.io.FilePermission ... read). Example permission tags\:
tutorial_1179_h2=Using a Connection Pool
tutorial_1180_p=For many databases, opening a connection is slow, and it is a good idea to use a connection pool to re-use connections. For H2 however opening a connection usually is fast if the database is already open. Using a connection pool for H2 actually slows down the process a bit, except if file encryption is used (in this case opening a connection is about half as fast as using a connection pool). A simple connection pool is included in H2. It is based on the <a href\="http\://www.source-code.biz/snippets/java/8.htm">Mini Connection Pool Manager</a> from Christian d'Heureuse. There are other, more complex connection pools available, for example <a href\="http\://jakarta.apache.org/commons/dbcp/">DBCP</a> . The build-in connection pool is used as follows\:
tutorial_1181_h2=Fulltext Search
tutorial_1182_p=H2 supports Lucene full text search and native full text search implementation.
tutorial_1183_h3=Using the Native Full Text Search
tutorial_1184_p=To initialize, call\:
tutorial_1185_p=You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using\:
tutorial_1186_p=PUBLIC is the schema, TEST is the table name. The list of column names (column separated) is optional, in this case all columns are indexed. The index is updated in read time. To search the index, use the following query\:
tutorial_1187_p=You can also call the index from within a Java application\:
tutorial_1188_h3=Using the Lucene Fulltext Search
tutorial_1189_p=To use the Lucene full text search, you need the Lucene library in the classpath. How his is done depends on the application; if you use the H2 Console, you can add the Lucene jar file to the environment variables H2DRIVERS or CLASSPATH. To initialize the Lucene full text search in a database, call\:
tutorial_1190_p=You need to initialize it in each database where you want to use it. Afterwards, you can create a full text index for a table using\:
tutorial_1191_p=PUBLIC is the schema, TEST is the table name. The list of column names (column separated) is optional, in this case all columns are indexed. The index is updated in read time. To search the index, use the following query\:
tutorial_1192_p=You can also call the index from within a Java application\:
tutorial_1193_h2=User-Defined Variables
tutorial_1194_p=This database supports user-defined variables. Variables start with @ and can be used wherever expressions or parameters are used. Variables not persisted and session scoped, that means only visible for the session where they are defined. A value is usually assigned using the SET command\:
tutorial_1195_p=It is also possible to change a value using the SET() method. This is useful in queries\:
tutorial_1196_p=Variables that are not set evaluate to NULL. The data type of a user-defined variable is the data type of the value assigned to it, that means it is not necessary (or possible) to declare variable names before using them. There are no restrictions on the assigned values; large objects (LOBs) are supported as well.
tutorial_1197_h2=Date and Time
tutorial_1198_p=Date, time and timestamp values support ISO 8601 formatting, including time zone\:
tutorial_1199_p=If the time zone is not set, the value is parsed using the current time zone setting of the system. Date and time information is stored in H2 database files in GMT (Greenwich Mean Time). If the database is opened using another system time zone, the date and time will change accordingly. If you want to move a database from one time zone to the other and don't want this to happen, you need to create a SQL script file using the SCRIPT command or Script tool, and then load the database using the RUNSCRIPT command or the RunScript tool in the new time zone.
h2/src/main/org/h2/server/web/DbStarter.java
浏览文件 @ 755bd88a
......@@ -46,7 +46,7 @@ public class DbStarter implements ServletContextListener {
server = Server.createTcpServer(params);
server.start();
}
// To access the database using the server, use the URL:
// To access the database in server mode, use the database URL:
// jdbc:h2:tcp://localhost/~/test
} catch (Exception e) {
......
h2/src/main/org/h2/tools/ConvertTraceFile.java
浏览文件 @ 755bd88a
......@@ -175,7 +175,7 @@ public class ConvertTraceFile extends Tool {
if (stats.size() > 0) {
scriptWriter.println("-----------------------------------------");
scriptWriter.println("-- SQL Statement Statistics");
scriptWriter.println("-- time: total time in milliseconds");
scriptWriter.println("-- time: total time in milliseconds (accumulated)");
scriptWriter.println("-- count: how many times the statement ran");
scriptWriter.println("-- result: total update count or row count");
scriptWriter.println("-----------------------------------------");
......
h2/src/tools/org/h2/build/Build.java
浏览文件 @ 755bd88a
......@@ -369,6 +369,7 @@ public class Build extends BuildBase {
private void resources(boolean clientOnly) {
FileList files = getFiles("src/main").
exclude("*.MF").
exclude("*.java").
exclude("*/package.html").
exclude("*/java.sql.Driver");
......
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