Return long results from row number and rank functions

h2/src/docsrc/help/help.csv

@@ -5335,10 +5335,10 @@ SELECT CUME_DIST() OVER (PARTITION BY CATEGORY ORDER BY ID), * FROM TEST;
 "
 
 "Functions (Window)","NTILE","
-NTILE(int) OVER windowNameOrSpecification
+NTILE(long) OVER windowNameOrSpecification
 ","
 Distributes the rows into a specified number of groups.
-Number of groups should be a positive integer value.
+Number of groups should be a positive long value.
 NTILE returns the 1-based number of the group to which the current row belongs.
 First groups will have more rows if number of rows is not divisible by number of groups.
 For example, if 5 rows are distributed into 2 groups this function returns 1 for the first 3 row and 2 for the last 2 rows.

h2/src/main/org/h2/expression/analysis/WindowFunction.java

@@ -18,7 +18,7 @@ import org.h2.table.ColumnResolver;
 import org.h2.table.TableFilter;
 import org.h2.value.Value;
 import org.h2.value.ValueDouble;
-import org.h2.value.ValueInt;
+import org.h2.value.ValueLong;
 import org.h2.value.ValueNull;
 
 /**
@@ -184,7 +184,7 @@ public class WindowFunction extends DataAnalysisOperation {
         switch (type) {
         case ROW_NUMBER:
             for (int i = 0, size = ordered.size(); i < size;) {
-                result.put(ordered.get(i)[rowIdColumn].getInt(), ValueInt.get(++i));
+                result.put(ordered.get(i)[rowIdColumn].getInt(), ValueLong.get(++i));
             }
             break;
         case RANK:
@@ -231,7 +231,7 @@ public class WindowFunction extends DataAnalysisOperation {
                 int nm = number - 1;
                 v = nm == 0 ? ValueDouble.ZERO : ValueDouble.get((double) nm / (size - 1));
             } else {
-                v = ValueInt.get(number);
+                v = ValueLong.get(number);
             }
             result.put(row[rowIdColumn].getInt(), v);
         }
@@ -260,20 +260,20 @@ public class WindowFunction extends DataAnalysisOperation {
         int size = orderedData.size();
         for (int i = 0; i < size; i++) {
             Value[] array = orderedData.get(i);
-            int buckets = array[0].getInt();
+            long buckets = array[0].getLong();
             if (buckets <= 0) {
                 throw DbException.getInvalidValueException("number of tiles", buckets);
             }
-            int perTile = size / buckets;
-            int numLarger = size - perTile * buckets;
-            int largerGroup = numLarger * (perTile + 1);
-            int v;
+            long perTile = size / buckets;
+            long numLarger = size - perTile * buckets;
+            long largerGroup = numLarger * (perTile + 1);
+            long v;
             if (i >= largerGroup) {
                 v = (i - largerGroup) / perTile + numLarger + 1;
             } else {
                 v = i / (perTile + 1) + 1;
             }
-            result.put(orderedData.get(i)[last].getInt(), ValueInt.get(v));
+            result.put(orderedData.get(i)[last].getInt(), ValueLong.get(v));
         }
     }
 
@@ -441,7 +441,7 @@ public class WindowFunction extends DataAnalysisOperation {
         case RANK:
         case DENSE_RANK:
         case NTILE:
-            return Value.INT;
+            return Value.LONG;
         case PERCENT_RANK:
         case CUME_DIST:
             return Value.DOUBLE;
@@ -477,7 +477,7 @@ public class WindowFunction extends DataAnalysisOperation {
         case RANK:
         case DENSE_RANK:
         case NTILE:
-            return ValueInt.PRECISION;
+            return ValueLong.PRECISION;
         case PERCENT_RANK:
         case CUME_DIST:
             return ValueDouble.PRECISION;
@@ -499,7 +499,7 @@ public class WindowFunction extends DataAnalysisOperation {
         case RANK:
         case DENSE_RANK:
         case NTILE:
-            return ValueInt.DISPLAY_SIZE;
+            return ValueLong.DISPLAY_SIZE;
         case PERCENT_RANK:
         case CUME_DIST:
             return ValueDouble.DISPLAY_SIZE;