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[WIP] Support GpuCollectList/GpuCollectSet in groupBy aggregation #2804

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[WIP] Support GpuCollectList/GpuCollectSet in groupBy aggregation #2804

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005237f
support GpuGroupByCollect
sperlingxx Jun 24, 2021
7854511
Merge remote-tracking branch 'origin/branch-21.08' into collect_ops_g…
sperlingxx Jun 24, 2021
3ac68e1
little updates
sperlingxx Jun 24, 2021
c5590c2
update docs
sperlingxx Jun 24, 2021
c3275ea
remove test code
sperlingxx Jun 24, 2021
211ad04
small fix
sperlingxx Jun 24, 2021
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5 changes: 3 additions & 2 deletions docs/configs.md
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Original file line number Diff line number Diff line change
Expand Up @@ -290,8 +290,8 @@ Name | SQL Function(s) | Description | Default Value | Notes
<a name="sql.expression.Year"></a>spark.rapids.sql.expression.Year|`year`|Returns the year from a date or timestamp|true|None|
<a name="sql.expression.AggregateExpression"></a>spark.rapids.sql.expression.AggregateExpression| |Aggregate expression|true|None|
<a name="sql.expression.Average"></a>spark.rapids.sql.expression.Average|`avg`, `mean`|Average aggregate operator|true|None|
<a name="sql.expression.CollectList"></a>spark.rapids.sql.expression.CollectList|`collect_list`|Collect a list of non-unique elements, only supported in rolling window in current.|true|None|
<a name="sql.expression.CollectSet"></a>spark.rapids.sql.expression.CollectSet|`collect_set`|Collect a set of unique elements, only supported in rolling window in current.|true|None|
<a name="sql.expression.CollectList"></a>spark.rapids.sql.expression.CollectList|`collect_list`|Collect a list of non-unique elements, NOT yet supported in reduction.|true|None|
<a name="sql.expression.CollectSet"></a>spark.rapids.sql.expression.CollectSet|`collect_set`|Collect a set of unique elements, NOT yet supported in reduction.|true|None|
<a name="sql.expression.Count"></a>spark.rapids.sql.expression.Count|`count`|Count aggregate operator|true|None|
<a name="sql.expression.First"></a>spark.rapids.sql.expression.First|`first_value`, `first`|first aggregate operator|true|None|
<a name="sql.expression.Last"></a>spark.rapids.sql.expression.Last|`last`, `last_value`|last aggregate operator|true|None|
Expand Down Expand Up @@ -323,6 +323,7 @@ Name | Description | Default Value | Notes
<a name="sql.exec.UnionExec"></a>spark.rapids.sql.exec.UnionExec|The backend for the union operator|true|None|
<a name="sql.exec.CustomShuffleReaderExec"></a>spark.rapids.sql.exec.CustomShuffleReaderExec|A wrapper of shuffle query stage|true|None|
<a name="sql.exec.HashAggregateExec"></a>spark.rapids.sql.exec.HashAggregateExec|The backend for hash based aggregations|true|None|
<a name="sql.exec.ObjectHashAggregateExec"></a>spark.rapids.sql.exec.ObjectHashAggregateExec|The backend for hash based aggregations|true|None|
<a name="sql.exec.SortAggregateExec"></a>spark.rapids.sql.exec.SortAggregateExec|The backend for sort based aggregations|true|None|
<a name="sql.exec.DataWritingCommandExec"></a>spark.rapids.sql.exec.DataWritingCommandExec|Writing data|true|None|
<a name="sql.exec.BatchScanExec"></a>spark.rapids.sql.exec.BatchScanExec|The backend for most file input|true|None|
Expand Down
155 changes: 89 additions & 66 deletions docs/supported_ops.md
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Expand Up @@ -495,6 +495,29 @@ Accelerator supports are described below.
<th>UDT</th>
</tr>
<tr>
<td>ObjectHashAggregateExec</td>
<td>The backend for hash based aggregations</td>
<td>None</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S*</td>
<td>S</td>
<td>S*</td>
<td>S</td>
<td><em>PS (Marking BINARY as plugin-supported is only to adapt the BINARY aggregation buffers of TypedImperativeAggregate.)</em></td>
<td><b>NS</b></td>
<td><em>PS* (not allowed for grouping expressions; missing nested BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><em>PS* (not allowed for grouping expressions; missing nested BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><em>PS* (not allowed for grouping expressions; missing nested BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><b>NS</b></td>
</tr>
<tr>
<td>SortAggregateExec</td>
<td>The backend for sort based aggregations</td>
<td>None</td>
Expand Down Expand Up @@ -602,11 +625,11 @@ Accelerator supports are described below.
<td>S</td>
<td>S*</td>
<td>S</td>
<td><em>PS (Marking BINARY as plugin-supported is only to adapt the BINARY aggregation buffers of TypedImperativeAggregate.)</em></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><em>PS* (Round-robin partitioning is not supported if spark.sql.execution.sortBeforeRepartition is true; missing nested BINARY, CALENDAR, MAP, UDT)</em></td>
<td><em>PS* (Round-robin partitioning is not supported if spark.sql.execution.sortBeforeRepartition is true; missing nested BINARY, CALENDAR, MAP, UDT)</em></td>
<td><em>PS* (Round-robin partitioning is not supported for nested structs if spark.sql.execution.sortBeforeRepartition is true; missing nested BINARY, CALENDAR, MAP, UDT)</em></td>
<td><em>PS* (Round-robin partitioning is not supported if spark.sql.execution.sortBeforeRepartition is true; missing nested CALENDAR, MAP, UDT)</em></td>
<td><em>PS* (Round-robin partitioning is not supported if spark.sql.execution.sortBeforeRepartition is true; missing nested CALENDAR, MAP, UDT)</em></td>
<td><em>PS* (Round-robin partitioning is not supported for nested structs if spark.sql.execution.sortBeforeRepartition is true; missing nested CALENDAR, MAP, UDT)</em></td>
<td><b>NS</b></td>
</tr>
<tr>
Expand Down Expand Up @@ -817,29 +840,6 @@ Accelerator supports are described below.
<td><b>NS</b></td>
</tr>
<tr>
<td>WindowInPandasExec</td>
<td>The backend for Window Aggregation Pandas UDF, Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled. For now it only supports row based window frame.</td>
<td>This is disabled by default because it only supports row based frame for now</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S*</td>
<td>S</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><em>PS* (missing nested DECIMAL, NULL, BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
</tr>
<tr>
<th>Executor</th>
<th>Description</th>
<th>Notes</th>
Expand All @@ -863,6 +863,29 @@ Accelerator supports are described below.
<th>UDT</th>
</tr>
<tr>
<td>WindowInPandasExec</td>
<td>The backend for Window Aggregation Pandas UDF, Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled. For now it only supports row based window frame.</td>
<td>This is disabled by default because it only supports row based frame for now</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S*</td>
<td>S</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><em>PS* (missing nested DECIMAL, NULL, BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
</tr>
<tr>
<td>WindowExec</td>
<td>Window-operator backend</td>
<td>None</td>
Expand Down Expand Up @@ -2243,11 +2266,11 @@ Accelerator support is described below.
<td>S</td>
<td>S*</td>
<td>S</td>
<td>S</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><em>PS* (missing nested BINARY, CALENDAR, UDT)</em></td>
<td><em>PS* (missing nested BINARY, CALENDAR, UDT)</em></td>
<td><em>PS* (missing nested BINARY, CALENDAR, UDT)</em></td>
<td><em>PS* (missing nested CALENDAR, UDT)</em></td>
<td><em>PS* (missing nested CALENDAR, UDT)</em></td>
<td><em>PS* (missing nested CALENDAR, UDT)</em></td>
<td><b>NS</b></td>
</tr>
<tr>
Expand Down Expand Up @@ -18305,9 +18328,9 @@ Accelerator support is described below.
<tr>
<td rowSpan="6">CollectList</td>
<td rowSpan="6">`collect_list`</td>
<td rowSpan="6">Collect a list of non-unique elements, only supported in rolling window in current.</td>
<td rowSpan="6">Collect a list of non-unique elements, NOT yet supported in reduction.</td>
<td rowSpan="6">None</td>
<td rowSpan="2">aggregation</td>
<td rowSpan="2">reduction</td>
<td>input</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
Expand Down Expand Up @@ -18350,25 +18373,25 @@ Accelerator support is described below.
<td> </td>
</tr>
<tr>
<td rowSpan="2">reduction</td>
<td rowSpan="2">aggregation</td>
<td>input</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S*</td>
<td>S</td>
<td>S*</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><em>PS* (missing nested NULL, BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><b>NS</b></td>
</tr>
<tr>
Expand All @@ -18387,7 +18410,7 @@ Accelerator support is described below.
<td> </td>
<td> </td>
<td> </td>
<td><b>NS</b></td>
<td><em>PS* (missing nested NULL, CALENDAR, ARRAY, MAP, UDT)</em></td>
<td> </td>
<td> </td>
<td> </td>
Expand Down Expand Up @@ -18430,17 +18453,17 @@ Accelerator support is described below.
<td> </td>
<td> </td>
<td> </td>
<td><em>PS* (missing nested NULL, BINARY, CALENDAR, ARRAY, MAP, UDT)</em></td>
<td><em>PS* (missing nested NULL, CALENDAR, ARRAY, MAP, UDT)</em></td>
<td> </td>
<td> </td>
<td> </td>
</tr>
<tr>
<td rowSpan="6">CollectSet</td>
<td rowSpan="6">`collect_set`</td>
<td rowSpan="6">Collect a set of unique elements, only supported in rolling window in current.</td>
<td rowSpan="6">Collect a set of unique elements, NOT yet supported in reduction.</td>
<td rowSpan="6">None</td>
<td rowSpan="2">aggregation</td>
<td rowSpan="2">reduction</td>
<td>input</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
Expand Down Expand Up @@ -18483,19 +18506,19 @@ Accelerator support is described below.
<td> </td>
</tr>
<tr>
<td rowSpan="2">reduction</td>
<td rowSpan="2">aggregation</td>
<td>input</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S</td>
<td>S*</td>
<td>S</td>
<td>S*</td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
Expand All @@ -18520,7 +18543,7 @@ Accelerator support is described below.
<td> </td>
<td> </td>
<td> </td>
<td><b>NS</b></td>
<td><em>PS* (missing nested NULL, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td> </td>
<td> </td>
<td> </td>
Expand Down Expand Up @@ -18563,7 +18586,7 @@ Accelerator support is described below.
<td> </td>
<td> </td>
<td> </td>
<td><em>PS* (missing nested NULL, BINARY, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td><em>PS* (missing nested NULL, CALENDAR, ARRAY, MAP, STRUCT, UDT)</em></td>
<td> </td>
<td> </td>
<td> </td>
Expand Down Expand Up @@ -20751,11 +20774,11 @@ as `a` don't show up in the table. They are controlled by the rules for
<td>S</td>
<td>S*</td>
<td>S</td>
<td><em>PS (Marking BINARY as plugin-supported is only to adapt the BINARY aggregation buffers of TypedImperativeAggregate.)</em></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><b>NS</b></td>
<td><em>PS* (missing nested BINARY, CALENDAR, ARRAY, MAP, UDT)</em></td>
<td><em>PS* (missing nested CALENDAR, ARRAY, MAP, UDT)</em></td>
<td><b>NS</b></td>
</tr>
<tr>
Expand Down
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