haohuaijin opened a new pull request, #8124: URL: https://github.com/apache/arrow-datafusion/pull/8124
## Which issue does this PR close?
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Closes #8123
## Rationale for this change
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In this pr
```
❯ SELECT "RegionID", SUM("AdvEngineID"), COUNT(DISTINCT "UserID") FROM
'../benchmarks/data/hits.parquet' GROUP BY "RegionID" order by "RegionID" limit
10;
+----------+--------------------------------------------------+--------------------------------------------------------+
| RegionID | SUM(../benchmarks/data/hits.parquet.AdvEngineID) |
COUNT(DISTINCT ../benchmarks/data/hits.parquet.UserID) |
+----------+--------------------------------------------------+--------------------------------------------------------+
| 0 | 0 | 8
|
| 1 | 147946 | 239380
|
| 2 | 441662 | 1081016
|
| 3 | 39724 | 131195
|
| 4 | 34557 | 79500
|
| 5 | 13502 | 40914
|
| 6 | 24338 | 55768
|
| 7 | 28417 | 64989
|
| 8 | 34483 | 65472
|
| 9 | 38047 | 91576
|
+----------+--------------------------------------------------+--------------------------------------------------------+
10 rows in set. Query took 0.945 seconds.
❯ explain SELECT "RegionID", SUM("AdvEngineID"), COUNT(DISTINCT "UserID")
FROM '../benchmarks/data/hits.parquet' GROUP BY "RegionID" order by "RegionID"
limit 10;
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan
|
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | Limit: skip=0, fetch=10
|
| | Sort: ../benchmarks/data/hits.parquet.RegionID ASC NULLS
LAST, fetch=10
|
| | Aggregate:
groupBy=[[../benchmarks/data/hits.parquet.RegionID]], aggr=[[SUM(alias2) AS
SUM(../benchmarks/data/hits.parquet.AdvEngineID), COUNT(alias1) AS
COUNT(DISTINCT ../benchmarks/data/hits.parquet.UserID)]]
|
| | Aggregate:
groupBy=[[../benchmarks/data/hits.parquet.RegionID,
../benchmarks/data/hits.parquet.UserID AS alias1]],
aggr=[[SUM(CAST(../benchmarks/data/hits.parquet.AdvEngineID AS Int64)) AS
alias2]]
|
| | TableScan: ../benchmarks/data/hits.parquet
projection=[RegionID, UserID, AdvEngineID]
|
| physical_plan | GlobalLimitExec: skip=0, fetch=10
|
| | SortPreservingMergeExec: [RegionID@0 ASC NULLS LAST],
fetch=10
|
| | SortExec: TopK(fetch=10), expr=[RegionID@0 ASC NULLS
LAST]
|
| | AggregateExec: mode=FinalPartitioned,
gby=[RegionID@0 as RegionID],
aggr=[SUM(../benchmarks/data/hits.parquet.AdvEngineID), COUNT(DISTINCT
../benchmarks/data/hits.parquet.UserID)]
|
| | CoalesceBatchesExec: target_batch_size=8192
|
| | RepartitionExec: partitioning=Hash([RegionID@0],
24), input_partitions=24
|
| | AggregateExec: mode=Partial, gby=[RegionID@0
as RegionID], aggr=[SUM(../benchmarks/data/hits.parquet.AdvEngineID),
COUNT(DISTINCT ../benchmarks/data/hits.parquet.UserID)]
|
| | AggregateExec: mode=FinalPartitioned,
gby=[RegionID@0 as RegionID, alias1@1 as alias1], aggr=[alias2]
|
| | CoalesceBatchesExec:
target_batch_size=8192
|
| | RepartitionExec:
partitioning=Hash([RegionID@0, alias1@1], 24), input_partitions=24
|
| | AggregateExec: mode=Partial,
gby=[RegionID@0 as RegionID, UserID@1 as alias1], aggr=[alias2]
|
| | ParquetExec: file_groups={24 groups:
[[home/hhj/datafusion/benchmarks/data/hits.parquet:0..615832352],
[home/hhj/datafusion/benchmarks/data/hits.parquet:615832352..1231664704],
[home/hhj/datafusion/benchmarks/data/hits.parquet:1231664704..1847497056],
[home/hhj/datafusion/benchmarks/data/hits.parquet:1847497056..2463329408],
[home/hhj/datafusion/benchmarks/data/hits.parquet:2463329408..3079161760],
...]}, projection=[RegionID, UserID, AdvEngineID] |
| |
|
+---------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
2 rows in set. Query took 0.043 seconds.
```
in main 43cc870a951611e9081a462d5a8a1686e87fce9a
```
❯ SELECT "RegionID", SUM("AdvEngineID"), COUNT(DISTINCT "UserID") FROM
'../benchmarks/data/hits.parquet' GROUP BY "RegionID" order by "RegionID" limit
10;
+----------+--------------------------------------------------+--------------------------------------------------------+
| RegionID | SUM(../benchmarks/data/hits.parquet.AdvEngineID) |
COUNT(DISTINCT ../benchmarks/data/hits.parquet.UserID) |
+----------+--------------------------------------------------+--------------------------------------------------------+
| 0 | 0 | 8
|
| 1 | 147946 | 239380
|
| 2 | 441662 | 1081016
|
| 3 | 39724 | 131195
|
| 4 | 34557 | 79500
|
| 5 | 13502 | 40914
|
| 6 | 24338 | 55768
|
| 7 | 28417 | 64989
|
| 8 | 34483 | 65472
|
| 9 | 38047 | 91576
|
+----------+--------------------------------------------------+--------------------------------------------------------+
10 rows in set. Query took 1.343 seconds.
❯ explain SELECT "RegionID", SUM("AdvEngineID"), COUNT(DISTINCT "UserID")
FROM '../benchmarks/data/hits.parquet' GROUP BY "RegionID" order by "RegionID"
limit 10;
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| plan_type | plan
|
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| logical_plan | Limit: skip=0, fetch=10
|
| | Sort: ../benchmarks/data/hits.parquet.RegionID ASC NULLS
LAST, fetch=10
|
| | Aggregate:
groupBy=[[../benchmarks/data/hits.parquet.RegionID]],
aggr=[[SUM(CAST(../benchmarks/data/hits.parquet.AdvEngineID AS Int64)),
COUNT(DISTINCT ../benchmarks/data/hits.parquet.UserID)]]
|
| | TableScan: ../benchmarks/data/hits.parquet
projection=[RegionID, UserID, AdvEngineID]
|
| physical_plan | GlobalLimitExec: skip=0, fetch=10
|
| | SortPreservingMergeExec: [RegionID@0 ASC NULLS LAST],
fetch=10
|
| | SortExec: TopK(fetch=10), expr=[RegionID@0 ASC NULLS
LAST]
|
| | AggregateExec: mode=FinalPartitioned,
gby=[RegionID@0 as RegionID],
aggr=[SUM(../benchmarks/data/hits.parquet.AdvEngineID), COUNT(DISTINCT
../benchmarks/data/hits.parquet.UserID)]
|
| | CoalesceBatchesExec: target_batch_size=8192
|
| | RepartitionExec: partitioning=Hash([RegionID@0],
24), input_partitions=24
|
| | AggregateExec: mode=Partial, gby=[RegionID@0
as RegionID], aggr=[SUM(../benchmarks/data/hits.parquet.AdvEngineID),
COUNT(DISTINCT ../benchmarks/data/hits.parquet.UserID)]
|
| | ParquetExec: file_groups={24 groups:
[[home/hhj/datafusion/benchmarks/data/hits.parquet:0..615832352],
[home/hhj/datafusion/benchmarks/data/hits.parquet:615832352..1231664704],
[home/hhj/datafusion/benchmarks/data/hits.parquet:1231664704..1847497056],
[home/hhj/datafusion/benchmarks/data/hits.parquet:1847497056..2463329408],
[home/hhj/datafusion/benchmarks/data/hits.parquet:2463329408..3079161760],
...]}, projection=[RegionID, UserID, AdvEngineID] |
| |
|
+---------------+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
2 rows in set. Query took 0.054 seconds.
```
## What changes are included in this PR?
add no-distinct count/sum/min/max aggregate support in
`single_distinct_to_group_by` rule
<!--
There is no need to duplicate the description in the issue here but it is
sometimes worth providing a summary of the individual changes in this PR.
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## Are these changes tested?
yes, add soem tests
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2. Serve as another way to document the expected behavior of the code
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## Are there any user-facing changes?
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