lgbo-ustc opened a new issue, #7087:
URL: https://github.com/apache/incubator-gluten/issues/7087
### Description
Part of #6067.
For ds q44, the phyiscal plan is
```
CHNativeColumnarToRow
+- TakeOrderedAndProjectExecTransformer (limit=100, orderBy=[rnk#74 ASC
NULLS FIRST], output=[rnk#74,best_performing#80,worst_performing#81])
+- ^(16) ProjectExecTransformer [rnk#74, i_product_name#135 AS
best_performing#80, i_product_name#180 AS worst_performing#81]
+- ^(16) CHSortMergeJoinExecTransformer [item_sk#75L],
[i_item_sk#159L], Inner, false
:- ^(16) SortExecTransformer [item_sk#75L ASC NULLS FIRST], false, 0
: +- ^(16) InputIteratorTransformer[rnk#74, item_sk#75L,
i_product_name#135]
: +- ColumnarExchange hashpartitioning(item_sk#75L, 5),
ENSURE_REQUIREMENTS, [plan_id=1465], [shuffle_writer_type=hash], [OUTPUT]
List(rnk:IntegerType, item_sk:LongType, i_product_name:StringType)
: +- ^(14) ProjectExecTransformer [rnk#74, item_sk#75L,
i_product_name#135]
: +- ^(14) CHSortMergeJoinExecTransformer [item_sk#70L],
[i_item_sk#114L], Inner, false
: :- ^(14) SortExecTransformer [item_sk#70L ASC NULLS
FIRST], false, 0
: : +- ^(14) InputIteratorTransformer[item_sk#70L,
rnk#74, item_sk#75L]
: : +- ColumnarExchange
hashpartitioning(item_sk#70L, 5), ENSURE_REQUIREMENTS, [plan_id=1407],
[shuffle_writer_type=hash], [OUTPUT] List(item_sk:LongType, rnk:IntegerType,
item_sk:LongType)
: : +- ^(12) ProjectExecTransformer
[item_sk#70L, rnk#74, item_sk#75L]
: : +- ^(12) CHSortMergeJoinExecTransformer
[rnk#74], [rnk#79], Inner, false
: : :- ^(12) SortExecTransformer [rnk#74
ASC NULLS FIRST], false, 0
: : : +- ^(12) ProjectExecTransformer
[item_sk#70L, rnk#74]
: : : +- ^(12) FilterExecTransformer
((rnk#74 < 11) AND isnotnull(item_sk#70L))
: : : +- ^(12)
WindowExecTransformer [rank(rank_col#71) windowspecdefinition(rank_col#71 ASC
NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(),
currentrow$())) AS rnk#74], [rank_col#71 ASC NULLS FIRST]
: : : +- ^(12)
InputIteratorTransformer[item_sk#70L, rank_col#71]
: : : +-
RowToCHNativeColumnar
: : : +- WindowGroupLimit
[rank_col#71 ASC NULLS FIRST], rank(rank_col#71), 10, Final
: : : +-
CHNativeColumnarToRow
: : : +- ^(8)
SortExecTransformer [rank_col#71 ASC NULLS FIRST], false, 0
: : : +- ^(8)
InputIteratorTransformer[item_sk#70L, rank_col#71]
: : : +-
ColumnarExchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=1210],
[shuffle_writer_type=hash], [OUTPUT] List(item_sk:LongType,
rank_col:DecimalType(11,6))
: : : +-
RowToCHNativeColumnar
: : :
+- WindowGroupLimit [rank_col#71 ASC NULLS FIRST], rank(rank_col#71), 10,
Partial
: : :
+- CHNativeColumnarToRow
: : :
+- ^(7) SortExecTransformer [rank_col#71 ASC NULLS FIRST], false, 0
: : :
+- ^(7) FilterExecTransformer (isnotnull(rank_col#71) AND
(cast(rank_col#71 as decimal(13,7)) > (0.9 * Subquery scalar-subquery#73,
[id=#294])))
: : :
: +- Subquery scalar-subquery#73, [id=#294]
: : :
: +- CHNativeColumnarToRow
: : :
: +- ^(3) ProjectExecTransformer
[cast((avg(UnscaledValue(ss_net_profit#209))#185 / 100.0) as decimal(11,6)) AS
rank_col#72]
: : :
: +- ^(3) HashAggregateTransformer(keys=[ss_store_sk#195L],
functions=[avg(UnscaledValue(ss_net_profit#209))], isStreamingAgg=false)
: : :
: +- ^(3) InputIteratorTransformer[ss_store_sk#195L,
sum#265, count#266L]
: : :
: +- ColumnarExchange
hashpartitioning(ss_store_sk#195L, 5), ENSURE_REQUIREMENTS, [plan_id=287],
[shuffle_writer_type=hash], [OUTPUT] ArrayBuffer(ss_store_sk:LongType,
sum:DoubleType, count:LongType)
: : :
: +- ^(2)
HashAggregateTransformer(keys=[ss_store_sk#195L],
functions=[partial_avg(_pre_0#267L)], isStreamingAgg=false)
: : :
: +- ^(2) ProjectExecTransformer
[ss_store_sk#195L, ss_net_profit#209, UnscaledValue(ss_net_profit#209) AS
_pre_0#267L]
: : :
: +- ^(2) FilterExecTransformer
((isnotnull(ss_store_sk#195L) AND (ss_store_sk#195L = cast(2 as bigint))) AND
isnull(ss_hdemo_sk#193L))
: : :
: +- ^(2) NativeFileScan parquet
spark_catalog.tpcds_pq100.store_sales[ss_hdemo_sk#193L,ss_store_sk#195L,ss_net_profit#209]
Batched: true, DataFilters: [isnotnull(ss_store_sk#195L),
isnull(ss_hdemo_sk#193L)], Format: Parquet, Location: InMemoryFileIndex(1
paths)[file:/data3/liangjiabiao/docker/local_gluten/spark-3.5.1-bin-hadoop3/s...,
PartitionFilters: [], PushedFilters: [IsNotNull(ss_store_sk),
IsNull(ss_hdemo_sk)], ReadSchema:
struct<ss_hdemo_sk:bigint,ss_store_sk:bigint,ss_net_profit:decimal(7,2)>
: : :
+- ^(7) ProjectExecTransformer [ss_item_sk#91L AS item_sk#70L,
cast((avg(UnscaledValue(ss_net_profit#113))#183 / 100.0) as decimal(11,6)) AS
rank_col#71]
: : :
+- ^(7) HashAggregateTransformer(keys=[ss_item_sk#91L],
functions=[avg(UnscaledValue(ss_net_profit#113))], isStreamingAgg=false)
: : :
+- ^(7) InputIteratorTransformer[ss_item_sk#91L, sum#257,
count#258L]
: : :
+- ColumnarExchange hashpartitioning(ss_item_sk#91L, 5),
ENSURE_REQUIREMENTS, [plan_id=1199], [shuffle_writer_type=hash], [OUTPUT]
ArrayBuffer(ss_item_sk:LongType, sum:DoubleType, count:LongType)
: : :
+- ^(6) HashAggregateTransformer(keys=[ss_item_sk#91L],
functions=[partial_avg(_pre_2#277L)], isStreamingAgg=false)
: : :
+- ^(6) ProjectExecTransformer [ss_item_sk#91L,
ss_net_profit#113, UnscaledValue(ss_net_profit#113) AS _pre_2#277L]
: : :
+- ^(6) FilterExecTransformer
(isnotnull(ss_store_sk#99L) AND (ss_store_sk#99L = cast(2 as bigint)))
: : :
+- ^(6) NativeFileScan parquet
spark_catalog.tpcds_pq100.store_sales[ss_item_sk#91L,ss_store_sk#99L,ss_net_profit#113]
Batched: true, DataFilters: [isnotnull(ss_store_sk#99L)], Format: Parquet,
Location: InMemoryFileIndex(1
paths)[file:/data3/liangjiabiao/docker/local_gluten/spark-3.5.1-bin-hadoop3/s...,
PartitionFilters: [], PushedFilters: [IsNotNull(ss_store_sk)], ReadSchema:
struct<ss_item_sk:bigint,ss_store_sk:bigint,ss_net_profit:decimal(7,2)>
: : +- ^(12) SortExecTransformer [rnk#79
ASC NULLS FIRST], false, 0
: : +- ^(12) ProjectExecTransformer
[item_sk#75L, rnk#79]
: : +- ^(12) FilterExecTransformer
((rnk#79 < 11) AND isnotnull(item_sk#75L))
: : +- ^(12)
WindowExecTransformer [rank(rank_col#76) windowspecdefinition(rank_col#76 DESC
NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(),
currentrow$())) AS rnk#79], [rank_col#76 DESC NULLS LAST]
: : +- ^(12)
InputIteratorTransformer[item_sk#75L, rank_col#76]
: : +-
RowToCHNativeColumnar
: : +- WindowGroupLimit
[rank_col#76 DESC NULLS LAST], rank(rank_col#76), 10, Final
: : +-
CHNativeColumnarToRow
: : +- ^(11)
SortExecTransformer [rank_col#76 DESC NULLS LAST], false, 0
: : +- ^(11)
InputIteratorTransformer[item_sk#75L, rank_col#76]
: : +-
ColumnarExchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=1374],
[shuffle_writer_type=hash], [OUTPUT] List(item_sk:LongType,
rank_col:DecimalType(11,6))
: : +-
RowToCHNativeColumnar
: :
+- WindowGroupLimit [rank_col#76 DESC NULLS LAST], rank(rank_col#76), 10,
Partial
: :
+- CHNativeColumnarToRow
: :
+- ^(10) SortExecTransformer [rank_col#76 DESC NULLS LAST], false, 0
: :
+- ^(10) FilterExecTransformer (isnotnull(rank_col#76) AND
(cast(rank_col#76 as decimal(13,7)) > (0.9 * ReusedSubquery Subquery
scalar-subquery#73, [id=#294])))
: :
: +- ReusedSubquery Subquery scalar-subquery#73, [id=#294]
: :
+- ^(10) ProjectExecTransformer [ss_item_sk#136L AS item_sk#75L,
cast((avg(UnscaledValue(ss_net_profit#158))#184 / 100.0) as decimal(11,6)) AS
rank_col#76]
: :
+- ^(10) HashAggregateTransformer(keys=[ss_item_sk#136L],
functions=[avg(UnscaledValue(ss_net_profit#158))], isStreamingAgg=false)
: :
+- ^(10) InputIteratorTransformer[ss_item_sk#136L, sum#261,
count#262L]
: :
+- ReusedExchange [ss_item_sk#136L, sum#261, count#262L],
ColumnarExchange hashpartitioning(ss_item_sk#91L, 5), ENSURE_REQUIREMENTS,
[plan_id=1199], [shuffle_writer_type=hash], [OUTPUT]
ArrayBuffer(ss_item_sk:LongType, sum:DoubleType, count:LongType)
: +- ^(14) SortExecTransformer [i_item_sk#114L ASC
NULLS FIRST], false, 0
: +- ^(14) InputIteratorTransformer[i_item_sk#114L,
i_product_name#135]
: +- ColumnarExchange
hashpartitioning(i_item_sk#114L, 5), ENSURE_REQUIREMENTS, [plan_id=1258],
[shuffle_writer_type=hash], [OUTPUT] List(i_item_sk:LongType,
i_product_name:StringType)
: +- ^(13) FilterExecTransformer
isnotnull(i_item_sk#114L)
: +- ^(13) NativeFileScan parquet
spark_catalog.tpcds_pq100.item[i_item_sk#114L,i_product_name#135] Batched:
true, DataFilters: [isnotnull(i_item_sk#114L)], Format: Parquet, Location:
InMemoryFileIndex(1
paths)[file:/data3/liangjiabiao/docker/local_gluten/spark-3.5.1-bin-hadoop3/s...,
PartitionFilters: [], PushedFilters: [IsNotNull(i_item_sk)], ReadSchema:
struct<i_item_sk:bigint,i_product_name:string>
+- ^(16) SortExecTransformer [i_item_sk#159L ASC NULLS FIRST],
false, 0
+- ^(16) InputIteratorTransformer[i_item_sk#159L,
i_product_name#180]
+- ReusedExchange [i_item_sk#159L, i_product_name#180],
ColumnarExchange hashpartitioning(i_item_sk#114L, 5), ENSURE_REQUIREMENTS,
[plan_id=1258], [shuffle_writer_type=hash], [OUTPUT] List(i_item_sk:LongType,
i_product_name:StringType)
```
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