== Physical Plan ==
VeloxColumnarToRow (61)
+- TakeOrderedAndProjectExecTransformer (60)
   +- ^ ProjectExecTransformer (58)
      +- ^ RegularHashAggregateExecTransformer (57)
         +- ^ InputIteratorTransformer (56)
            +- ColumnarExchange (54)
               +- VeloxResizeBatches (53)
                  +- ^ ProjectExecTransformer (51)
                     +- ^ FlushableHashAggregateExecTransformer (50)
                        +- ^ ProjectExecTransformer (49)
                           +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (48)
                              :- ^ ProjectExecTransformer (41)
                              :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (40)
                              :     :- ^ ProjectExecTransformer (33)
                              :     :  +- ^ BroadcastHashJoinExecTransformer LeftSemi BuildRight (32)
                              :     :     :- ^ BroadcastHashJoinExecTransformer LeftSemi BuildRight (13)
                              :     :     :  :- ^ FilterExecTransformer (2)
                              :     :     :  :  +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer (1)
                              :     :     :  +- ^ InputIteratorTransformer (12)
                              :     :     :     +- ColumnarBroadcastExchange (10)
                              :     :     :        +- ^ ProjectExecTransformer (8)
                              :     :     :           +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (7)
                              :     :     :              :- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store_sales (3)
                              :     :     :              +- ^ InputIteratorTransformer (6)
                              :     :     :                 +- ReusedExchange (4)
                              :     :     +- ^ InputIteratorTransformer (31)
                              :     :        +- ColumnarBroadcastExchange (29)
                              :     :           +- ColumnarUnion (28)
                              :     :              :- ^ ProjectExecTransformer (19)
                              :     :              :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (18)
                              :     :              :     :- ^ FileSourceScanExecTransformer parquet spark_catalog.default.web_sales (14)
                              :     :              :     +- ^ InputIteratorTransformer (17)
                              :     :              :        +- ReusedExchange (15)
                              :     :              +- ^ ProjectExecTransformer (26)
                              :     :                 +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (25)
                              :     :                    :- ^ FileSourceScanExecTransformer parquet spark_catalog.default.catalog_sales (21)
                              :     :                    +- ^ InputIteratorTransformer (24)
                              :     :                       +- ReusedExchange (22)
                              :     +- ^ InputIteratorTransformer (39)
                              :        +- ColumnarBroadcastExchange (37)
                              :           +- ^ FilterExecTransformer (35)
                              :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_address (34)
                              +- ^ InputIteratorTransformer (47)
                                 +- ColumnarBroadcastExchange (45)
                                    +- ^ FilterExecTransformer (43)
                                       +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (42)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.customer
Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer]
PushedFilters: [IsNotNull(c_current_addr_sk), IsNotNull(c_current_cdemo_sk)]
ReadSchema: struct<c_customer_sk:int,c_current_cdemo_sk:int,c_current_addr_sk:int>

(2) FilterExecTransformer
Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Arguments: (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2))

(3) FileSourceScanExecTransformer parquet spark_catalog.default.store_sales
Output [2]: [ss_customer_sk#4, ss_sold_date_sk#5]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#5), dynamicpruningexpression(ss_sold_date_sk#5 IN dynamicpruning#6)]
ReadSchema: struct<ss_customer_sk:int>

(4) ReusedExchange [Reuses operator id: 66]
Output [1]: [d_date_sk#7]

(5) InputAdapter
Input [1]: [d_date_sk#7]

(6) InputIteratorTransformer
Input [1]: [d_date_sk#7]

(7) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_sold_date_sk#5]
Right keys [1]: [d_date_sk#7]
Join type: Inner
Join condition: None

(8) ProjectExecTransformer
Output [1]: [ss_customer_sk#4]
Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7]

(9) WholeStageCodegenTransformer (3)
Input [1]: [ss_customer_sk#4]
Arguments: false

(10) ColumnarBroadcastExchange
Input [1]: [ss_customer_sk#4]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(11) InputAdapter
Input [1]: [ss_customer_sk#4]

(12) InputIteratorTransformer
Input [1]: [ss_customer_sk#4]

(13) BroadcastHashJoinExecTransformer
Left keys [1]: [c_customer_sk#1]
Right keys [1]: [ss_customer_sk#4]
Join type: LeftSemi
Join condition: None

(14) FileSourceScanExecTransformer parquet spark_catalog.default.web_sales
Output [2]: [ws_bill_customer_sk#8, ws_sold_date_sk#9]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#9), dynamicpruningexpression(ws_sold_date_sk#9 IN dynamicpruning#6)]
ReadSchema: struct<ws_bill_customer_sk:int>

(15) ReusedExchange [Reuses operator id: 66]
Output [1]: [d_date_sk#10]

(16) InputAdapter
Input [1]: [d_date_sk#10]

(17) InputIteratorTransformer
Input [1]: [d_date_sk#10]

(18) BroadcastHashJoinExecTransformer
Left keys [1]: [ws_sold_date_sk#9]
Right keys [1]: [d_date_sk#10]
Join type: Inner
Join condition: None

(19) ProjectExecTransformer
Output [1]: [ws_bill_customer_sk#8 AS customsk#11]
Input [3]: [ws_bill_customer_sk#8, ws_sold_date_sk#9, d_date_sk#10]

(20) WholeStageCodegenTransformer (6)
Input [1]: [customsk#11]
Arguments: false

(21) FileSourceScanExecTransformer parquet spark_catalog.default.catalog_sales
Output [2]: [cs_ship_customer_sk#12, cs_sold_date_sk#13]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#13), dynamicpruningexpression(cs_sold_date_sk#13 IN dynamicpruning#6)]
ReadSchema: struct<cs_ship_customer_sk:int>

(22) ReusedExchange [Reuses operator id: 66]
Output [1]: [d_date_sk#14]

(23) InputAdapter
Input [1]: [d_date_sk#14]

(24) InputIteratorTransformer
Input [1]: [d_date_sk#14]

(25) BroadcastHashJoinExecTransformer
Left keys [1]: [cs_sold_date_sk#13]
Right keys [1]: [d_date_sk#14]
Join type: Inner
Join condition: None

(26) ProjectExecTransformer
Output [1]: [cs_ship_customer_sk#12 AS customsk#15]
Input [3]: [cs_ship_customer_sk#12, cs_sold_date_sk#13, d_date_sk#14]

(27) WholeStageCodegenTransformer (9)
Input [1]: [customsk#15]
Arguments: false

(28) ColumnarUnion
Arguments: UnknownPartitioning(0)

(29) ColumnarBroadcastExchange
Input [1]: [customsk#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(30) InputAdapter
Input [1]: [customsk#11]

(31) InputIteratorTransformer
Input [1]: [customsk#11]

(32) BroadcastHashJoinExecTransformer
Left keys [1]: [c_customer_sk#1]
Right keys [1]: [customsk#11]
Join type: LeftSemi
Join condition: None

(33) ProjectExecTransformer
Output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3]
Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]

(34) FileSourceScanExecTransformer parquet spark_catalog.default.customer_address
Output [2]: [ca_address_sk#16, ca_state#17]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_address]
PushedFilters: [IsNotNull(ca_address_sk)]
ReadSchema: struct<ca_address_sk:int,ca_state:string>

(35) FilterExecTransformer
Input [2]: [ca_address_sk#16, ca_state#17]
Arguments: isnotnull(ca_address_sk#16)

(36) WholeStageCodegenTransformer (10)
Input [2]: [ca_address_sk#16, ca_state#17]
Arguments: false

(37) ColumnarBroadcastExchange
Input [2]: [ca_address_sk#16, ca_state#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(38) InputAdapter
Input [2]: [ca_address_sk#16, ca_state#17]

(39) InputIteratorTransformer
Input [2]: [ca_address_sk#16, ca_state#17]

(40) BroadcastHashJoinExecTransformer
Left keys [1]: [c_current_addr_sk#3]
Right keys [1]: [ca_address_sk#16]
Join type: Inner
Join condition: None

(41) ProjectExecTransformer
Output [2]: [c_current_cdemo_sk#2, ca_state#17]
Input [4]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#16, ca_state#17]

(42) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_gender:string,cd_marital_status:string,cd_dep_count:int,cd_dep_employed_count:int,cd_dep_college_count:int>

(43) FilterExecTransformer
Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Arguments: isnotnull(cd_demo_sk#18)

(44) WholeStageCodegenTransformer (11)
Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Arguments: false

(45) ColumnarBroadcastExchange
Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4]

(46) InputAdapter
Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]

(47) InputIteratorTransformer
Input [6]: [cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]

(48) BroadcastHashJoinExecTransformer
Left keys [1]: [c_current_cdemo_sk#2]
Right keys [1]: [cd_demo_sk#18]
Join type: Inner
Join condition: None

(49) ProjectExecTransformer
Output [6]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Input [8]: [c_current_cdemo_sk#2, ca_state#17, cd_demo_sk#18, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]

(50) FlushableHashAggregateExecTransformer
Input [6]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Keys [6]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Functions [10]: [partial_count(1), partial_avg(cd_dep_count#21), partial_max(cd_dep_count#21), partial_sum(cd_dep_count#21), partial_avg(cd_dep_employed_count#22), partial_max(cd_dep_employed_count#22), partial_sum(cd_dep_employed_count#22), partial_avg(cd_dep_college_count#23), partial_max(cd_dep_college_count#23), partial_sum(cd_dep_college_count#23)]
Aggregate Attributes [13]: [count#24, sum#25, count#26, max#27, sum#28, sum#29, count#30, max#31, sum#32, sum#33, count#34, max#35, sum#36]
Results [19]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]

(51) ProjectExecTransformer
Output [20]: [hash(ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, 42) AS hash_partition_key#50, ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]
Input [19]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]

(52) WholeStageCodegenTransformer (12)
Input [20]: [hash_partition_key#50, ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]
Arguments: false

(53) VeloxResizeBatches
Input [20]: [hash_partition_key#50, ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]
Arguments: 1024, 2147483647, 10485760

(54) ColumnarExchange
Input [20]: [hash_partition_key#50, ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]
Arguments: hashpartitioning(ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, 1), ENSURE_REQUIREMENTS, [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49], [plan_id=5], [shuffle_writer_type=hash]

(55) InputAdapter
Input [19]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]

(56) InputIteratorTransformer
Input [19]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]

(57) RegularHashAggregateExecTransformer
Input [19]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count#37, sum#38, count#39, max#40, sum#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49]
Keys [6]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23]
Functions [10]: [count(1), avg(cd_dep_count#21), max(cd_dep_count#21), sum(cd_dep_count#21), avg(cd_dep_employed_count#22), max(cd_dep_employed_count#22), sum(cd_dep_employed_count#22), avg(cd_dep_college_count#23), max(cd_dep_college_count#23), sum(cd_dep_college_count#23)]
Aggregate Attributes [10]: [count(1)#51, avg(cd_dep_count#21)#52, max(cd_dep_count#21)#53, sum(cd_dep_count#21)#54, avg(cd_dep_employed_count#22)#55, max(cd_dep_employed_count#22)#56, sum(cd_dep_employed_count#22)#57, avg(cd_dep_college_count#23)#58, max(cd_dep_college_count#23)#59, sum(cd_dep_college_count#23)#60]
Results [16]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count(1)#51, avg(cd_dep_count#21)#52, max(cd_dep_count#21)#53, sum(cd_dep_count#21)#54, avg(cd_dep_employed_count#22)#55, max(cd_dep_employed_count#22)#56, sum(cd_dep_employed_count#22)#57, avg(cd_dep_college_count#23)#58, max(cd_dep_college_count#23)#59, sum(cd_dep_college_count#23)#60]

(58) ProjectExecTransformer
Output [18]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, count(1)#51 AS cnt1#61, avg(cd_dep_count#21)#52 AS avg(cd_dep_count)#62, max(cd_dep_count#21)#53 AS max(cd_dep_count)#63, sum(cd_dep_count#21)#54 AS sum(cd_dep_count)#64, cd_dep_employed_count#22, count(1)#51 AS cnt2#65, avg(cd_dep_employed_count#22)#55 AS avg(cd_dep_employed_count)#66, max(cd_dep_employed_count#22)#56 AS max(cd_dep_employed_count)#67, sum(cd_dep_employed_count#22)#57 AS sum(cd_dep_employed_count)#68, cd_dep_college_count#23, count(1)#51 AS cnt3#69, avg(cd_dep_college_count#23)#58 AS avg(cd_dep_college_count)#70, max(cd_dep_college_count#23)#59 AS max(cd_dep_college_count)#71, sum(cd_dep_college_count#23)#60 AS sum(cd_dep_college_count)#72]
Input [16]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cd_dep_employed_count#22, cd_dep_college_count#23, count(1)#51, avg(cd_dep_count#21)#52, max(cd_dep_count#21)#53, sum(cd_dep_count#21)#54, avg(cd_dep_employed_count#22)#55, max(cd_dep_employed_count#22)#56, sum(cd_dep_employed_count#22)#57, avg(cd_dep_college_count#23)#58, max(cd_dep_college_count#23)#59, sum(cd_dep_college_count#23)#60]

(59) WholeStageCodegenTransformer (13)
Input [18]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cnt1#61, avg(cd_dep_count)#62, max(cd_dep_count)#63, sum(cd_dep_count)#64, cd_dep_employed_count#22, cnt2#65, avg(cd_dep_employed_count)#66, max(cd_dep_employed_count)#67, sum(cd_dep_employed_count)#68, cd_dep_college_count#23, cnt3#69, avg(cd_dep_college_count)#70, max(cd_dep_college_count)#71, sum(cd_dep_college_count)#72]
Arguments: false

(60) TakeOrderedAndProjectExecTransformer
Input [18]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cnt1#61, avg(cd_dep_count)#62, max(cd_dep_count)#63, sum(cd_dep_count)#64, cd_dep_employed_count#22, cnt2#65, avg(cd_dep_employed_count)#66, max(cd_dep_employed_count)#67, sum(cd_dep_employed_count)#68, cd_dep_college_count#23, cnt3#69, avg(cd_dep_college_count)#70, max(cd_dep_college_count)#71, sum(cd_dep_college_count)#72]
Arguments: 100, [ca_state#17 ASC NULLS FIRST, cd_gender#19 ASC NULLS FIRST, cd_marital_status#20 ASC NULLS FIRST, cd_dep_count#21 ASC NULLS FIRST, cd_dep_employed_count#22 ASC NULLS FIRST, cd_dep_college_count#23 ASC NULLS FIRST], [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cnt1#61, avg(cd_dep_count)#62, max(cd_dep_count)#63, sum(cd_dep_count)#64, cd_dep_employed_count#22, cnt2#65, avg(cd_dep_employed_count)#66, max(cd_dep_employed_count)#67, sum(cd_dep_employed_count)#68, cd_dep_college_count#23, cnt3#69, avg(cd_dep_college_count)#70, max(cd_dep_college_count)#71, sum(cd_dep_college_count)#72], 0

(61) VeloxColumnarToRow
Input [18]: [ca_state#17, cd_gender#19, cd_marital_status#20, cd_dep_count#21, cnt1#61, avg(cd_dep_count)#62, max(cd_dep_count)#63, sum(cd_dep_count)#64, cd_dep_employed_count#22, cnt2#65, avg(cd_dep_employed_count)#66, max(cd_dep_employed_count)#67, sum(cd_dep_employed_count)#68, cd_dep_college_count#23, cnt3#69, avg(cd_dep_college_count)#70, max(cd_dep_college_count)#71, sum(cd_dep_college_count)#72]

===== Subqueries =====

Subquery:1 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
ColumnarBroadcastExchange (66)
+- ^ ProjectExecTransformer (64)
   +- ^ FilterExecTransformer (63)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (62)


(62) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#7, d_year#73, d_qoy#74]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,1999), LessThan(d_qoy,4), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_qoy:int>

(63) FilterExecTransformer
Input [3]: [d_date_sk#7, d_year#73, d_qoy#74]
Arguments: ((((isnotnull(d_year#73) AND isnotnull(d_qoy#74)) AND (d_year#73 = 1999)) AND (d_qoy#74 < 4)) AND isnotnull(d_date_sk#7))

(64) ProjectExecTransformer
Output [1]: [d_date_sk#7]
Input [3]: [d_date_sk#7, d_year#73, d_qoy#74]

(65) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#7]
Arguments: false

(66) ColumnarBroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]

Subquery:2 Hosting operator id = 14 Hosting Expression = ws_sold_date_sk#9 IN dynamicpruning#6

Subquery:3 Hosting operator id = 21 Hosting Expression = cs_sold_date_sk#13 IN dynamicpruning#6


