== Physical Plan ==
TakeOrderedAndProject (40)
+- * HashAggregate (39)
   +- * ColumnarToRow (38)
      +- CometColumnarExchange (37)
         +- RowToColumnar (36)
            +- * HashAggregate (35)
               +- * ColumnarToRow (34)
                  +- CometProject (33)
                     +- CometBroadcastHashJoin (32)
                        :- CometProject (28)
                        :  +- CometBroadcastHashJoin (27)
                        :     :- CometProject (23)
                        :     :  +- CometBroadcastHashJoin (22)
                        :     :     :- CometBroadcastHashJoin (11)
                        :     :     :  :- CometFilter (2)
                        :     :     :  :  +- CometScan parquet spark_catalog.default.customer (1)
                        :     :     :  +- CometBroadcastExchange (10)
                        :     :     :     +- CometProject (9)
                        :     :     :        +- CometBroadcastHashJoin (8)
                        :     :     :           :- CometScan parquet spark_catalog.default.store_sales (3)
                        :     :     :           +- CometBroadcastExchange (7)
                        :     :     :              +- CometProject (6)
                        :     :     :                 +- CometFilter (5)
                        :     :     :                    +- CometScan parquet spark_catalog.default.date_dim (4)
                        :     :     +- CometBroadcastExchange (21)
                        :     :        +- CometUnion (20)
                        :     :           :- CometProject (15)
                        :     :           :  +- CometBroadcastHashJoin (14)
                        :     :           :     :- CometScan parquet spark_catalog.default.web_sales (12)
                        :     :           :     +- ReusedExchange (13)
                        :     :           +- CometProject (19)
                        :     :              +- CometBroadcastHashJoin (18)
                        :     :                 :- CometScan parquet spark_catalog.default.catalog_sales (16)
                        :     :                 +- ReusedExchange (17)
                        :     +- CometBroadcastExchange (26)
                        :        +- CometFilter (25)
                        :           +- CometScan parquet spark_catalog.default.customer_address (24)
                        +- CometBroadcastExchange (31)
                           +- CometFilter (30)
                              +- CometScan parquet spark_catalog.default.customer_demographics (29)


(1) Scan parquet spark_catalog.default.customer
Output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Batched: true
Location [not included in comparison]/{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) CometFilter
Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Condition : (isnotnull(c_current_addr_sk#3) AND isnotnull(c_current_cdemo_sk#2))

(3) Scan 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) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#7, d_year#8, d_qoy#9]
Batched: true
Location [not included in comparison]/{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>

(5) CometFilter
Input [3]: [d_date_sk#7, d_year#8, d_qoy#9]
Condition : ((((isnotnull(d_year#8) AND isnotnull(d_qoy#9)) AND (d_year#8 = 1999)) AND (d_qoy#9 < 4)) AND isnotnull(d_date_sk#7))

(6) CometProject
Input [3]: [d_date_sk#7, d_year#8, d_qoy#9]
Arguments: [d_date_sk#7], [d_date_sk#7]

(7) CometBroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: [d_date_sk#7]

(8) CometBroadcastHashJoin
Left output [2]: [ss_customer_sk#4, ss_sold_date_sk#5]
Right output [1]: [d_date_sk#7]
Arguments: [ss_sold_date_sk#5], [d_date_sk#7], Inner, BuildRight

(9) CometProject
Input [3]: [ss_customer_sk#4, ss_sold_date_sk#5, d_date_sk#7]
Arguments: [ss_customer_sk#4], [ss_customer_sk#4]

(10) CometBroadcastExchange
Input [1]: [ss_customer_sk#4]
Arguments: [ss_customer_sk#4]

(11) CometBroadcastHashJoin
Left output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Right output [1]: [ss_customer_sk#4]
Arguments: [c_customer_sk#1], [ss_customer_sk#4], LeftSemi, BuildRight

(12) Scan parquet spark_catalog.default.web_sales
Output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#11), dynamicpruningexpression(ws_sold_date_sk#11 IN dynamicpruning#12)]
ReadSchema: struct<ws_bill_customer_sk:int>

(13) ReusedExchange [Reuses operator id: 7]
Output [1]: [d_date_sk#13]

(14) CometBroadcastHashJoin
Left output [2]: [ws_bill_customer_sk#10, ws_sold_date_sk#11]
Right output [1]: [d_date_sk#13]
Arguments: [ws_sold_date_sk#11], [d_date_sk#13], Inner, BuildRight

(15) CometProject
Input [3]: [ws_bill_customer_sk#10, ws_sold_date_sk#11, d_date_sk#13]
Arguments: [customsk#14], [ws_bill_customer_sk#10 AS customsk#14]

(16) Scan parquet spark_catalog.default.catalog_sales
Output [2]: [cs_ship_customer_sk#15, cs_sold_date_sk#16]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#16), dynamicpruningexpression(cs_sold_date_sk#16 IN dynamicpruning#17)]
ReadSchema: struct<cs_ship_customer_sk:int>

(17) ReusedExchange [Reuses operator id: 7]
Output [1]: [d_date_sk#18]

(18) CometBroadcastHashJoin
Left output [2]: [cs_ship_customer_sk#15, cs_sold_date_sk#16]
Right output [1]: [d_date_sk#18]
Arguments: [cs_sold_date_sk#16], [d_date_sk#18], Inner, BuildRight

(19) CometProject
Input [3]: [cs_ship_customer_sk#15, cs_sold_date_sk#16, d_date_sk#18]
Arguments: [customsk#19], [cs_ship_customer_sk#15 AS customsk#19]

(20) CometUnion
Child 0 Input [1]: [customsk#14]
Child 1 Input [1]: [customsk#19]

(21) CometBroadcastExchange
Input [1]: [customsk#14]
Arguments: [customsk#14]

(22) CometBroadcastHashJoin
Left output [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Right output [1]: [customsk#14]
Arguments: [c_customer_sk#1], [customsk#14], LeftSemi, BuildRight

(23) CometProject
Input [3]: [c_customer_sk#1, c_current_cdemo_sk#2, c_current_addr_sk#3]
Arguments: [c_current_cdemo_sk#2, c_current_addr_sk#3], [c_current_cdemo_sk#2, c_current_addr_sk#3]

(24) Scan parquet spark_catalog.default.customer_address
Output [2]: [ca_address_sk#20, ca_state#21]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer_address]
PushedFilters: [IsNotNull(ca_address_sk)]
ReadSchema: struct<ca_address_sk:int,ca_state:string>

(25) CometFilter
Input [2]: [ca_address_sk#20, ca_state#21]
Condition : isnotnull(ca_address_sk#20)

(26) CometBroadcastExchange
Input [2]: [ca_address_sk#20, ca_state#21]
Arguments: [ca_address_sk#20, ca_state#21]

(27) CometBroadcastHashJoin
Left output [2]: [c_current_cdemo_sk#2, c_current_addr_sk#3]
Right output [2]: [ca_address_sk#20, ca_state#21]
Arguments: [c_current_addr_sk#3], [ca_address_sk#20], Inner, BuildRight

(28) CometProject
Input [4]: [c_current_cdemo_sk#2, c_current_addr_sk#3, ca_address_sk#20, ca_state#21]
Arguments: [c_current_cdemo_sk#2, ca_state#21], [c_current_cdemo_sk#2, ca_state#21]

(29) Scan parquet spark_catalog.default.customer_demographics
Output [6]: [cd_demo_sk#22, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Batched: true
Location [not included in comparison]/{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>

(30) CometFilter
Input [6]: [cd_demo_sk#22, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Condition : isnotnull(cd_demo_sk#22)

(31) CometBroadcastExchange
Input [6]: [cd_demo_sk#22, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Arguments: [cd_demo_sk#22, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]

(32) CometBroadcastHashJoin
Left output [2]: [c_current_cdemo_sk#2, ca_state#21]
Right output [6]: [cd_demo_sk#22, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Arguments: [c_current_cdemo_sk#2], [cd_demo_sk#22], Inner, BuildRight

(33) CometProject
Input [8]: [c_current_cdemo_sk#2, ca_state#21, cd_demo_sk#22, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Arguments: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27], [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]

(34) ColumnarToRow [codegen id : 1]
Input [6]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]

(35) HashAggregate [codegen id : 1]
Input [6]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Keys [6]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Functions [10]: [partial_count(1), partial_avg(cd_dep_count#25), partial_max(cd_dep_count#25), partial_sum(cd_dep_count#25), partial_avg(cd_dep_employed_count#26), partial_max(cd_dep_employed_count#26), partial_sum(cd_dep_employed_count#26), partial_avg(cd_dep_college_count#27), partial_max(cd_dep_college_count#27), partial_sum(cd_dep_college_count#27)]
Aggregate Attributes [13]: [count#28, sum#29, count#30, max#31, sum#32, sum#33, count#34, max#35, sum#36, sum#37, count#38, max#39, sum#40]
Results [19]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27, count#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49, sum#50, count#51, max#52, sum#53]

(36) RowToColumnar
Input [19]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27, count#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49, sum#50, count#51, max#52, sum#53]

(37) CometColumnarExchange
Input [19]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27, count#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49, sum#50, count#51, max#52, sum#53]
Arguments: hashpartitioning(ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(38) ColumnarToRow [codegen id : 2]
Input [19]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27, count#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49, sum#50, count#51, max#52, sum#53]

(39) HashAggregate [codegen id : 2]
Input [19]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27, count#41, sum#42, count#43, max#44, sum#45, sum#46, count#47, max#48, sum#49, sum#50, count#51, max#52, sum#53]
Keys [6]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cd_dep_employed_count#26, cd_dep_college_count#27]
Functions [10]: [count(1), avg(cd_dep_count#25), max(cd_dep_count#25), sum(cd_dep_count#25), avg(cd_dep_employed_count#26), max(cd_dep_employed_count#26), sum(cd_dep_employed_count#26), avg(cd_dep_college_count#27), max(cd_dep_college_count#27), sum(cd_dep_college_count#27)]
Aggregate Attributes [10]: [count(1)#54, avg(cd_dep_count#25)#55, max(cd_dep_count#25)#56, sum(cd_dep_count#25)#57, avg(cd_dep_employed_count#26)#58, max(cd_dep_employed_count#26)#59, sum(cd_dep_employed_count#26)#60, avg(cd_dep_college_count#27)#61, max(cd_dep_college_count#27)#62, sum(cd_dep_college_count#27)#63]
Results [18]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, count(1)#54 AS cnt1#64, avg(cd_dep_count#25)#55 AS avg(cd_dep_count)#65, max(cd_dep_count#25)#56 AS max(cd_dep_count)#66, sum(cd_dep_count#25)#57 AS sum(cd_dep_count)#67, cd_dep_employed_count#26, count(1)#54 AS cnt2#68, avg(cd_dep_employed_count#26)#58 AS avg(cd_dep_employed_count)#69, max(cd_dep_employed_count#26)#59 AS max(cd_dep_employed_count)#70, sum(cd_dep_employed_count#26)#60 AS sum(cd_dep_employed_count)#71, cd_dep_college_count#27, count(1)#54 AS cnt3#72, avg(cd_dep_college_count#27)#61 AS avg(cd_dep_college_count)#73, max(cd_dep_college_count#27)#62 AS max(cd_dep_college_count)#74, sum(cd_dep_college_count#27)#63 AS sum(cd_dep_college_count)#75]

(40) TakeOrderedAndProject
Input [18]: [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cnt1#64, avg(cd_dep_count)#65, max(cd_dep_count)#66, sum(cd_dep_count)#67, cd_dep_employed_count#26, cnt2#68, avg(cd_dep_employed_count)#69, max(cd_dep_employed_count)#70, sum(cd_dep_employed_count)#71, cd_dep_college_count#27, cnt3#72, avg(cd_dep_college_count)#73, max(cd_dep_college_count)#74, sum(cd_dep_college_count)#75]
Arguments: 100, [ca_state#21 ASC NULLS FIRST, cd_gender#23 ASC NULLS FIRST, cd_marital_status#24 ASC NULLS FIRST, cd_dep_count#25 ASC NULLS FIRST, cd_dep_employed_count#26 ASC NULLS FIRST, cd_dep_college_count#27 ASC NULLS FIRST], [ca_state#21, cd_gender#23, cd_marital_status#24, cd_dep_count#25, cnt1#64, avg(cd_dep_count)#65, max(cd_dep_count)#66, sum(cd_dep_count)#67, cd_dep_employed_count#26, cnt2#68, avg(cd_dep_employed_count)#69, max(cd_dep_employed_count)#70, sum(cd_dep_employed_count)#71, cd_dep_college_count#27, cnt3#72, avg(cd_dep_college_count)#73, max(cd_dep_college_count)#74, sum(cd_dep_college_count)#75]

===== Subqueries =====

Subquery:1 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
BroadcastExchange (45)
+- * ColumnarToRow (44)
   +- CometProject (43)
      +- CometFilter (42)
         +- CometScan parquet spark_catalog.default.date_dim (41)


(41) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#7, d_year#8, d_qoy#9]
Batched: true
Location [not included in comparison]/{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>

(42) CometFilter
Input [3]: [d_date_sk#7, d_year#8, d_qoy#9]
Condition : ((((isnotnull(d_year#8) AND isnotnull(d_qoy#9)) AND (d_year#8 = 1999)) AND (d_qoy#9 < 4)) AND isnotnull(d_date_sk#7))

(43) CometProject
Input [3]: [d_date_sk#7, d_year#8, d_qoy#9]
Arguments: [d_date_sk#7], [d_date_sk#7]

(44) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#7]

(45) BroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

Subquery:2 Hosting operator id = 12 Hosting Expression = ws_sold_date_sk#11 IN dynamicpruning#6

Subquery:3 Hosting operator id = 16 Hosting Expression = cs_sold_date_sk#16 IN dynamicpruning#6


