== Physical Plan ==
TakeOrderedAndProject (47)
+- * HashAggregate (46)
   +- * CometColumnarToRow (45)
      +- CometColumnarExchange (44)
         +- * HashAggregate (43)
            +- * Project (42)
               +- * BroadcastHashJoin Inner BuildRight (41)
                  :- * Project (35)
                  :  +- * BroadcastHashJoin Inner BuildRight (34)
                  :     :- * Project (28)
                  :     :  +- * Filter (27)
                  :     :     +- * BroadcastHashJoin ExistenceJoin(exists#1) BuildRight (26)
                  :     :        :- * BroadcastHashJoin ExistenceJoin(exists#2) BuildRight (19)
                  :     :        :  :- * CometColumnarToRow (12)
                  :     :        :  :  +- CometBroadcastHashJoin (11)
                  :     :        :  :     :- CometFilter (2)
                  :     :        :  :     :  +- CometScan [native_iceberg_compat] parquet spark_catalog.default.customer (1)
                  :     :        :  :     +- CometBroadcastExchange (10)
                  :     :        :  :        +- CometProject (9)
                  :     :        :  :           +- CometBroadcastHashJoin (8)
                  :     :        :  :              :- CometScan [native_iceberg_compat] parquet spark_catalog.default.store_sales (3)
                  :     :        :  :              +- CometBroadcastExchange (7)
                  :     :        :  :                 +- CometProject (6)
                  :     :        :  :                    +- CometFilter (5)
                  :     :        :  :                       +- CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim (4)
                  :     :        :  +- BroadcastExchange (18)
                  :     :        :     +- * CometColumnarToRow (17)
                  :     :        :        +- CometProject (16)
                  :     :        :           +- CometBroadcastHashJoin (15)
                  :     :        :              :- CometScan [native_iceberg_compat] parquet spark_catalog.default.web_sales (13)
                  :     :        :              +- ReusedExchange (14)
                  :     :        +- BroadcastExchange (25)
                  :     :           +- * CometColumnarToRow (24)
                  :     :              +- CometProject (23)
                  :     :                 +- CometBroadcastHashJoin (22)
                  :     :                    :- CometScan [native_iceberg_compat] parquet spark_catalog.default.catalog_sales (20)
                  :     :                    +- ReusedExchange (21)
                  :     +- BroadcastExchange (33)
                  :        +- * CometColumnarToRow (32)
                  :           +- CometProject (31)
                  :              +- CometFilter (30)
                  :                 +- CometScan [native_iceberg_compat] parquet spark_catalog.default.customer_address (29)
                  +- BroadcastExchange (40)
                     +- * CometColumnarToRow (39)
                        +- CometProject (38)
                           +- CometFilter (37)
                              +- CometScan [native_iceberg_compat] parquet spark_catalog.default.customer_demographics (36)


(1) CometScan [native_iceberg_compat] parquet spark_catalog.default.customer
Output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5]
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#3, c_current_cdemo_sk#4, c_current_addr_sk#5]
Condition : (isnotnull(c_current_addr_sk#5) AND isnotnull(c_current_cdemo_sk#4))

(3) CometScan [native_iceberg_compat] parquet spark_catalog.default.store_sales
Output [2]: [ss_customer_sk#6, ss_sold_date_sk#7]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#7), dynamicpruningexpression(ss_sold_date_sk#7 IN dynamicpruning#8)]
ReadSchema: struct<ss_customer_sk:int>

(4) CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#9, d_year#10, d_qoy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), 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#9, d_year#10, d_qoy#11]
Condition : ((((isnotnull(d_year#10) AND isnotnull(d_qoy#11)) AND (d_year#10 = 2002)) AND (d_qoy#11 < 4)) AND isnotnull(d_date_sk#9))

(6) CometProject
Input [3]: [d_date_sk#9, d_year#10, d_qoy#11]
Arguments: [d_date_sk#9], [d_date_sk#9]

(7) CometBroadcastExchange
Input [1]: [d_date_sk#9]
Arguments: [d_date_sk#9]

(8) CometBroadcastHashJoin
Left output [2]: [ss_customer_sk#6, ss_sold_date_sk#7]
Right output [1]: [d_date_sk#9]
Arguments: [ss_sold_date_sk#7], [d_date_sk#9], Inner, BuildRight

(9) CometProject
Input [3]: [ss_customer_sk#6, ss_sold_date_sk#7, d_date_sk#9]
Arguments: [ss_customer_sk#6], [ss_customer_sk#6]

(10) CometBroadcastExchange
Input [1]: [ss_customer_sk#6]
Arguments: [ss_customer_sk#6]

(11) CometBroadcastHashJoin
Left output [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5]
Right output [1]: [ss_customer_sk#6]
Arguments: [c_customer_sk#3], [ss_customer_sk#6], LeftSemi, BuildRight

(12) CometColumnarToRow [codegen id : 5]
Input [3]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5]

(13) CometScan [native_iceberg_compat] parquet spark_catalog.default.web_sales
Output [2]: [ws_bill_customer_sk#12, ws_sold_date_sk#13]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#13), dynamicpruningexpression(ws_sold_date_sk#13 IN dynamicpruning#14)]
ReadSchema: struct<ws_bill_customer_sk:int>

(14) ReusedExchange [Reuses operator id: 7]
Output [1]: [d_date_sk#9]

(15) CometBroadcastHashJoin
Left output [2]: [ws_bill_customer_sk#12, ws_sold_date_sk#13]
Right output [1]: [d_date_sk#9]
Arguments: [ws_sold_date_sk#13], [d_date_sk#9], Inner, BuildRight

(16) CometProject
Input [3]: [ws_bill_customer_sk#12, ws_sold_date_sk#13, d_date_sk#9]
Arguments: [ws_bill_customer_sk#12], [ws_bill_customer_sk#12]

(17) CometColumnarToRow [codegen id : 1]
Input [1]: [ws_bill_customer_sk#12]

(18) BroadcastExchange
Input [1]: [ws_bill_customer_sk#12]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(19) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [c_customer_sk#3]
Right keys [1]: [ws_bill_customer_sk#12]
Join type: ExistenceJoin(exists#2)
Join condition: None

(20) CometScan [native_iceberg_compat] 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>

(21) ReusedExchange [Reuses operator id: 7]
Output [1]: [d_date_sk#9]

(22) CometBroadcastHashJoin
Left output [2]: [cs_ship_customer_sk#15, cs_sold_date_sk#16]
Right output [1]: [d_date_sk#9]
Arguments: [cs_sold_date_sk#16], [d_date_sk#9], Inner, BuildRight

(23) CometProject
Input [3]: [cs_ship_customer_sk#15, cs_sold_date_sk#16, d_date_sk#9]
Arguments: [cs_ship_customer_sk#15], [cs_ship_customer_sk#15]

(24) CometColumnarToRow [codegen id : 2]
Input [1]: [cs_ship_customer_sk#15]

(25) BroadcastExchange
Input [1]: [cs_ship_customer_sk#15]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(26) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [c_customer_sk#3]
Right keys [1]: [cs_ship_customer_sk#15]
Join type: ExistenceJoin(exists#1)
Join condition: None

(27) Filter [codegen id : 5]
Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1]
Condition : (exists#2 OR exists#1)

(28) Project [codegen id : 5]
Output [2]: [c_current_cdemo_sk#4, c_current_addr_sk#5]
Input [5]: [c_customer_sk#3, c_current_cdemo_sk#4, c_current_addr_sk#5, exists#2, exists#1]

(29) CometScan [native_iceberg_compat] parquet spark_catalog.default.customer_address
Output [2]: [ca_address_sk#18, ca_state#19]
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>

(30) CometFilter
Input [2]: [ca_address_sk#18, ca_state#19]
Condition : isnotnull(ca_address_sk#18)

(31) CometProject
Input [2]: [ca_address_sk#18, ca_state#19]
Arguments: [ca_address_sk#18, ca_state#20], [ca_address_sk#18, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, ca_state#19, 2, true, false, true) AS ca_state#20]

(32) CometColumnarToRow [codegen id : 3]
Input [2]: [ca_address_sk#18, ca_state#20]

(33) BroadcastExchange
Input [2]: [ca_address_sk#18, ca_state#20]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(34) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [c_current_addr_sk#5]
Right keys [1]: [ca_address_sk#18]
Join type: Inner
Join condition: None

(35) Project [codegen id : 5]
Output [2]: [c_current_cdemo_sk#4, ca_state#20]
Input [4]: [c_current_cdemo_sk#4, c_current_addr_sk#5, ca_address_sk#18, ca_state#20]

(36) CometScan [native_iceberg_compat] parquet spark_catalog.default.customer_demographics
Output [6]: [cd_demo_sk#21, cd_gender#22, cd_marital_status#23, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
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>

(37) CometFilter
Input [6]: [cd_demo_sk#21, cd_gender#22, cd_marital_status#23, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Condition : isnotnull(cd_demo_sk#21)

(38) CometProject
Input [6]: [cd_demo_sk#21, cd_gender#22, cd_marital_status#23, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Arguments: [cd_demo_sk#21, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26], [cd_demo_sk#21, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_gender#22, 1, true, false, true) AS cd_gender#27, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_marital_status#23, 1, true, false, true) AS cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]

(39) CometColumnarToRow [codegen id : 4]
Input [6]: [cd_demo_sk#21, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]

(40) BroadcastExchange
Input [6]: [cd_demo_sk#21, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]

(41) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [c_current_cdemo_sk#4]
Right keys [1]: [cd_demo_sk#21]
Join type: Inner
Join condition: None

(42) Project [codegen id : 5]
Output [6]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Input [8]: [c_current_cdemo_sk#4, ca_state#20, cd_demo_sk#21, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]

(43) HashAggregate [codegen id : 5]
Input [6]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Keys [6]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Functions [10]: [partial_count(1), partial_avg(cd_dep_count#24), partial_max(cd_dep_count#24), partial_sum(cd_dep_count#24), partial_avg(cd_dep_employed_count#25), partial_max(cd_dep_employed_count#25), partial_sum(cd_dep_employed_count#25), partial_avg(cd_dep_college_count#26), partial_max(cd_dep_college_count#26), partial_sum(cd_dep_college_count#26)]
Aggregate Attributes [13]: [count#29, sum#30, count#31, max#32, sum#33, sum#34, count#35, max#36, sum#37, sum#38, count#39, max#40, sum#41]
Results [19]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26, count#42, sum#43, count#44, max#45, sum#46, sum#47, count#48, max#49, sum#50, sum#51, count#52, max#53, sum#54]

(44) CometColumnarExchange
Input [19]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26, count#42, sum#43, count#44, max#45, sum#46, sum#47, count#48, max#49, sum#50, sum#51, count#52, max#53, sum#54]
Arguments: hashpartitioning(ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(45) CometColumnarToRow [codegen id : 6]
Input [19]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26, count#42, sum#43, count#44, max#45, sum#46, sum#47, count#48, max#49, sum#50, sum#51, count#52, max#53, sum#54]

(46) HashAggregate [codegen id : 6]
Input [19]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26, count#42, sum#43, count#44, max#45, sum#46, sum#47, count#48, max#49, sum#50, sum#51, count#52, max#53, sum#54]
Keys [6]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cd_dep_employed_count#25, cd_dep_college_count#26]
Functions [10]: [count(1), avg(cd_dep_count#24), max(cd_dep_count#24), sum(cd_dep_count#24), avg(cd_dep_employed_count#25), max(cd_dep_employed_count#25), sum(cd_dep_employed_count#25), avg(cd_dep_college_count#26), max(cd_dep_college_count#26), sum(cd_dep_college_count#26)]
Aggregate Attributes [10]: [count(1)#55, avg(cd_dep_count#24)#56, max(cd_dep_count#24)#57, sum(cd_dep_count#24)#58, avg(cd_dep_employed_count#25)#59, max(cd_dep_employed_count#25)#60, sum(cd_dep_employed_count#25)#61, avg(cd_dep_college_count#26)#62, max(cd_dep_college_count#26)#63, sum(cd_dep_college_count#26)#64]
Results [18]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, count(1)#55 AS cnt1#65, avg(cd_dep_count#24)#56 AS avg(cd_dep_count)#66, max(cd_dep_count#24)#57 AS max(cd_dep_count)#67, sum(cd_dep_count#24)#58 AS sum(cd_dep_count)#68, cd_dep_employed_count#25, count(1)#55 AS cnt2#69, avg(cd_dep_employed_count#25)#59 AS avg(cd_dep_employed_count)#70, max(cd_dep_employed_count#25)#60 AS max(cd_dep_employed_count)#71, sum(cd_dep_employed_count#25)#61 AS sum(cd_dep_employed_count)#72, cd_dep_college_count#26, count(1)#55 AS cnt3#73, avg(cd_dep_college_count#26)#62 AS avg(cd_dep_college_count)#74, max(cd_dep_college_count#26)#63 AS max(cd_dep_college_count)#75, sum(cd_dep_college_count#26)#64 AS sum(cd_dep_college_count)#76]

(47) TakeOrderedAndProject
Input [18]: [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cnt1#65, avg(cd_dep_count)#66, max(cd_dep_count)#67, sum(cd_dep_count)#68, cd_dep_employed_count#25, cnt2#69, avg(cd_dep_employed_count)#70, max(cd_dep_employed_count)#71, sum(cd_dep_employed_count)#72, cd_dep_college_count#26, cnt3#73, avg(cd_dep_college_count)#74, max(cd_dep_college_count)#75, sum(cd_dep_college_count)#76]
Arguments: 100, [ca_state#20 ASC NULLS FIRST, cd_gender#27 ASC NULLS FIRST, cd_marital_status#28 ASC NULLS FIRST, cd_dep_count#24 ASC NULLS FIRST, cd_dep_employed_count#25 ASC NULLS FIRST, cd_dep_college_count#26 ASC NULLS FIRST], [ca_state#20, cd_gender#27, cd_marital_status#28, cd_dep_count#24, cnt1#65, avg(cd_dep_count)#66, max(cd_dep_count)#67, sum(cd_dep_count)#68, cd_dep_employed_count#25, cnt2#69, avg(cd_dep_employed_count)#70, max(cd_dep_employed_count)#71, sum(cd_dep_employed_count)#72, cd_dep_college_count#26, cnt3#73, avg(cd_dep_college_count)#74, max(cd_dep_college_count)#75, sum(cd_dep_college_count)#76]

===== Subqueries =====

Subquery:1 Hosting operator id = 3 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8
BroadcastExchange (52)
+- * CometColumnarToRow (51)
   +- CometProject (50)
      +- CometFilter (49)
         +- CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim (48)


(48) CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#9, d_year#10, d_qoy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_qoy), EqualTo(d_year,2002), LessThan(d_qoy,4), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_qoy:int>

(49) CometFilter
Input [3]: [d_date_sk#9, d_year#10, d_qoy#11]
Condition : ((((isnotnull(d_year#10) AND isnotnull(d_qoy#11)) AND (d_year#10 = 2002)) AND (d_qoy#11 < 4)) AND isnotnull(d_date_sk#9))

(50) CometProject
Input [3]: [d_date_sk#9, d_year#10, d_qoy#11]
Arguments: [d_date_sk#9], [d_date_sk#9]

(51) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#9]

(52) BroadcastExchange
Input [1]: [d_date_sk#9]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]

Subquery:2 Hosting operator id = 13 Hosting Expression = ws_sold_date_sk#13 IN dynamicpruning#8

Subquery:3 Hosting operator id = 20 Hosting Expression = cs_sold_date_sk#16 IN dynamicpruning#8


