== Physical Plan ==
TakeOrderedAndProject (30)
+- * HashAggregate (29)
   +- * CometColumnarToRow (28)
      +- CometColumnarExchange (27)
         +- * HashAggregate (26)
            +- * Project (25)
               +- * BroadcastHashJoin Inner BuildRight (24)
                  :- * Project (22)
                  :  +- * BroadcastHashJoin Inner BuildRight (21)
                  :     :- * Project (16)
                  :     :  +- * BroadcastHashJoin Inner BuildRight (15)
                  :     :     :- * Project (9)
                  :     :     :  +- * BroadcastHashJoin Inner BuildRight (8)
                  :     :     :     :- * CometColumnarToRow (3)
                  :     :     :     :  +- CometFilter (2)
                  :     :     :     :     +- CometNativeScan parquet spark_catalog.default.store_sales (1)
                  :     :     :     +- BroadcastExchange (7)
                  :     :     :        +- * Filter (6)
                  :     :     :           +- * ColumnarToRow (5)
                  :     :     :              +- Scan parquet spark_catalog.default.store_returns (4)
                  :     :     +- BroadcastExchange (14)
                  :     :        +- * CometColumnarToRow (13)
                  :     :           +- CometProject (12)
                  :     :              +- CometFilter (11)
                  :     :                 +- CometNativeScan parquet spark_catalog.default.store (10)
                  :     +- BroadcastExchange (20)
                  :        +- * CometColumnarToRow (19)
                  :           +- CometFilter (18)
                  :              +- CometNativeScan parquet spark_catalog.default.date_dim (17)
                  +- ReusedExchange (23)


(1) CometNativeScan parquet spark_catalog.default.store_sales
Output [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5]
Batched: true
Location: InMemoryFileIndex(0 paths)[]
PartitionFilters: [isnotnull(ss_sold_date_sk#5)]
PushedFilters: [IsNotNull(ss_ticket_number), IsNotNull(ss_item_sk), IsNotNull(ss_customer_sk), IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_item_sk:int,ss_customer_sk:int,ss_store_sk:int,ss_ticket_number:int>

(2) CometFilter
Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5]
Condition : (((isnotnull(ss_ticket_number#4) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_customer_sk#2)) AND isnotnull(ss_store_sk#3))

(3) CometColumnarToRow [codegen id : 5]
Input [5]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5]

(4) Scan parquet spark_catalog.default.store_returns
Output [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(sr_returned_date_sk#9), dynamicpruningexpression(sr_returned_date_sk#9 IN dynamicpruning#10)]
PushedFilters: [IsNotNull(sr_ticket_number), IsNotNull(sr_item_sk), IsNotNull(sr_customer_sk)]
ReadSchema: struct<sr_item_sk:int,sr_customer_sk:int,sr_ticket_number:int>

(5) ColumnarToRow [codegen id : 1]
Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9]

(6) Filter [codegen id : 1]
Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9]
Condition : ((isnotnull(sr_ticket_number#8) AND isnotnull(sr_item_sk#6)) AND isnotnull(sr_customer_sk#7))

(7) BroadcastExchange
Input [4]: [sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9]
Arguments: HashedRelationBroadcastMode(List(input[2, int, false], input[0, int, false], input[1, int, false]),false), [plan_id=1]

(8) BroadcastHashJoin [codegen id : 5]
Left keys [3]: [ss_ticket_number#4, ss_item_sk#1, ss_customer_sk#2]
Right keys [3]: [sr_ticket_number#8, sr_item_sk#6, sr_customer_sk#7]
Join type: Inner
Join condition: None

(9) Project [codegen id : 5]
Output [3]: [ss_store_sk#3, ss_sold_date_sk#5, sr_returned_date_sk#9]
Input [9]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5, sr_item_sk#6, sr_customer_sk#7, sr_ticket_number#8, sr_returned_date_sk#9]

(10) CometNativeScan parquet spark_catalog.default.store
Output [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_store_name:string,s_company_id:int,s_street_number:string,s_street_name:string,s_street_type:string,s_suite_number:string,s_city:string,s_county:string,s_state:string,s_zip:string>

(11) CometFilter
Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21]
Condition : isnotnull(s_store_sk#11)

(12) CometProject
Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#16, s_suite_number#17, s_city#18, s_county#19, s_state#20, s_zip#21]
Arguments: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25], [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, static_invoke(CharVarcharCodegenUtils.readSidePadding(s_street_type#16, 15)) AS s_street_type#22, static_invoke(CharVarcharCodegenUtils.readSidePadding(s_suite_number#17, 10)) AS s_suite_number#23, s_city#18, s_county#19, static_invoke(CharVarcharCodegenUtils.readSidePadding(s_state#20, 2)) AS s_state#24, static_invoke(CharVarcharCodegenUtils.readSidePadding(s_zip#21, 10)) AS s_zip#25]

(13) CometColumnarToRow [codegen id : 2]
Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]

(14) BroadcastExchange
Input [11]: [s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(15) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_store_sk#3]
Right keys [1]: [s_store_sk#11]
Join type: Inner
Join condition: None

(16) Project [codegen id : 5]
Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Input [14]: [ss_store_sk#3, ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_sk#11, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]

(17) CometNativeScan parquet spark_catalog.default.date_dim
Output [1]: [d_date_sk#26]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int>

(18) CometFilter
Input [1]: [d_date_sk#26]
Condition : isnotnull(d_date_sk#26)

(19) CometColumnarToRow [codegen id : 3]
Input [1]: [d_date_sk#26]

(20) BroadcastExchange
Input [1]: [d_date_sk#26]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(21) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_sold_date_sk#5]
Right keys [1]: [d_date_sk#26]
Join type: Inner
Join condition: None

(22) Project [codegen id : 5]
Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Input [13]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, d_date_sk#26]

(23) ReusedExchange [Reuses operator id: 35]
Output [1]: [d_date_sk#27]

(24) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [sr_returned_date_sk#9]
Right keys [1]: [d_date_sk#27]
Join type: Inner
Join condition: None

(25) Project [codegen id : 5]
Output [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Input [13]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, d_date_sk#27]

(26) HashAggregate [codegen id : 5]
Input [12]: [ss_sold_date_sk#5, sr_returned_date_sk#9, s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Keys [10]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Functions [5]: [partial_sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), partial_sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)]
Aggregate Attributes [5]: [sum#28, sum#29, sum#30, sum#31, sum#32]
Results [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, sum#33, sum#34, sum#35, sum#36, sum#37]

(27) CometColumnarExchange
Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, sum#33, sum#34, sum#35, sum#36, sum#37]
Arguments: hashpartitioning(s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(28) CometColumnarToRow [codegen id : 6]
Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, sum#33, sum#34, sum#35, sum#36, sum#37]

(29) HashAggregate [codegen id : 6]
Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, sum#33, sum#34, sum#35, sum#36, sum#37]
Keys [10]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25]
Functions [5]: [sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END), sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END), sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)]
Aggregate Attributes [5]: [sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#38, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#39, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#40, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#41, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#42]
Results [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 30) THEN 1 ELSE 0 END)#38 AS 30 days #43, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 30) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 60)) THEN 1 ELSE 0 END)#39 AS 31 - 60 days #44, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 60) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 90)) THEN 1 ELSE 0 END)#40 AS 61 - 90 days #45, sum(CASE WHEN (((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 90) AND ((sr_returned_date_sk#9 - ss_sold_date_sk#5) <= 120)) THEN 1 ELSE 0 END)#41 AS 91 - 120 days #46, sum(CASE WHEN ((sr_returned_date_sk#9 - ss_sold_date_sk#5) > 120) THEN 1 ELSE 0 END)#42 AS >120 days #47]

(30) TakeOrderedAndProject
Input [15]: [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, 30 days #43, 31 - 60 days #44, 61 - 90 days #45, 91 - 120 days #46, >120 days #47]
Arguments: 100, [s_store_name#12 ASC NULLS FIRST, s_company_id#13 ASC NULLS FIRST, s_street_number#14 ASC NULLS FIRST, s_street_name#15 ASC NULLS FIRST, s_street_type#22 ASC NULLS FIRST, s_suite_number#23 ASC NULLS FIRST, s_city#18 ASC NULLS FIRST, s_county#19 ASC NULLS FIRST, s_state#24 ASC NULLS FIRST, s_zip#25 ASC NULLS FIRST], [s_store_name#12, s_company_id#13, s_street_number#14, s_street_name#15, s_street_type#22, s_suite_number#23, s_city#18, s_county#19, s_state#24, s_zip#25, 30 days #43, 31 - 60 days #44, 61 - 90 days #45, 91 - 120 days #46, >120 days #47]

===== Subqueries =====

Subquery:1 Hosting operator id = 4 Hosting Expression = sr_returned_date_sk#9 IN dynamicpruning#10
BroadcastExchange (35)
+- * CometColumnarToRow (34)
   +- CometProject (33)
      +- CometFilter (32)
         +- CometNativeScan parquet spark_catalog.default.date_dim (31)


(31) CometNativeScan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#27, d_year#48, d_moy#49]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,8), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(32) CometFilter
Input [3]: [d_date_sk#27, d_year#48, d_moy#49]
Condition : ((((isnotnull(d_year#48) AND isnotnull(d_moy#49)) AND (d_year#48 = 2001)) AND (d_moy#49 = 8)) AND isnotnull(d_date_sk#27))

(33) CometProject
Input [3]: [d_date_sk#27, d_year#48, d_moy#49]
Arguments: [d_date_sk#27], [d_date_sk#27]

(34) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#27]

(35) BroadcastExchange
Input [1]: [d_date_sk#27]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


