== Physical Plan ==
TakeOrderedAndProject (49)
+- * Project (48)
   +- * BroadcastHashJoin Inner BuildRight (47)
      :- * Project (42)
      :  +- * BroadcastHashJoin Inner BuildRight (41)
      :     :- * Project (35)
      :     :  +- * BroadcastHashJoin Inner BuildRight (34)
      :     :     :- * Filter (15)
      :     :     :  +- * HashAggregate (14)
      :     :     :     +- * ColumnarToRow (13)
      :     :     :        +- CometColumnarExchange (12)
      :     :     :           +- RowToColumnar (11)
      :     :     :              +- * HashAggregate (10)
      :     :     :                 +- * ColumnarToRow (9)
      :     :     :                    +- CometProject (8)
      :     :     :                       +- CometBroadcastHashJoin (7)
      :     :     :                          :- CometFilter (2)
      :     :     :                          :  +- CometScan parquet spark_catalog.default.store_returns (1)
      :     :     :                          +- CometBroadcastExchange (6)
      :     :     :                             +- CometProject (5)
      :     :     :                                +- CometFilter (4)
      :     :     :                                   +- CometScan parquet spark_catalog.default.date_dim (3)
      :     :     +- BroadcastExchange (33)
      :     :        +- * Filter (32)
      :     :           +- * HashAggregate (31)
      :     :              +- * ColumnarToRow (30)
      :     :                 +- CometColumnarExchange (29)
      :     :                    +- RowToColumnar (28)
      :     :                       +- * HashAggregate (27)
      :     :                          +- * HashAggregate (26)
      :     :                             +- * ColumnarToRow (25)
      :     :                                +- CometColumnarExchange (24)
      :     :                                   +- RowToColumnar (23)
      :     :                                      +- * HashAggregate (22)
      :     :                                         +- * ColumnarToRow (21)
      :     :                                            +- CometProject (20)
      :     :                                               +- CometBroadcastHashJoin (19)
      :     :                                                  :- CometFilter (17)
      :     :                                                  :  +- CometScan parquet spark_catalog.default.store_returns (16)
      :     :                                                  +- ReusedExchange (18)
      :     +- BroadcastExchange (40)
      :        +- * ColumnarToRow (39)
      :           +- CometProject (38)
      :              +- CometFilter (37)
      :                 +- CometScan parquet spark_catalog.default.store (36)
      +- BroadcastExchange (46)
         +- * ColumnarToRow (45)
            +- CometFilter (44)
               +- CometScan parquet spark_catalog.default.customer (43)


(1) Scan parquet spark_catalog.default.store_returns
Output [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(sr_returned_date_sk#4), dynamicpruningexpression(sr_returned_date_sk#4 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(sr_store_sk), IsNotNull(sr_customer_sk)]
ReadSchema: struct<sr_customer_sk:int,sr_store_sk:int,sr_return_amt:decimal(7,2)>

(2) CometFilter
Input [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4]
Condition : (isnotnull(sr_store_sk#2) AND isnotnull(sr_customer_sk#1))

(3) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#6, d_year#7]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(4) CometFilter
Input [2]: [d_date_sk#6, d_year#7]
Condition : ((isnotnull(d_year#7) AND (d_year#7 = 2000)) AND isnotnull(d_date_sk#6))

(5) CometProject
Input [2]: [d_date_sk#6, d_year#7]
Arguments: [d_date_sk#6], [d_date_sk#6]

(6) CometBroadcastExchange
Input [1]: [d_date_sk#6]
Arguments: [d_date_sk#6]

(7) CometBroadcastHashJoin
Left output [4]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4]
Right output [1]: [d_date_sk#6]
Arguments: [sr_returned_date_sk#4], [d_date_sk#6], Inner, BuildRight

(8) CometProject
Input [5]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3, sr_returned_date_sk#4, d_date_sk#6]
Arguments: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3], [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3]

(9) ColumnarToRow [codegen id : 1]
Input [3]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3]

(10) HashAggregate [codegen id : 1]
Input [3]: [sr_customer_sk#1, sr_store_sk#2, sr_return_amt#3]
Keys [2]: [sr_customer_sk#1, sr_store_sk#2]
Functions [1]: [partial_sum(UnscaledValue(sr_return_amt#3))]
Aggregate Attributes [1]: [sum#8]
Results [3]: [sr_customer_sk#1, sr_store_sk#2, sum#9]

(11) RowToColumnar
Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#9]

(12) CometColumnarExchange
Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#9]
Arguments: hashpartitioning(sr_customer_sk#1, sr_store_sk#2, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(13) ColumnarToRow [codegen id : 7]
Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#9]

(14) HashAggregate [codegen id : 7]
Input [3]: [sr_customer_sk#1, sr_store_sk#2, sum#9]
Keys [2]: [sr_customer_sk#1, sr_store_sk#2]
Functions [1]: [sum(UnscaledValue(sr_return_amt#3))]
Aggregate Attributes [1]: [sum(UnscaledValue(sr_return_amt#3))#10]
Results [3]: [sr_customer_sk#1 AS ctr_customer_sk#11, sr_store_sk#2 AS ctr_store_sk#12, MakeDecimal(sum(UnscaledValue(sr_return_amt#3))#10,17,2) AS ctr_total_return#13]

(15) Filter [codegen id : 7]
Input [3]: [ctr_customer_sk#11, ctr_store_sk#12, ctr_total_return#13]
Condition : isnotnull(ctr_total_return#13)

(16) Scan parquet spark_catalog.default.store_returns
Output [4]: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16, sr_returned_date_sk#17]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(sr_returned_date_sk#17), dynamicpruningexpression(sr_returned_date_sk#17 IN dynamicpruning#18)]
PushedFilters: [IsNotNull(sr_store_sk)]
ReadSchema: struct<sr_customer_sk:int,sr_store_sk:int,sr_return_amt:decimal(7,2)>

(17) CometFilter
Input [4]: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16, sr_returned_date_sk#17]
Condition : isnotnull(sr_store_sk#15)

(18) ReusedExchange [Reuses operator id: 6]
Output [1]: [d_date_sk#19]

(19) CometBroadcastHashJoin
Left output [4]: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16, sr_returned_date_sk#17]
Right output [1]: [d_date_sk#19]
Arguments: [sr_returned_date_sk#17], [d_date_sk#19], Inner, BuildRight

(20) CometProject
Input [5]: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16, sr_returned_date_sk#17, d_date_sk#19]
Arguments: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16], [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16]

(21) ColumnarToRow [codegen id : 2]
Input [3]: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16]

(22) HashAggregate [codegen id : 2]
Input [3]: [sr_customer_sk#14, sr_store_sk#15, sr_return_amt#16]
Keys [2]: [sr_customer_sk#14, sr_store_sk#15]
Functions [1]: [partial_sum(UnscaledValue(sr_return_amt#16))]
Aggregate Attributes [1]: [sum#20]
Results [3]: [sr_customer_sk#14, sr_store_sk#15, sum#21]

(23) RowToColumnar
Input [3]: [sr_customer_sk#14, sr_store_sk#15, sum#21]

(24) CometColumnarExchange
Input [3]: [sr_customer_sk#14, sr_store_sk#15, sum#21]
Arguments: hashpartitioning(sr_customer_sk#14, sr_store_sk#15, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(25) ColumnarToRow [codegen id : 3]
Input [3]: [sr_customer_sk#14, sr_store_sk#15, sum#21]

(26) HashAggregate [codegen id : 3]
Input [3]: [sr_customer_sk#14, sr_store_sk#15, sum#21]
Keys [2]: [sr_customer_sk#14, sr_store_sk#15]
Functions [1]: [sum(UnscaledValue(sr_return_amt#16))]
Aggregate Attributes [1]: [sum(UnscaledValue(sr_return_amt#16))#10]
Results [2]: [sr_store_sk#15 AS ctr_store_sk#22, MakeDecimal(sum(UnscaledValue(sr_return_amt#16))#10,17,2) AS ctr_total_return#23]

(27) HashAggregate [codegen id : 3]
Input [2]: [ctr_store_sk#22, ctr_total_return#23]
Keys [1]: [ctr_store_sk#22]
Functions [1]: [partial_avg(ctr_total_return#23)]
Aggregate Attributes [2]: [sum#24, count#25]
Results [3]: [ctr_store_sk#22, sum#26, count#27]

(28) RowToColumnar
Input [3]: [ctr_store_sk#22, sum#26, count#27]

(29) CometColumnarExchange
Input [3]: [ctr_store_sk#22, sum#26, count#27]
Arguments: hashpartitioning(ctr_store_sk#22, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=3]

(30) ColumnarToRow [codegen id : 4]
Input [3]: [ctr_store_sk#22, sum#26, count#27]

(31) HashAggregate [codegen id : 4]
Input [3]: [ctr_store_sk#22, sum#26, count#27]
Keys [1]: [ctr_store_sk#22]
Functions [1]: [avg(ctr_total_return#23)]
Aggregate Attributes [1]: [avg(ctr_total_return#23)#28]
Results [2]: [(avg(ctr_total_return#23)#28 * 1.2) AS (avg(ctr_total_return) * 1.2)#29, ctr_store_sk#22]

(32) Filter [codegen id : 4]
Input [2]: [(avg(ctr_total_return) * 1.2)#29, ctr_store_sk#22]
Condition : isnotnull((avg(ctr_total_return) * 1.2)#29)

(33) BroadcastExchange
Input [2]: [(avg(ctr_total_return) * 1.2)#29, ctr_store_sk#22]
Arguments: HashedRelationBroadcastMode(List(cast(input[1, int, true] as bigint)),false), [plan_id=4]

(34) BroadcastHashJoin [codegen id : 7]
Left keys [1]: [ctr_store_sk#12]
Right keys [1]: [ctr_store_sk#22]
Join type: Inner
Join condition: (cast(ctr_total_return#13 as decimal(24,7)) > (avg(ctr_total_return) * 1.2)#29)

(35) Project [codegen id : 7]
Output [2]: [ctr_customer_sk#11, ctr_store_sk#12]
Input [5]: [ctr_customer_sk#11, ctr_store_sk#12, ctr_total_return#13, (avg(ctr_total_return) * 1.2)#29, ctr_store_sk#22]

(36) Scan parquet spark_catalog.default.store
Output [2]: [s_store_sk#30, s_state#31]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_state:string>

(37) CometFilter
Input [2]: [s_store_sk#30, s_state#31]
Condition : ((isnotnull(s_state#31) AND (s_state#31 = TN)) AND isnotnull(s_store_sk#30))

(38) CometProject
Input [2]: [s_store_sk#30, s_state#31]
Arguments: [s_store_sk#30], [s_store_sk#30]

(39) ColumnarToRow [codegen id : 5]
Input [1]: [s_store_sk#30]

(40) BroadcastExchange
Input [1]: [s_store_sk#30]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]

(41) BroadcastHashJoin [codegen id : 7]
Left keys [1]: [ctr_store_sk#12]
Right keys [1]: [s_store_sk#30]
Join type: Inner
Join condition: None

(42) Project [codegen id : 7]
Output [1]: [ctr_customer_sk#11]
Input [3]: [ctr_customer_sk#11, ctr_store_sk#12, s_store_sk#30]

(43) Scan parquet spark_catalog.default.customer
Output [2]: [c_customer_sk#32, c_customer_id#33]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer]
PushedFilters: [IsNotNull(c_customer_sk)]
ReadSchema: struct<c_customer_sk:int,c_customer_id:string>

(44) CometFilter
Input [2]: [c_customer_sk#32, c_customer_id#33]
Condition : isnotnull(c_customer_sk#32)

(45) ColumnarToRow [codegen id : 6]
Input [2]: [c_customer_sk#32, c_customer_id#33]

(46) BroadcastExchange
Input [2]: [c_customer_sk#32, c_customer_id#33]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6]

(47) BroadcastHashJoin [codegen id : 7]
Left keys [1]: [ctr_customer_sk#11]
Right keys [1]: [c_customer_sk#32]
Join type: Inner
Join condition: None

(48) Project [codegen id : 7]
Output [1]: [c_customer_id#33]
Input [3]: [ctr_customer_sk#11, c_customer_sk#32, c_customer_id#33]

(49) TakeOrderedAndProject
Input [1]: [c_customer_id#33]
Arguments: 100, [c_customer_id#33 ASC NULLS FIRST], [c_customer_id#33]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = sr_returned_date_sk#4 IN dynamicpruning#5
BroadcastExchange (54)
+- * ColumnarToRow (53)
   +- CometProject (52)
      +- CometFilter (51)
         +- CometScan parquet spark_catalog.default.date_dim (50)


(50) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#6, d_year#7]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(51) CometFilter
Input [2]: [d_date_sk#6, d_year#7]
Condition : ((isnotnull(d_year#7) AND (d_year#7 = 2000)) AND isnotnull(d_date_sk#6))

(52) CometProject
Input [2]: [d_date_sk#6, d_year#7]
Arguments: [d_date_sk#6], [d_date_sk#6]

(53) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#6]

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

Subquery:2 Hosting operator id = 16 Hosting Expression = sr_returned_date_sk#17 IN dynamicpruning#5


