== Physical Plan ==
TakeOrderedAndProject (52)
+- * HashAggregate (51)
   +- Exchange (50)
      +- * HashAggregate (49)
         +- * Project (48)
            +- * BroadcastHashJoin Inner BuildRight (47)
               :- * Project (42)
               :  +- * BroadcastHashJoin Inner BuildRight (41)
               :     :- * Project (36)
               :     :  +- * BroadcastHashJoin Inner BuildRight (35)
               :     :     :- * Project (29)
               :     :     :  +- * BroadcastHashJoin Inner BuildRight (28)
               :     :     :     :- * Project (22)
               :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (21)
               :     :     :     :     :- * Project (15)
               :     :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (14)
               :     :     :     :     :     :- * Project (9)
               :     :     :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (8)
               :     :     :     :     :     :     :- * Filter (3)
               :     :     :     :     :     :     :  +- * ColumnarToRow (2)
               :     :     :     :     :     :     :     +- Scan parquet spark_catalog.default.store_sales (1)
               :     :     :     :     :     :     +- BroadcastExchange (7)
               :     :     :     :     :     :        +- * Filter (6)
               :     :     :     :     :     :           +- * ColumnarToRow (5)
               :     :     :     :     :     :              +- Scan parquet spark_catalog.default.store_returns (4)
               :     :     :     :     :     +- BroadcastExchange (13)
               :     :     :     :     :        +- * Filter (12)
               :     :     :     :     :           +- * ColumnarToRow (11)
               :     :     :     :     :              +- Scan parquet spark_catalog.default.catalog_sales (10)
               :     :     :     :     +- BroadcastExchange (20)
               :     :     :     :        +- * Project (19)
               :     :     :     :           +- * Filter (18)
               :     :     :     :              +- * ColumnarToRow (17)
               :     :     :     :                 +- Scan parquet spark_catalog.default.date_dim (16)
               :     :     :     +- BroadcastExchange (27)
               :     :     :        +- * Project (26)
               :     :     :           +- * Filter (25)
               :     :     :              +- * ColumnarToRow (24)
               :     :     :                 +- Scan parquet spark_catalog.default.date_dim (23)
               :     :     +- BroadcastExchange (34)
               :     :        +- * Project (33)
               :     :           +- * Filter (32)
               :     :              +- * ColumnarToRow (31)
               :     :                 +- Scan parquet spark_catalog.default.date_dim (30)
               :     +- BroadcastExchange (40)
               :        +- * Filter (39)
               :           +- * ColumnarToRow (38)
               :              +- Scan parquet spark_catalog.default.store (37)
               +- BroadcastExchange (46)
                  +- * Filter (45)
                     +- * ColumnarToRow (44)
                        +- Scan parquet spark_catalog.default.item (43)


(1) Scan parquet spark_catalog.default.store_sales
Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#6)]
PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_item_sk:int,ss_customer_sk:int,ss_store_sk:int,ss_ticket_number:int,ss_quantity:int>

(2) ColumnarToRow [codegen id : 8]
Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6]

(3) Filter [codegen id : 8]
Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6]
Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3))

(4) Scan parquet spark_catalog.default.store_returns
Output [5]: [sr_item_sk#7, sr_customer_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(sr_returned_date_sk#11)]
PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)]
ReadSchema: struct<sr_item_sk:int,sr_customer_sk:int,sr_ticket_number:int,sr_return_quantity:int>

(5) ColumnarToRow [codegen id : 1]
Input [5]: [sr_item_sk#7, sr_customer_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11]

(6) Filter [codegen id : 1]
Input [5]: [sr_item_sk#7, sr_customer_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11]
Condition : ((isnotnull(sr_customer_sk#8) AND isnotnull(sr_item_sk#7)) AND isnotnull(sr_ticket_number#9))

(7) BroadcastExchange
Input [5]: [sr_item_sk#7, sr_customer_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11]
Arguments: HashedRelationBroadcastMode(List(input[1, int, false], input[0, int, false], input[2, int, false]),false), [plan_id=1]

(8) BroadcastHashJoin [codegen id : 8]
Left keys [3]: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4]
Right keys [3]: [sr_customer_sk#8, sr_item_sk#7, sr_ticket_number#9]
Join type: Inner
Join condition: None

(9) Project [codegen id : 8]
Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#7, sr_customer_sk#8, sr_return_quantity#10, sr_returned_date_sk#11]
Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#7, sr_customer_sk#8, sr_ticket_number#9, sr_return_quantity#10, sr_returned_date_sk#11]

(10) Scan parquet spark_catalog.default.catalog_sales
Output [4]: [cs_bill_customer_sk#12, cs_item_sk#13, cs_quantity#14, cs_sold_date_sk#15]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#15)]
PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_bill_customer_sk:int,cs_item_sk:int,cs_quantity:int>

(11) ColumnarToRow [codegen id : 2]
Input [4]: [cs_bill_customer_sk#12, cs_item_sk#13, cs_quantity#14, cs_sold_date_sk#15]

(12) Filter [codegen id : 2]
Input [4]: [cs_bill_customer_sk#12, cs_item_sk#13, cs_quantity#14, cs_sold_date_sk#15]
Condition : (isnotnull(cs_bill_customer_sk#12) AND isnotnull(cs_item_sk#13))

(13) BroadcastExchange
Input [4]: [cs_bill_customer_sk#12, cs_item_sk#13, cs_quantity#14, cs_sold_date_sk#15]
Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[0, int, false] as bigint), 32) | (cast(input[1, int, false] as bigint) & 4294967295))),false), [plan_id=2]

(14) BroadcastHashJoin [codegen id : 8]
Left keys [2]: [sr_customer_sk#8, sr_item_sk#7]
Right keys [2]: [cs_bill_customer_sk#12, cs_item_sk#13]
Join type: Inner
Join condition: None

(15) Project [codegen id : 8]
Output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#10, sr_returned_date_sk#11, cs_quantity#14, cs_sold_date_sk#15]
Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#7, sr_customer_sk#8, sr_return_quantity#10, sr_returned_date_sk#11, cs_bill_customer_sk#12, cs_item_sk#13, cs_quantity#14, cs_sold_date_sk#15]

(16) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#16, d_year#17, d_moy#18]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,9), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(17) ColumnarToRow [codegen id : 3]
Input [3]: [d_date_sk#16, d_year#17, d_moy#18]

(18) Filter [codegen id : 3]
Input [3]: [d_date_sk#16, d_year#17, d_moy#18]
Condition : ((((isnotnull(d_moy#18) AND isnotnull(d_year#17)) AND (d_moy#18 = 9)) AND (d_year#17 = 1999)) AND isnotnull(d_date_sk#16))

(19) Project [codegen id : 3]
Output [1]: [d_date_sk#16]
Input [3]: [d_date_sk#16, d_year#17, d_moy#18]

(20) BroadcastExchange
Input [1]: [d_date_sk#16]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(21) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [ss_sold_date_sk#6]
Right keys [1]: [d_date_sk#16]
Join type: Inner
Join condition: None

(22) Project [codegen id : 8]
Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#10, sr_returned_date_sk#11, cs_quantity#14, cs_sold_date_sk#15]
Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#10, sr_returned_date_sk#11, cs_quantity#14, cs_sold_date_sk#15, d_date_sk#16]

(23) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#19, d_year#20, d_moy#21]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,9), LessThanOrEqual(d_moy,12), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(24) ColumnarToRow [codegen id : 4]
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]

(25) Filter [codegen id : 4]
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]
Condition : (((((isnotnull(d_moy#21) AND isnotnull(d_year#20)) AND (d_moy#21 >= 9)) AND (d_moy#21 <= 12)) AND (d_year#20 = 1999)) AND isnotnull(d_date_sk#19))

(26) Project [codegen id : 4]
Output [1]: [d_date_sk#19]
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]

(27) BroadcastExchange
Input [1]: [d_date_sk#19]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]

(28) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [sr_returned_date_sk#11]
Right keys [1]: [d_date_sk#19]
Join type: Inner
Join condition: None

(29) Project [codegen id : 8]
Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#10, cs_quantity#14, cs_sold_date_sk#15]
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#10, sr_returned_date_sk#11, cs_quantity#14, cs_sold_date_sk#15, d_date_sk#19]

(30) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#22, d_year#23]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(31) ColumnarToRow [codegen id : 5]
Input [2]: [d_date_sk#22, d_year#23]

(32) Filter [codegen id : 5]
Input [2]: [d_date_sk#22, d_year#23]
Condition : (d_year#23 IN (1999,2000,2001) AND isnotnull(d_date_sk#22))

(33) Project [codegen id : 5]
Output [1]: [d_date_sk#22]
Input [2]: [d_date_sk#22, d_year#23]

(34) BroadcastExchange
Input [1]: [d_date_sk#22]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]

(35) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [cs_sold_date_sk#15]
Right keys [1]: [d_date_sk#22]
Join type: Inner
Join condition: None

(36) Project [codegen id : 8]
Output [5]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#10, cs_quantity#14]
Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#10, cs_quantity#14, cs_sold_date_sk#15, d_date_sk#22]

(37) Scan parquet spark_catalog.default.store
Output [3]: [s_store_sk#24, s_store_id#25, s_store_name#26]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_store_id:string,s_store_name:string>

(38) ColumnarToRow [codegen id : 6]
Input [3]: [s_store_sk#24, s_store_id#25, s_store_name#26]

(39) Filter [codegen id : 6]
Input [3]: [s_store_sk#24, s_store_id#25, s_store_name#26]
Condition : isnotnull(s_store_sk#24)

(40) BroadcastExchange
Input [3]: [s_store_sk#24, s_store_id#25, s_store_name#26]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6]

(41) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [ss_store_sk#3]
Right keys [1]: [s_store_sk#24]
Join type: Inner
Join condition: None

(42) Project [codegen id : 8]
Output [6]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#10, cs_quantity#14, s_store_id#25, s_store_name#26]
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#10, cs_quantity#14, s_store_sk#24, s_store_id#25, s_store_name#26]

(43) Scan parquet spark_catalog.default.item
Output [3]: [i_item_sk#27, i_item_id#28, i_item_desc#29]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string,i_item_desc:string>

(44) ColumnarToRow [codegen id : 7]
Input [3]: [i_item_sk#27, i_item_id#28, i_item_desc#29]

(45) Filter [codegen id : 7]
Input [3]: [i_item_sk#27, i_item_id#28, i_item_desc#29]
Condition : isnotnull(i_item_sk#27)

(46) BroadcastExchange
Input [3]: [i_item_sk#27, i_item_id#28, i_item_desc#29]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7]

(47) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#27]
Join type: Inner
Join condition: None

(48) Project [codegen id : 8]
Output [7]: [ss_quantity#5, sr_return_quantity#10, cs_quantity#14, s_store_id#25, s_store_name#26, i_item_id#28, i_item_desc#29]
Input [9]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#10, cs_quantity#14, s_store_id#25, s_store_name#26, i_item_sk#27, i_item_id#28, i_item_desc#29]

(49) HashAggregate [codegen id : 8]
Input [7]: [ss_quantity#5, sr_return_quantity#10, cs_quantity#14, s_store_id#25, s_store_name#26, i_item_id#28, i_item_desc#29]
Keys [4]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26]
Functions [3]: [partial_sum(ss_quantity#5), partial_sum(sr_return_quantity#10), partial_sum(cs_quantity#14)]
Aggregate Attributes [3]: [sum#30, sum#31, sum#32]
Results [7]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, sum#33, sum#34, sum#35]

(50) Exchange
Input [7]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, sum#33, sum#34, sum#35]
Arguments: hashpartitioning(i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, 5), ENSURE_REQUIREMENTS, [plan_id=8]

(51) HashAggregate [codegen id : 9]
Input [7]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, sum#33, sum#34, sum#35]
Keys [4]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26]
Functions [3]: [sum(ss_quantity#5), sum(sr_return_quantity#10), sum(cs_quantity#14)]
Aggregate Attributes [3]: [sum(ss_quantity#5)#36, sum(sr_return_quantity#10)#37, sum(cs_quantity#14)#38]
Results [7]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, sum(ss_quantity#5)#36 AS store_sales_quantity#39, sum(sr_return_quantity#10)#37 AS store_returns_quantity#40, sum(cs_quantity#14)#38 AS catalog_sales_quantity#41]

(52) TakeOrderedAndProject
Input [7]: [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, store_sales_quantity#39, store_returns_quantity#40, catalog_sales_quantity#41]
Arguments: 100, [i_item_id#28 ASC NULLS FIRST, i_item_desc#29 ASC NULLS FIRST, s_store_id#25 ASC NULLS FIRST, s_store_name#26 ASC NULLS FIRST], [i_item_id#28, i_item_desc#29, s_store_id#25, s_store_name#26, store_sales_quantity#39, store_returns_quantity#40, catalog_sales_quantity#41]

