== Physical Plan ==
VeloxColumnarToRow (41)
+- ^ RegularHashAggregateExecTransformer (39)
   +- ^ InputIteratorTransformer (38)
      +- ColumnarExchange (36)
         +- VeloxResizeBatches (35)
            +- ^ FlushableHashAggregateExecTransformer (33)
               +- ^ ProjectExecTransformer (32)
                  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (31)
                     :- ^ ProjectExecTransformer (27)
                     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (26)
                     :     :- ^ ProjectExecTransformer (18)
                     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (17)
                     :     :     :- ^ ProjectExecTransformer (10)
                     :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (9)
                     :     :     :     :- ^ FilterExecTransformer (2)
                     :     :     :     :  +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store_sales (1)
                     :     :     :     +- ^ InputIteratorTransformer (8)
                     :     :     :        +- ColumnarBroadcastExchange (6)
                     :     :     :           +- ^ FilterExecTransformer (4)
                     :     :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store (3)
                     :     :     +- ^ InputIteratorTransformer (16)
                     :     :        +- ColumnarBroadcastExchange (14)
                     :     :           +- ^ FilterExecTransformer (12)
                     :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (11)
                     :     +- ^ InputIteratorTransformer (25)
                     :        +- ColumnarBroadcastExchange (23)
                     :           +- ^ ProjectExecTransformer (21)
                     :              +- ^ FilterExecTransformer (20)
                     :                 +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_address (19)
                     +- ^ InputIteratorTransformer (30)
                        +- ReusedExchange (28)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.store_sales
Output [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#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)]
PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_addr_sk), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00))), Or(Or(And(GreaterThanOrEqual(ss_net_profit,0.00),LessThanOrEqual(ss_net_profit,2000.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,3000.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,25000.00)))]
ReadSchema: struct<ss_cdemo_sk:int,ss_addr_sk:int,ss_store_sk:int,ss_quantity:int,ss_sales_price:decimal(7,2),ss_net_profit:decimal(7,2)>

(2) FilterExecTransformer
Input [7]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7]
Arguments: ((((isnotnull(ss_store_sk#3) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_addr_sk#2)) AND ((((ss_sales_price#5 >= 100.00) AND (ss_sales_price#5 <= 150.00)) OR ((ss_sales_price#5 >= 50.00) AND (ss_sales_price#5 <= 100.00))) OR ((ss_sales_price#5 >= 150.00) AND (ss_sales_price#5 <= 200.00)))) AND ((((ss_net_profit#6 >= 0.00) AND (ss_net_profit#6 <= 2000.00)) OR ((ss_net_profit#6 >= 150.00) AND (ss_net_profit#6 <= 3000.00))) OR ((ss_net_profit#6 >= 50.00) AND (ss_net_profit#6 <= 25000.00))))

(3) FileSourceScanExecTransformer parquet spark_catalog.default.store
Output [1]: [s_store_sk#9]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int>

(4) FilterExecTransformer
Input [1]: [s_store_sk#9]
Arguments: isnotnull(s_store_sk#9)

(5) WholeStageCodegenTransformer (2)
Input [1]: [s_store_sk#9]
Arguments: false

(6) ColumnarBroadcastExchange
Input [1]: [s_store_sk#9]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(7) InputAdapter
Input [1]: [s_store_sk#9]

(8) InputIteratorTransformer
Input [1]: [s_store_sk#9]

(9) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_store_sk#3]
Right keys [1]: [s_store_sk#9]
Join type: Inner
Join condition: None

(10) ProjectExecTransformer
Output [6]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7]
Input [8]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_store_sk#3, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, s_store_sk#9]

(11) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk), Or(Or(And(EqualTo(cd_marital_status,M),EqualTo(cd_education_status,4 yr Degree         )),And(EqualTo(cd_marital_status,D),EqualTo(cd_education_status,2 yr Degree         ))),And(EqualTo(cd_marital_status,S),EqualTo(cd_education_status,College             )))]
ReadSchema: struct<cd_demo_sk:int,cd_marital_status:string,cd_education_status:string>

(12) FilterExecTransformer
Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]
Arguments: (isnotnull(cd_demo_sk#10) AND ((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree         )) OR ((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree         ))) OR ((cd_marital_status#11 = S) AND (cd_education_status#12 = College             ))))

(13) WholeStageCodegenTransformer (3)
Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]
Arguments: false

(14) ColumnarBroadcastExchange
Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(15) InputAdapter
Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]

(16) InputIteratorTransformer
Input [3]: [cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]

(17) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_cdemo_sk#1]
Right keys [1]: [cd_demo_sk#10]
Join type: Inner
Join condition: ((((((cd_marital_status#11 = M) AND (cd_education_status#12 = 4 yr Degree         )) AND (ss_sales_price#5 >= 100.00)) AND (ss_sales_price#5 <= 150.00)) OR ((((cd_marital_status#11 = D) AND (cd_education_status#12 = 2 yr Degree         )) AND (ss_sales_price#5 >= 50.00)) AND (ss_sales_price#5 <= 100.00))) OR ((((cd_marital_status#11 = S) AND (cd_education_status#12 = College             )) AND (ss_sales_price#5 >= 150.00)) AND (ss_sales_price#5 <= 200.00)))

(18) ProjectExecTransformer
Output [4]: [ss_addr_sk#2, ss_quantity#4, ss_net_profit#6, ss_sold_date_sk#7]
Input [9]: [ss_cdemo_sk#1, ss_addr_sk#2, ss_quantity#4, ss_sales_price#5, ss_net_profit#6, ss_sold_date_sk#7, cd_demo_sk#10, cd_marital_status#11, cd_education_status#12]

(19) FileSourceScanExecTransformer parquet spark_catalog.default.customer_address
Output [3]: [ca_address_sk#13, ca_state#14, ca_country#15]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_address]
PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk), Or(Or(In(ca_state, [CO,OH,TX]),In(ca_state, [KY,MN,OR])),In(ca_state, [CA,MS,VA]))]
ReadSchema: struct<ca_address_sk:int,ca_state:string,ca_country:string>

(20) FilterExecTransformer
Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15]
Arguments: (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((ca_state#14 IN (CO,OH,TX) OR ca_state#14 IN (OR,MN,KY)) OR ca_state#14 IN (VA,CA,MS)))

(21) ProjectExecTransformer
Output [2]: [ca_address_sk#13, ca_state#14]
Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15]

(22) WholeStageCodegenTransformer (4)
Input [2]: [ca_address_sk#13, ca_state#14]
Arguments: false

(23) ColumnarBroadcastExchange
Input [2]: [ca_address_sk#13, ca_state#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(24) InputAdapter
Input [2]: [ca_address_sk#13, ca_state#14]

(25) InputIteratorTransformer
Input [2]: [ca_address_sk#13, ca_state#14]

(26) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_addr_sk#2]
Right keys [1]: [ca_address_sk#13]
Join type: Inner
Join condition: ((((ca_state#14 IN (CO,OH,TX) AND (ss_net_profit#6 >= 0.00)) AND (ss_net_profit#6 <= 2000.00)) OR ((ca_state#14 IN (OR,MN,KY) AND (ss_net_profit#6 >= 150.00)) AND (ss_net_profit#6 <= 3000.00))) OR ((ca_state#14 IN (VA,CA,MS) AND (ss_net_profit#6 >= 50.00)) AND (ss_net_profit#6 <= 25000.00)))

(27) ProjectExecTransformer
Output [2]: [ss_quantity#4, ss_sold_date_sk#7]
Input [6]: [ss_addr_sk#2, ss_quantity#4, ss_net_profit#6, ss_sold_date_sk#7, ca_address_sk#13, ca_state#14]

(28) ReusedExchange [Reuses operator id: 46]
Output [1]: [d_date_sk#16]

(29) InputAdapter
Input [1]: [d_date_sk#16]

(30) InputIteratorTransformer
Input [1]: [d_date_sk#16]

(31) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_sold_date_sk#7]
Right keys [1]: [d_date_sk#16]
Join type: Inner
Join condition: None

(32) ProjectExecTransformer
Output [1]: [ss_quantity#4]
Input [3]: [ss_quantity#4, ss_sold_date_sk#7, d_date_sk#16]

(33) FlushableHashAggregateExecTransformer
Input [1]: [ss_quantity#4]
Keys: []
Functions [1]: [partial_sum(ss_quantity#4)]
Aggregate Attributes [1]: [sum#17]
Results [1]: [sum#18]

(34) WholeStageCodegenTransformer (6)
Input [1]: [sum#18]
Arguments: false

(35) VeloxResizeBatches
Input [1]: [sum#18]
Arguments: 1024, 2147483647, 10485760

(36) ColumnarExchange
Input [1]: [sum#18]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=4], [shuffle_writer_type=hash]

(37) InputAdapter
Input [1]: [sum#18]

(38) InputIteratorTransformer
Input [1]: [sum#18]

(39) RegularHashAggregateExecTransformer
Input [1]: [sum#18]
Keys: []
Functions [1]: [sum(ss_quantity#4)]
Aggregate Attributes [1]: [sum(ss_quantity#4)#19]
Results [1]: [sum(ss_quantity#4)#19 AS sum(ss_quantity)#20]

(40) WholeStageCodegenTransformer (7)
Input [1]: [sum(ss_quantity)#20]
Arguments: false

(41) VeloxColumnarToRow
Input [1]: [sum(ss_quantity)#20]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#7 IN dynamicpruning#8
ColumnarBroadcastExchange (46)
+- ^ ProjectExecTransformer (44)
   +- ^ FilterExecTransformer (43)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (42)


(42) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#16, d_year#21]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(43) FilterExecTransformer
Input [2]: [d_date_sk#16, d_year#21]
Arguments: ((isnotnull(d_year#21) AND (d_year#21 = 2001)) AND isnotnull(d_date_sk#16))

(44) ProjectExecTransformer
Output [1]: [d_date_sk#16]
Input [2]: [d_date_sk#16, d_year#21]

(45) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#16]
Arguments: false

(46) ColumnarBroadcastExchange
Input [1]: [d_date_sk#16]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


