== Physical Plan ==
VeloxColumnarToRow (46)
+- TakeOrderedAndProjectExecTransformer (45)
   +- ^ ProjectExecTransformer (43)
      +- ^ RegularHashAggregateExecTransformer (42)
         +- ^ InputIteratorTransformer (41)
            +- ColumnarExchange (39)
               +- VeloxResizeBatches (38)
                  +- ^ ProjectExecTransformer (36)
                     +- ^ FlushableHashAggregateExecTransformer (35)
                        +- ^ ProjectExecTransformer (34)
                           +- ^ ExpandExecTransformer (33)
                              +- ^ ProjectExecTransformer (32)
                                 +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (31)
                                    :- ^ ProjectExecTransformer (24)
                                    :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (23)
                                    :     :- ^ ProjectExecTransformer (16)
                                    :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (15)
                                    :     :     :- ^ ProjectExecTransformer (11)
                                    :     :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (10)
                                    :     :     :     :- ^ FilterExecTransformer (2)
                                    :     :     :     :  +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store_sales (1)
                                    :     :     :     +- ^ InputIteratorTransformer (9)
                                    :     :     :        +- ColumnarBroadcastExchange (7)
                                    :     :     :           +- ^ ProjectExecTransformer (5)
                                    :     :     :              +- ^ FilterExecTransformer (4)
                                    :     :     :                 +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics (3)
                                    :     :     +- ^ InputIteratorTransformer (14)
                                    :     :        +- ReusedExchange (12)
                                    :     +- ^ InputIteratorTransformer (22)
                                    :        +- ColumnarBroadcastExchange (20)
                                    :           +- ^ FilterExecTransformer (18)
                                    :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store (17)
                                    +- ^ InputIteratorTransformer (30)
                                       +- ColumnarBroadcastExchange (28)
                                          +- ^ FilterExecTransformer (26)
                                             +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (25)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.store_sales
Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)]
PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_cdemo_sk:int,ss_store_sk:int,ss_quantity:int,ss_list_price:decimal(7,2),ss_sales_price:decimal(7,2),ss_coupon_amt:decimal(7,2)>

(2) FilterExecTransformer
Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Arguments: ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1))

(3) FileSourceScanExecTransformer parquet spark_catalog.default.customer_demographics
Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_gender), IsNotNull(cd_marital_status), IsNotNull(cd_education_status), EqualTo(cd_gender,M), EqualTo(cd_marital_status,S), EqualTo(cd_education_status,College             ), IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_gender:string,cd_marital_status:string,cd_education_status:string>

(4) FilterExecTransformer
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Arguments: ((((((isnotnull(cd_gender#11) AND isnotnull(cd_marital_status#12)) AND isnotnull(cd_education_status#13)) AND (cd_gender#11 = M)) AND (cd_marital_status#12 = S)) AND (cd_education_status#13 = College             )) AND isnotnull(cd_demo_sk#10))

(5) ProjectExecTransformer
Output [1]: [cd_demo_sk#10]
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]

(6) WholeStageCodegenTransformer (2)
Input [1]: [cd_demo_sk#10]
Arguments: false

(7) ColumnarBroadcastExchange
Input [1]: [cd_demo_sk#10]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(8) InputAdapter
Input [1]: [cd_demo_sk#10]

(9) InputIteratorTransformer
Input [1]: [cd_demo_sk#10]

(10) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_cdemo_sk#2]
Right keys [1]: [cd_demo_sk#10]
Join type: Inner
Join condition: None

(11) ProjectExecTransformer
Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10]

(12) ReusedExchange [Reuses operator id: 51]
Output [1]: [d_date_sk#14]

(13) InputAdapter
Input [1]: [d_date_sk#14]

(14) InputIteratorTransformer
Input [1]: [d_date_sk#14]

(15) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_sold_date_sk#8]
Right keys [1]: [d_date_sk#14]
Join type: Inner
Join condition: None

(16) ProjectExecTransformer
Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7]
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14]

(17) FileSourceScanExecTransformer parquet spark_catalog.default.store
Output [2]: [s_store_sk#15, s_state#16]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_state), EqualTo(s_state,TN), IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_state:string>

(18) FilterExecTransformer
Input [2]: [s_store_sk#15, s_state#16]
Arguments: ((isnotnull(s_state#16) AND (s_state#16 = TN)) AND isnotnull(s_store_sk#15))

(19) WholeStageCodegenTransformer (4)
Input [2]: [s_store_sk#15, s_state#16]
Arguments: false

(20) ColumnarBroadcastExchange
Input [2]: [s_store_sk#15, s_state#16]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(21) InputAdapter
Input [2]: [s_store_sk#15, s_state#16]

(22) InputIteratorTransformer
Input [2]: [s_store_sk#15, s_state#16]

(23) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_store_sk#3]
Right keys [1]: [s_store_sk#15]
Join type: Inner
Join condition: None

(24) ProjectExecTransformer
Output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16]
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#15, s_state#16]

(25) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [2]: [i_item_sk#17, i_item_id#18]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(26) FilterExecTransformer
Input [2]: [i_item_sk#17, i_item_id#18]
Arguments: isnotnull(i_item_sk#17)

(27) WholeStageCodegenTransformer (5)
Input [2]: [i_item_sk#17, i_item_id#18]
Arguments: false

(28) ColumnarBroadcastExchange
Input [2]: [i_item_sk#17, i_item_id#18]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(29) InputAdapter
Input [2]: [i_item_sk#17, i_item_id#18]

(30) InputIteratorTransformer
Input [2]: [i_item_sk#17, i_item_id#18]

(31) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#17]
Join type: Inner
Join condition: None

(32) ProjectExecTransformer
Output [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16]
Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#16, i_item_sk#17, i_item_id#18]

(33) ExpandExecTransformer
Input [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16]
Arguments: [[ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, s_state#16, 0], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#18, null, 1], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, null, null, 3]], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#20, spark_grouping_id#21]

(34) ProjectExecTransformer
Output [7]: [ss_quantity#4, i_item_id#19, s_state#20, spark_grouping_id#21, UnscaledValue(ss_list_price#5) AS _pre_1#22, UnscaledValue(ss_coupon_amt#7) AS _pre_2#23, UnscaledValue(ss_sales_price#6) AS _pre_3#24]
Input [7]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#19, s_state#20, spark_grouping_id#21]

(35) FlushableHashAggregateExecTransformer
Input [7]: [ss_quantity#4, i_item_id#19, s_state#20, spark_grouping_id#21, _pre_1#22, _pre_2#23, _pre_3#24]
Keys [3]: [i_item_id#19, s_state#20, spark_grouping_id#21]
Functions [4]: [partial_avg(ss_quantity#4), partial_avg(_pre_1#22), partial_avg(_pre_2#23), partial_avg(_pre_3#24)]
Aggregate Attributes [8]: [sum#25, count#26, sum#27, count#28, sum#29, count#30, sum#31, count#32]
Results [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]

(36) ProjectExecTransformer
Output [12]: [hash(i_item_id#19, s_state#20, spark_grouping_id#21, 42) AS hash_partition_key#41, i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]
Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]

(37) WholeStageCodegenTransformer (6)
Input [12]: [hash_partition_key#41, i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]
Arguments: false

(38) VeloxResizeBatches
Input [12]: [hash_partition_key#41, i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]
Arguments: 1024, 2147483647, 10485760

(39) ColumnarExchange
Input [12]: [hash_partition_key#41, i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]
Arguments: hashpartitioning(i_item_id#19, s_state#20, spark_grouping_id#21, 1), ENSURE_REQUIREMENTS, [i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40], [plan_id=4], [shuffle_writer_type=hash]

(40) InputAdapter
Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]

(41) InputIteratorTransformer
Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]

(42) RegularHashAggregateExecTransformer
Input [11]: [i_item_id#19, s_state#20, spark_grouping_id#21, sum#33, count#34, sum#35, count#36, sum#37, count#38, sum#39, count#40]
Keys [3]: [i_item_id#19, s_state#20, spark_grouping_id#21]
Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))]
Aggregate Attributes [4]: [avg(ss_quantity#4)#42, avg(UnscaledValue(ss_list_price#5))#43, avg(UnscaledValue(ss_coupon_amt#7))#44, avg(UnscaledValue(ss_sales_price#6))#45]
Results [7]: [i_item_id#19, s_state#20, spark_grouping_id#21, avg(ss_quantity#4)#42, avg(UnscaledValue(ss_list_price#5))#43, avg(UnscaledValue(ss_coupon_amt#7))#44, avg(UnscaledValue(ss_sales_price#6))#45]

(43) ProjectExecTransformer
Output [7]: [i_item_id#19, s_state#20, cast((shiftright(spark_grouping_id#21, 0) & 1) as tinyint) AS g_state#46, avg(ss_quantity#4)#42 AS agg1#47, cast((avg(UnscaledValue(ss_list_price#5))#43 / 100.0) as decimal(11,6)) AS agg2#48, cast((avg(UnscaledValue(ss_coupon_amt#7))#44 / 100.0) as decimal(11,6)) AS agg3#49, cast((avg(UnscaledValue(ss_sales_price#6))#45 / 100.0) as decimal(11,6)) AS agg4#50]
Input [7]: [i_item_id#19, s_state#20, spark_grouping_id#21, avg(ss_quantity#4)#42, avg(UnscaledValue(ss_list_price#5))#43, avg(UnscaledValue(ss_coupon_amt#7))#44, avg(UnscaledValue(ss_sales_price#6))#45]

(44) WholeStageCodegenTransformer (7)
Input [7]: [i_item_id#19, s_state#20, g_state#46, agg1#47, agg2#48, agg3#49, agg4#50]
Arguments: false

(45) TakeOrderedAndProjectExecTransformer
Input [7]: [i_item_id#19, s_state#20, g_state#46, agg1#47, agg2#48, agg3#49, agg4#50]
Arguments: 100, [i_item_id#19 ASC NULLS FIRST, s_state#20 ASC NULLS FIRST], [i_item_id#19, s_state#20, g_state#46, agg1#47, agg2#48, agg3#49, agg4#50], 0

(46) VeloxColumnarToRow
Input [7]: [i_item_id#19, s_state#20, g_state#46, agg1#47, agg2#48, agg3#49, agg4#50]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9
ColumnarBroadcastExchange (51)
+- ^ ProjectExecTransformer (49)
   +- ^ FilterExecTransformer (48)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (47)


(47) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#14, d_year#51]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(48) FilterExecTransformer
Input [2]: [d_date_sk#14, d_year#51]
Arguments: ((isnotnull(d_year#51) AND (d_year#51 = 2002)) AND isnotnull(d_date_sk#14))

(49) ProjectExecTransformer
Output [1]: [d_date_sk#14]
Input [2]: [d_date_sk#14, d_year#51]

(50) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#14]
Arguments: false

(51) ColumnarBroadcastExchange
Input [1]: [d_date_sk#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


