== Physical Plan ==
VeloxColumnarToRow (44)
+- TakeOrderedAndProjectExecTransformer (43)
   +- ^ ProjectExecTransformer (41)
      +- ^ FilterExecTransformer (40)
         +- ^ WindowExecTransformer (39)
            +- ^ SortExecTransformer (38)
               +- ^ InputIteratorTransformer (37)
                  +- ColumnarExchange (35)
                     +- VeloxResizeBatches (34)
                        +- ^ ProjectExecTransformer (32)
                           +- ^ RegularHashAggregateExecTransformer (31)
                              +- ^ InputIteratorTransformer (30)
                                 +- ColumnarExchange (28)
                                    +- VeloxResizeBatches (27)
                                       +- ^ ProjectExecTransformer (25)
                                          +- ^ FlushableHashAggregateExecTransformer (24)
                                             +- ^ ProjectExecTransformer (23)
                                                +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (22)
                                                   :- ^ ProjectExecTransformer (15)
                                                   :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (14)
                                                   :     :- ^ ProjectExecTransformer (10)
                                                   :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildLeft (9)
                                                   :     :     :- ^ InputIteratorTransformer (6)
                                                   :     :     :  +- ColumnarBroadcastExchange (4)
                                                   :     :     :     +- ^ FilterExecTransformer (2)
                                                   :     :     :        +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (1)
                                                   :     :     +- ^ FilterExecTransformer (8)
                                                   :     :        +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store_sales (7)
                                                   :     +- ^ InputIteratorTransformer (13)
                                                   :        +- ReusedExchange (11)
                                                   +- ^ InputIteratorTransformer (21)
                                                      +- ColumnarBroadcastExchange (19)
                                                         +- ^ FilterExecTransformer (17)
                                                            +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store (16)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [Or(And(In(i_category, [Books                                             ,Electronics                                       ,Sports                                            ]),In(i_class, [computers                                         ,football                                          ,stereo                                            ])),And(In(i_category, [Jewelry                                           ,Men                                               ,Women                                             ]),In(i_class, [birdal                                            ,dresses                                           ,shirts                                            ]))), IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand:string,i_class:string,i_category:string>

(2) FilterExecTransformer
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]
Arguments: (((i_category#4 IN (Books                                             ,Electronics                                       ,Sports                                            ) AND i_class#3 IN (computers                                         ,stereo                                            ,football                                          )) OR (i_category#4 IN (Men                                               ,Jewelry                                           ,Women                                             ) AND i_class#3 IN (shirts                                            ,birdal                                            ,dresses                                           ))) AND isnotnull(i_item_sk#1))

(3) WholeStageCodegenTransformer (1)
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]
Arguments: false

(4) ColumnarBroadcastExchange
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(5) InputAdapter
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]

(6) InputIteratorTransformer
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]

(7) FileSourceScanExecTransformer parquet spark_catalog.default.store_sales
Output [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#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_item_sk), IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_item_sk:int,ss_store_sk:int,ss_sales_price:decimal(7,2)>

(8) FilterExecTransformer
Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]
Arguments: (isnotnull(ss_item_sk#5) AND isnotnull(ss_store_sk#6))

(9) BroadcastHashJoinExecTransformer
Left keys [1]: [i_item_sk#1]
Right keys [1]: [ss_item_sk#5]
Join type: Inner
Join condition: None

(10) ProjectExecTransformer
Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]
Input [8]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]

(11) ReusedExchange [Reuses operator id: 49]
Output [2]: [d_date_sk#10, d_moy#11]

(12) InputAdapter
Input [2]: [d_date_sk#10, d_moy#11]

(13) InputIteratorTransformer
Input [2]: [d_date_sk#10, d_moy#11]

(14) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_sold_date_sk#8]
Right keys [1]: [d_date_sk#10]
Join type: Inner
Join condition: None

(15) ProjectExecTransformer
Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#11]
Input [8]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8, d_date_sk#10, d_moy#11]

(16) FileSourceScanExecTransformer parquet spark_catalog.default.store
Output [3]: [s_store_sk#12, s_store_name#13, s_company_name#14]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_store_name:string,s_company_name:string>

(17) FilterExecTransformer
Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14]
Arguments: isnotnull(s_store_sk#12)

(18) WholeStageCodegenTransformer (4)
Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14]
Arguments: false

(19) ColumnarBroadcastExchange
Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(20) InputAdapter
Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14]

(21) InputIteratorTransformer
Input [3]: [s_store_sk#12, s_store_name#13, s_company_name#14]

(22) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_store_sk#6]
Right keys [1]: [s_store_sk#12]
Join type: Inner
Join condition: None

(23) ProjectExecTransformer
Output [7]: [i_brand#2, i_class#3, i_category#4, d_moy#11, s_store_name#13, s_company_name#14, UnscaledValue(ss_sales_price#7) AS _pre_1#15]
Input [9]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#11, s_store_sk#12, s_store_name#13, s_company_name#14]

(24) FlushableHashAggregateExecTransformer
Input [7]: [i_brand#2, i_class#3, i_category#4, d_moy#11, s_store_name#13, s_company_name#14, _pre_1#15]
Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11]
Functions [1]: [partial_sum(_pre_1#15)]
Aggregate Attributes [1]: [sum#16]
Results [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]

(25) ProjectExecTransformer
Output [8]: [hash(i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, 42) AS hash_partition_key#18, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]

(26) WholeStageCodegenTransformer (5)
Input [8]: [hash_partition_key#18, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]
Arguments: false

(27) VeloxResizeBatches
Input [8]: [hash_partition_key#18, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]
Arguments: 1024, 2147483647, 10485760

(28) ColumnarExchange
Input [8]: [hash_partition_key#18, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]
Arguments: hashpartitioning(i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, 1), ENSURE_REQUIREMENTS, [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17], [plan_id=3], [shuffle_writer_type=hash]

(29) InputAdapter
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]

(30) InputIteratorTransformer
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]

(31) RegularHashAggregateExecTransformer
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum#17]
Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11]
Functions [1]: [sum(UnscaledValue(ss_sales_price#7))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#7))#19]
Results [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum(UnscaledValue(ss_sales_price#7))#19]

(32) ProjectExecTransformer
Output [9]: [hash(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, 42) AS hash_partition_key#20, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#19,17,2) AS sum_sales#21, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#19,17,2) AS _w0#22]
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum(UnscaledValue(ss_sales_price#7))#19]

(33) WholeStageCodegenTransformer (6)
Input [9]: [hash_partition_key#20, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]
Arguments: false

(34) VeloxResizeBatches
Input [9]: [hash_partition_key#20, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]
Arguments: 1024, 2147483647, 10485760

(35) ColumnarExchange
Input [9]: [hash_partition_key#20, i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]
Arguments: hashpartitioning(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, 1), ENSURE_REQUIREMENTS, [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22], [plan_id=4], [shuffle_writer_type=hash]

(36) InputAdapter
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]

(37) InputIteratorTransformer
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]

(38) SortExecTransformer
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]
Arguments: [i_category#4 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST, s_company_name#14 ASC NULLS FIRST], false, 0

(39) WindowExecTransformer
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22]
Arguments: [avg(_w0#22) windowspecdefinition(i_category#4, i_brand#2, s_store_name#13, s_company_name#14, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#23], [i_category#4, i_brand#2, s_store_name#13, s_company_name#14]

(40) FilterExecTransformer
Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22, avg_monthly_sales#23]
Arguments: CASE WHEN NOT (avg_monthly_sales#23 = 0.000000) THEN ((abs((sum_sales#21 - avg_monthly_sales#23)) / avg_monthly_sales#23) > 0.1000000000000000) END

(41) ProjectExecTransformer
Output [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, avg_monthly_sales#23, (sum_sales#21 - avg_monthly_sales#23) AS _pre_2#24]
Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, _w0#22, avg_monthly_sales#23]

(42) WholeStageCodegenTransformer (7)
Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, avg_monthly_sales#23, _pre_2#24]
Arguments: false

(43) TakeOrderedAndProjectExecTransformer
Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, avg_monthly_sales#23, _pre_2#24]
Arguments: 100, [_pre_2#24 ASC NULLS FIRST, s_store_name#13 ASC NULLS FIRST], [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, avg_monthly_sales#23], 0

(44) VeloxColumnarToRow
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#13, s_company_name#14, d_moy#11, sum_sales#21, avg_monthly_sales#23]

===== Subqueries =====

Subquery:1 Hosting operator id = 7 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9
ColumnarBroadcastExchange (49)
+- ^ ProjectExecTransformer (47)
   +- ^ FilterExecTransformer (46)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (45)


(45) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#10, d_year#25, d_moy#11]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(46) FilterExecTransformer
Input [3]: [d_date_sk#10, d_year#25, d_moy#11]
Arguments: ((isnotnull(d_year#25) AND (d_year#25 = 1999)) AND isnotnull(d_date_sk#10))

(47) ProjectExecTransformer
Output [2]: [d_date_sk#10, d_moy#11]
Input [3]: [d_date_sk#10, d_year#25, d_moy#11]

(48) WholeStageCodegenTransformer (2)
Input [2]: [d_date_sk#10, d_moy#11]
Arguments: false

(49) ColumnarBroadcastExchange
Input [2]: [d_date_sk#10, d_moy#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


