== Physical Plan ==
VeloxColumnarToRow (45)
+- TakeOrderedAndProjectExecTransformer (44)
   +- ^ ProjectExecTransformer (42)
      +- ^ FilterExecTransformer (41)
         +- ^ WindowExecTransformer (40)
            +- ^ SortExecTransformer (39)
               +- ^ InputIteratorTransformer (38)
                  +- ColumnarExchange (36)
                     +- VeloxResizeBatches (35)
                        +- ^ ProjectExecTransformer (33)
                           +- ^ RegularHashAggregateExecTransformer (32)
                              +- ^ InputIteratorTransformer (31)
                                 +- ColumnarExchange (29)
                                    +- VeloxResizeBatches (28)
                                       +- ^ ProjectExecTransformer (26)
                                          +- ^ FlushableHashAggregateExecTransformer (25)
                                             +- ^ ProjectExecTransformer (24)
                                                +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (23)
                                                   :- ^ ProjectExecTransformer (16)
                                                   :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (15)
                                                   :     :- ^ ProjectExecTransformer (11)
                                                   :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (10)
                                                   :     :     :- ^ ProjectExecTransformer (3)
                                                   :     :     :  +- ^ FilterExecTransformer (2)
                                                   :     :     :     +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (1)
                                                   :     :     +- ^ InputIteratorTransformer (9)
                                                   :     :        +- ColumnarBroadcastExchange (7)
                                                   :     :           +- ^ FilterExecTransformer (5)
                                                   :     :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store_sales (4)
                                                   :     +- ^ InputIteratorTransformer (14)
                                                   :        +- ReusedExchange (12)
                                                   +- ^ InputIteratorTransformer (22)
                                                      +- ColumnarBroadcastExchange (20)
                                                         +- ^ FilterExecTransformer (18)
                                                            +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store (17)


(1) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [Or(And(And(In(i_category, [Books                                             ,Children                                          ,Electronics                                       ]),In(i_class, [personal                                          ,portable                                          ,reference                                         ,self-help                                         ])),In(i_brand, [exportiunivamalg #6                               ,scholaramalgamalg #7                             ,scholaramalgamalg #8                              ,scholaramalgamalg #6                              ])),And(And(In(i_category, [Men                                               ,Music                                             ,Women                                             ]),In(i_class, [accessories                                       ,classical                                         ,fragrances                                        ,pants                                             ])),In(i_brand, [amalgimporto #9                                   ,edu packscholar #9                                ,exportiimporto #9                                 ,importoamalg #9                                   ]))), IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand:string,i_class:string,i_category:string,i_manufact_id:int>

(2) FilterExecTransformer
Input [5]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, i_manufact_id#5]
Arguments: ((((i_category#4 IN (Books                                             ,Children                                          ,Electronics                                       ) AND i_class#3 IN (personal                                          ,portable                                          ,reference                                         ,self-help                                         )) AND i_brand#2 IN (scholaramalgamalg #7                             ,scholaramalgamalg #8                              ,exportiunivamalg #6                               ,scholaramalgamalg #6                              )) OR ((i_category#4 IN (Women                                             ,Music                                             ,Men                                               ) AND i_class#3 IN (accessories                                       ,classical                                         ,fragrances                                        ,pants                                             )) AND i_brand#2 IN (amalgimporto #9                                   ,edu packscholar #9                                ,exportiimporto #9                                 ,importoamalg #9                                   ))) AND isnotnull(i_item_sk#1))

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

(4) FileSourceScanExecTransformer parquet spark_catalog.default.store_sales
Output [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#13), dynamicpruningexpression(ss_sold_date_sk#13 IN dynamicpruning#14)]
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)>

(5) FilterExecTransformer
Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]
Arguments: (isnotnull(ss_item_sk#10) AND isnotnull(ss_store_sk#11))

(6) WholeStageCodegenTransformer (2)
Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]
Arguments: false

(7) ColumnarBroadcastExchange
Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(8) InputAdapter
Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]

(9) InputIteratorTransformer
Input [4]: [ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]

(10) BroadcastHashJoinExecTransformer
Left keys [1]: [i_item_sk#1]
Right keys [1]: [ss_item_sk#10]
Join type: Inner
Join condition: None

(11) ProjectExecTransformer
Output [4]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]
Input [6]: [i_item_sk#1, i_manufact_id#5, ss_item_sk#10, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13]

(12) ReusedExchange [Reuses operator id: 50]
Output [2]: [d_date_sk#15, d_qoy#16]

(13) InputAdapter
Input [2]: [d_date_sk#15, d_qoy#16]

(14) InputIteratorTransformer
Input [2]: [d_date_sk#15, d_qoy#16]

(15) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_sold_date_sk#13]
Right keys [1]: [d_date_sk#15]
Join type: Inner
Join condition: None

(16) ProjectExecTransformer
Output [4]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, d_qoy#16]
Input [6]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, ss_sold_date_sk#13, d_date_sk#15, d_qoy#16]

(17) FileSourceScanExecTransformer parquet spark_catalog.default.store
Output [1]: [s_store_sk#17]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int>

(18) FilterExecTransformer
Input [1]: [s_store_sk#17]
Arguments: isnotnull(s_store_sk#17)

(19) WholeStageCodegenTransformer (4)
Input [1]: [s_store_sk#17]
Arguments: false

(20) ColumnarBroadcastExchange
Input [1]: [s_store_sk#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(21) InputAdapter
Input [1]: [s_store_sk#17]

(22) InputIteratorTransformer
Input [1]: [s_store_sk#17]

(23) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_store_sk#11]
Right keys [1]: [s_store_sk#17]
Join type: Inner
Join condition: None

(24) ProjectExecTransformer
Output [3]: [i_manufact_id#5, d_qoy#16, UnscaledValue(ss_sales_price#12) AS _pre_1#18]
Input [5]: [i_manufact_id#5, ss_store_sk#11, ss_sales_price#12, d_qoy#16, s_store_sk#17]

(25) FlushableHashAggregateExecTransformer
Input [3]: [i_manufact_id#5, d_qoy#16, _pre_1#18]
Keys [2]: [i_manufact_id#5, d_qoy#16]
Functions [1]: [partial_sum(_pre_1#18)]
Aggregate Attributes [1]: [sum#19]
Results [3]: [i_manufact_id#5, d_qoy#16, sum#20]

(26) ProjectExecTransformer
Output [4]: [hash(i_manufact_id#5, d_qoy#16, 42) AS hash_partition_key#21, i_manufact_id#5, d_qoy#16, sum#20]
Input [3]: [i_manufact_id#5, d_qoy#16, sum#20]

(27) WholeStageCodegenTransformer (5)
Input [4]: [hash_partition_key#21, i_manufact_id#5, d_qoy#16, sum#20]
Arguments: false

(28) VeloxResizeBatches
Input [4]: [hash_partition_key#21, i_manufact_id#5, d_qoy#16, sum#20]
Arguments: 1024, 2147483647, 10485760

(29) ColumnarExchange
Input [4]: [hash_partition_key#21, i_manufact_id#5, d_qoy#16, sum#20]
Arguments: hashpartitioning(i_manufact_id#5, d_qoy#16, 1), ENSURE_REQUIREMENTS, [i_manufact_id#5, d_qoy#16, sum#20], [plan_id=3], [shuffle_writer_type=hash]

(30) InputAdapter
Input [3]: [i_manufact_id#5, d_qoy#16, sum#20]

(31) InputIteratorTransformer
Input [3]: [i_manufact_id#5, d_qoy#16, sum#20]

(32) RegularHashAggregateExecTransformer
Input [3]: [i_manufact_id#5, d_qoy#16, sum#20]
Keys [2]: [i_manufact_id#5, d_qoy#16]
Functions [1]: [sum(UnscaledValue(ss_sales_price#12))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#12))#22]
Results [3]: [i_manufact_id#5, d_qoy#16, sum(UnscaledValue(ss_sales_price#12))#22]

(33) ProjectExecTransformer
Output [4]: [hash(i_manufact_id#5, 42) AS hash_partition_key#23, i_manufact_id#5, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#22,17,2) AS sum_sales#24, MakeDecimal(sum(UnscaledValue(ss_sales_price#12))#22,17,2) AS _w0#25]
Input [3]: [i_manufact_id#5, d_qoy#16, sum(UnscaledValue(ss_sales_price#12))#22]

(34) WholeStageCodegenTransformer (6)
Input [4]: [hash_partition_key#23, i_manufact_id#5, sum_sales#24, _w0#25]
Arguments: false

(35) VeloxResizeBatches
Input [4]: [hash_partition_key#23, i_manufact_id#5, sum_sales#24, _w0#25]
Arguments: 1024, 2147483647, 10485760

(36) ColumnarExchange
Input [4]: [hash_partition_key#23, i_manufact_id#5, sum_sales#24, _w0#25]
Arguments: hashpartitioning(i_manufact_id#5, 1), ENSURE_REQUIREMENTS, [i_manufact_id#5, sum_sales#24, _w0#25], [plan_id=4], [shuffle_writer_type=hash]

(37) InputAdapter
Input [3]: [i_manufact_id#5, sum_sales#24, _w0#25]

(38) InputIteratorTransformer
Input [3]: [i_manufact_id#5, sum_sales#24, _w0#25]

(39) SortExecTransformer
Input [3]: [i_manufact_id#5, sum_sales#24, _w0#25]
Arguments: [i_manufact_id#5 ASC NULLS FIRST], false, 0

(40) WindowExecTransformer
Input [3]: [i_manufact_id#5, sum_sales#24, _w0#25]
Arguments: [avg(_w0#25) windowspecdefinition(i_manufact_id#5, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_quarterly_sales#26], [i_manufact_id#5]

(41) FilterExecTransformer
Input [4]: [i_manufact_id#5, sum_sales#24, _w0#25, avg_quarterly_sales#26]
Arguments: CASE WHEN (avg_quarterly_sales#26 > 0.000000) THEN ((abs((sum_sales#24 - avg_quarterly_sales#26)) / avg_quarterly_sales#26) > 0.1000000000000000) ELSE false END

(42) ProjectExecTransformer
Output [3]: [i_manufact_id#5, sum_sales#24, avg_quarterly_sales#26]
Input [4]: [i_manufact_id#5, sum_sales#24, _w0#25, avg_quarterly_sales#26]

(43) WholeStageCodegenTransformer (7)
Input [3]: [i_manufact_id#5, sum_sales#24, avg_quarterly_sales#26]
Arguments: false

(44) TakeOrderedAndProjectExecTransformer
Input [3]: [i_manufact_id#5, sum_sales#24, avg_quarterly_sales#26]
Arguments: 100, [avg_quarterly_sales#26 ASC NULLS FIRST, sum_sales#24 ASC NULLS FIRST, i_manufact_id#5 ASC NULLS FIRST], [i_manufact_id#5, sum_sales#24, avg_quarterly_sales#26], 0

(45) VeloxColumnarToRow
Input [3]: [i_manufact_id#5, sum_sales#24, avg_quarterly_sales#26]

===== Subqueries =====

Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#13 IN dynamicpruning#14
ColumnarBroadcastExchange (50)
+- ^ ProjectExecTransformer (48)
   +- ^ FilterExecTransformer (47)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (46)


(46) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#15, d_month_seq#27, d_qoy#16]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/date_dim]
PushedFilters: [In(d_month_seq, [1200,1201,1202,1203,1204,1205,1206,1207,1208,1209,1210,1211]), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int,d_qoy:int>

(47) FilterExecTransformer
Input [3]: [d_date_sk#15, d_month_seq#27, d_qoy#16]
Arguments: (d_month_seq#27 INSET 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211 AND isnotnull(d_date_sk#15))

(48) ProjectExecTransformer
Output [2]: [d_date_sk#15, d_qoy#16]
Input [3]: [d_date_sk#15, d_month_seq#27, d_qoy#16]

(49) WholeStageCodegenTransformer (1)
Input [2]: [d_date_sk#15, d_qoy#16]
Arguments: false

(50) ColumnarBroadcastExchange
Input [2]: [d_date_sk#15, d_qoy#16]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


