== Physical Plan ==
VeloxColumnarToRow (47)
+- TakeOrderedAndProjectExecTransformer (46)
   +- ^ ProjectExecTransformer (44)
      +- ^ WindowExecTransformer (43)
         +- ^ SortExecTransformer (42)
            +- ^ InputIteratorTransformer (41)
               +- ColumnarExchange (39)
                  +- VeloxResizeBatches (38)
                     +- ^ ProjectExecTransformer (36)
                        +- ^ ProjectExecTransformer (35)
                           +- ^ RegularHashAggregateExecTransformer (34)
                              +- ^ InputIteratorTransformer (33)
                                 +- ColumnarExchange (31)
                                    +- VeloxResizeBatches (30)
                                       +- ^ ProjectExecTransformer (28)
                                          +- ^ FlushableHashAggregateExecTransformer (27)
                                             +- ^ ProjectExecTransformer (26)
                                                +- ^ ExpandExecTransformer (25)
                                                   +- ^ ProjectExecTransformer (24)
                                                      +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (23)
                                                         :- ^ ProjectExecTransformer (15)
                                                         :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (14)
                                                         :     :- ^ ProjectExecTransformer (7)
                                                         :     :  +- ^ BroadcastHashJoinExecTransformer Inner BuildRight (6)
                                                         :     :     :- ^ FilterExecTransformer (2)
                                                         :     :     :  +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store_sales (1)
                                                         :     :     +- ^ InputIteratorTransformer (5)
                                                         :     :        +- ReusedExchange (3)
                                                         :     +- ^ InputIteratorTransformer (13)
                                                         :        +- ColumnarBroadcastExchange (11)
                                                         :           +- ^ FilterExecTransformer (9)
                                                         :              +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.item (8)
                                                         +- ^ InputIteratorTransformer (22)
                                                            +- ColumnarBroadcastExchange (20)
                                                               +- ^ ProjectExecTransformer (18)
                                                                  +- ^ FilterExecTransformer (17)
                                                                     +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.store (16)


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

(2) FilterExecTransformer
Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5]
Arguments: (isnotnull(ss_item_sk#1) AND isnotnull(ss_store_sk#2))

(3) ReusedExchange [Reuses operator id: 52]
Output [1]: [d_date_sk#7]

(4) InputAdapter
Input [1]: [d_date_sk#7]

(5) InputIteratorTransformer
Input [1]: [d_date_sk#7]

(6) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_sold_date_sk#5]
Right keys [1]: [d_date_sk#7]
Join type: Inner
Join condition: None

(7) ProjectExecTransformer
Output [4]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4]
Input [6]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, ss_sold_date_sk#5, d_date_sk#7]

(8) FileSourceScanExecTransformer parquet spark_catalog.default.item
Output [3]: [i_item_sk#8, i_class#9, i_category#10]
Batched: true
Location: InMemoryFileIndex [{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_class:string,i_category:string>

(9) FilterExecTransformer
Input [3]: [i_item_sk#8, i_class#9, i_category#10]
Arguments: isnotnull(i_item_sk#8)

(10) WholeStageCodegenTransformer (3)
Input [3]: [i_item_sk#8, i_class#9, i_category#10]
Arguments: false

(11) ColumnarBroadcastExchange
Input [3]: [i_item_sk#8, i_class#9, i_category#10]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(12) InputAdapter
Input [3]: [i_item_sk#8, i_class#9, i_category#10]

(13) InputIteratorTransformer
Input [3]: [i_item_sk#8, i_class#9, i_category#10]

(14) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#8]
Join type: Inner
Join condition: None

(15) ProjectExecTransformer
Output [5]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10]
Input [7]: [ss_item_sk#1, ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_item_sk#8, i_class#9, i_category#10]

(16) FileSourceScanExecTransformer parquet spark_catalog.default.store
Output [2]: [s_store_sk#11, s_state#12]
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>

(17) FilterExecTransformer
Input [2]: [s_store_sk#11, s_state#12]
Arguments: ((isnotnull(s_state#12) AND (s_state#12 = TN)) AND isnotnull(s_store_sk#11))

(18) ProjectExecTransformer
Output [1]: [s_store_sk#11]
Input [2]: [s_store_sk#11, s_state#12]

(19) WholeStageCodegenTransformer (4)
Input [1]: [s_store_sk#11]
Arguments: false

(20) ColumnarBroadcastExchange
Input [1]: [s_store_sk#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(21) InputAdapter
Input [1]: [s_store_sk#11]

(22) InputIteratorTransformer
Input [1]: [s_store_sk#11]

(23) BroadcastHashJoinExecTransformer
Left keys [1]: [ss_store_sk#2]
Right keys [1]: [s_store_sk#11]
Join type: Inner
Join condition: None

(24) ProjectExecTransformer
Output [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9]
Input [6]: [ss_store_sk#2, ss_ext_sales_price#3, ss_net_profit#4, i_class#9, i_category#10, s_store_sk#11]

(25) ExpandExecTransformer
Input [4]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9]
Arguments: [[ss_ext_sales_price#3, ss_net_profit#4, i_category#10, i_class#9, 0], [ss_ext_sales_price#3, ss_net_profit#4, i_category#10, null, 1], [ss_ext_sales_price#3, ss_net_profit#4, null, null, 3]], [ss_ext_sales_price#3, ss_net_profit#4, i_category#13, i_class#14, spark_grouping_id#15]

(26) ProjectExecTransformer
Output [5]: [i_category#13, i_class#14, spark_grouping_id#15, UnscaledValue(ss_net_profit#4) AS _pre_1#16, UnscaledValue(ss_ext_sales_price#3) AS _pre_2#17]
Input [5]: [ss_ext_sales_price#3, ss_net_profit#4, i_category#13, i_class#14, spark_grouping_id#15]

(27) FlushableHashAggregateExecTransformer
Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, _pre_1#16, _pre_2#17]
Keys [3]: [i_category#13, i_class#14, spark_grouping_id#15]
Functions [2]: [partial_sum(_pre_1#16), partial_sum(_pre_2#17)]
Aggregate Attributes [2]: [sum#18, sum#19]
Results [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]

(28) ProjectExecTransformer
Output [6]: [hash(i_category#13, i_class#14, spark_grouping_id#15, 42) AS hash_partition_key#22, i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]
Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]

(29) WholeStageCodegenTransformer (5)
Input [6]: [hash_partition_key#22, i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]
Arguments: false

(30) VeloxResizeBatches
Input [6]: [hash_partition_key#22, i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]
Arguments: 1024, 2147483647, 10485760

(31) ColumnarExchange
Input [6]: [hash_partition_key#22, i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]
Arguments: hashpartitioning(i_category#13, i_class#14, spark_grouping_id#15, 1), ENSURE_REQUIREMENTS, [i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21], [plan_id=3], [shuffle_writer_type=hash]

(32) InputAdapter
Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]

(33) InputIteratorTransformer
Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]

(34) RegularHashAggregateExecTransformer
Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum#20, sum#21]
Keys [3]: [i_category#13, i_class#14, spark_grouping_id#15]
Functions [2]: [sum(UnscaledValue(ss_net_profit#4)), sum(UnscaledValue(ss_ext_sales_price#3))]
Aggregate Attributes [2]: [sum(UnscaledValue(ss_net_profit#4))#23, sum(UnscaledValue(ss_ext_sales_price#3))#24]
Results [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum(UnscaledValue(ss_net_profit#4))#23, sum(UnscaledValue(ss_ext_sales_price#3))#24]

(35) ProjectExecTransformer
Output [7]: [(MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#23,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#24,17,2)) AS gross_margin#25, i_category#13, i_class#14, (cast((shiftright(spark_grouping_id#15, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint)) AS lochierarchy#26, (MakeDecimal(sum(UnscaledValue(ss_net_profit#4))#23,17,2) / MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#3))#24,17,2)) AS _w0#27, (cast((shiftright(spark_grouping_id#15, 1) & 1) as tinyint) + cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint)) AS _w1#28, CASE WHEN (cast((shiftright(spark_grouping_id#15, 0) & 1) as tinyint) = 0) THEN i_category#13 END AS _w2#29]
Input [5]: [i_category#13, i_class#14, spark_grouping_id#15, sum(UnscaledValue(ss_net_profit#4))#23, sum(UnscaledValue(ss_ext_sales_price#3))#24]

(36) ProjectExecTransformer
Output [8]: [hash(_w1#28, _w2#29, 42) AS hash_partition_key#30, gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]
Input [7]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]

(37) WholeStageCodegenTransformer (6)
Input [8]: [hash_partition_key#30, gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]
Arguments: false

(38) VeloxResizeBatches
Input [8]: [hash_partition_key#30, gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]
Arguments: 1024, 2147483647, 10485760

(39) ColumnarExchange
Input [8]: [hash_partition_key#30, gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]
Arguments: hashpartitioning(_w1#28, _w2#29, 1), ENSURE_REQUIREMENTS, [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29], [plan_id=4], [shuffle_writer_type=hash]

(40) InputAdapter
Input [7]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]

(41) InputIteratorTransformer
Input [7]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]

(42) SortExecTransformer
Input [7]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]
Arguments: [_w1#28 ASC NULLS FIRST, _w2#29 ASC NULLS FIRST, _w0#27 ASC NULLS FIRST], false, 0

(43) WindowExecTransformer
Input [7]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29]
Arguments: [rank(_w0#27) windowspecdefinition(_w1#28, _w2#29, _w0#27 ASC NULLS FIRST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#31], [_w1#28, _w2#29], [_w0#27 ASC NULLS FIRST]

(44) ProjectExecTransformer
Output [6]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, rank_within_parent#31, CASE WHEN (lochierarchy#26 = 0) THEN i_category#13 END AS _pre_3#32]
Input [8]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, _w0#27, _w1#28, _w2#29, rank_within_parent#31]

(45) WholeStageCodegenTransformer (7)
Input [6]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, rank_within_parent#31, _pre_3#32]
Arguments: false

(46) TakeOrderedAndProjectExecTransformer
Input [6]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, rank_within_parent#31, _pre_3#32]
Arguments: 100, [lochierarchy#26 DESC NULLS LAST, _pre_3#32 ASC NULLS FIRST, rank_within_parent#31 ASC NULLS FIRST], [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, rank_within_parent#31], 0

(47) VeloxColumnarToRow
Input [5]: [gross_margin#25, i_category#13, i_class#14, lochierarchy#26, rank_within_parent#31]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
ColumnarBroadcastExchange (52)
+- ^ ProjectExecTransformer (50)
   +- ^ FilterExecTransformer (49)
      +- ^ FileSourceScanExecTransformer parquet spark_catalog.default.date_dim (48)


(48) FileSourceScanExecTransformer parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#7, d_year#33]
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>

(49) FilterExecTransformer
Input [2]: [d_date_sk#7, d_year#33]
Arguments: ((isnotnull(d_year#33) AND (d_year#33 = 2001)) AND isnotnull(d_date_sk#7))

(50) ProjectExecTransformer
Output [1]: [d_date_sk#7]
Input [2]: [d_date_sk#7, d_year#33]

(51) WholeStageCodegenTransformer (1)
Input [1]: [d_date_sk#7]
Arguments: false

(52) ColumnarBroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


