== Physical Plan ==
TakeOrderedAndProject (31)
+- * Filter (30)
   +- Window (29)
      +- WindowGroupLimit (28)
         +- * Sort (27)
            +- Exchange (26)
               +- WindowGroupLimit (25)
                  +- * Sort (24)
                     +- * HashAggregate (23)
                        +- Exchange (22)
                           +- * HashAggregate (21)
                              +- * ColumnarToRow (20)
                                 +- CometExpand (19)
                                    +- CometProject (18)
                                       +- CometBroadcastHashJoin (17)
                                          :- CometProject (13)
                                          :  +- CometBroadcastHashJoin (12)
                                          :     :- CometProject (8)
                                          :     :  +- CometBroadcastHashJoin (7)
                                          :     :     :- CometFilter (2)
                                          :     :     :  +- CometScan parquet spark_catalog.default.store_sales (1)
                                          :     :     +- CometBroadcastExchange (6)
                                          :     :        +- CometProject (5)
                                          :     :           +- CometFilter (4)
                                          :     :              +- CometScan parquet spark_catalog.default.date_dim (3)
                                          :     +- CometBroadcastExchange (11)
                                          :        +- CometFilter (10)
                                          :           +- CometScan parquet spark_catalog.default.store (9)
                                          +- CometBroadcastExchange (16)
                                             +- CometFilter (15)
                                                +- CometScan parquet spark_catalog.default.item (14)


(1) CometScan parquet spark_catalog.default.store_sales
Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#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_store_sk), IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_store_sk:int,ss_quantity:int,ss_sales_price:decimal(7,2)>

(2) CometFilter
Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5]
Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1))

(3) CometScan parquet spark_catalog.default.date_dim
Output [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int,d_year:int,d_moy:int,d_qoy:int>

(4) CometFilter
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Condition : (((isnotnull(d_month_seq#8) AND (d_month_seq#8 >= 1200)) AND (d_month_seq#8 <= 1211)) AND isnotnull(d_date_sk#7))

(5) CometProject
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Arguments: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11], [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(6) CometBroadcastExchange
Input [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(7) CometBroadcastHashJoin
Left output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5]
Right output [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: [ss_sold_date_sk#5], [d_date_sk#7], Inner, BuildRight

(8) CometProject
Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5, d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11], [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11]

(9) CometScan parquet spark_catalog.default.store
Output [2]: [s_store_sk#12, s_store_id#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_store_id:string>

(10) CometFilter
Input [2]: [s_store_sk#12, s_store_id#13]
Condition : isnotnull(s_store_sk#12)

(11) CometBroadcastExchange
Input [2]: [s_store_sk#12, s_store_id#13]
Arguments: [s_store_sk#12, s_store_id#13]

(12) CometBroadcastHashJoin
Left output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11]
Right output [2]: [s_store_sk#12, s_store_id#13]
Arguments: [ss_store_sk#2], [s_store_sk#12], Inner, BuildRight

(13) CometProject
Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_sk#12, s_store_id#13]
Arguments: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#13], [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#13]

(14) CometScan parquet spark_catalog.default.item
Output [5]: [i_item_sk#14, i_brand#15, i_class#16, i_category#17, i_product_name#18]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand:string,i_class:string,i_category:string,i_product_name:string>

(15) CometFilter
Input [5]: [i_item_sk#14, i_brand#15, i_class#16, i_category#17, i_product_name#18]
Condition : isnotnull(i_item_sk#14)

(16) CometBroadcastExchange
Input [5]: [i_item_sk#14, i_brand#15, i_class#16, i_category#17, i_product_name#18]
Arguments: [i_item_sk#14, i_brand#15, i_class#16, i_category#17, i_product_name#18]

(17) CometBroadcastHashJoin
Left output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#13]
Right output [5]: [i_item_sk#14, i_brand#15, i_class#16, i_category#17, i_product_name#18]
Arguments: [ss_item_sk#1], [i_item_sk#14], Inner, BuildRight

(18) CometProject
Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#13, i_item_sk#14, i_brand#15, i_class#16, i_category#17, i_product_name#18]
Arguments: [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, d_qoy#11, d_moy#10, s_store_id#13], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, d_qoy#11, d_moy#10, s_store_id#13]

(19) CometExpand
Input [10]: [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, d_qoy#11, d_moy#10, s_store_id#13]
Arguments: [[ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, d_qoy#11, d_moy#10, s_store_id#13, 0], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, d_qoy#11, d_moy#10, null, 1], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, d_qoy#11, null, null, 3], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, d_year#9, null, null, null, 7], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, i_product_name#18, null, null, null, null, 15], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, i_brand#15, null, null, null, null, null, 31], [ss_quantity#3, ss_sales_price#4, i_category#17, i_class#16, null, null, null, null, null, null, 63], [ss_quantity#3, ss_sales_price#4, i_category#17, null, null, null, null, null, null, null, 127], [ss_quantity#3, ss_sales_price#4, null, null, null, null, null, null, null, null, 255]], [ss_quantity#3, ss_sales_price#4, i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27]

(20) ColumnarToRow [codegen id : 1]
Input [11]: [ss_quantity#3, ss_sales_price#4, i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27]

(21) HashAggregate [codegen id : 1]
Input [11]: [ss_quantity#3, ss_sales_price#4, i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27]
Keys [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27]
Functions [1]: [partial_sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))]
Aggregate Attributes [2]: [sum#28, isEmpty#29]
Results [11]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27, sum#30, isEmpty#31]

(22) Exchange
Input [11]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27, sum#30, isEmpty#31]
Arguments: hashpartitioning(i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27, 5), ENSURE_REQUIREMENTS, [plan_id=1]

(23) HashAggregate [codegen id : 2]
Input [11]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27, sum#30, isEmpty#31]
Keys [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, spark_grouping_id#27]
Functions [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))]
Aggregate Attributes [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#32]
Results [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))#32 AS sumsales#33]

(24) Sort [codegen id : 2]
Input [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33]
Arguments: [i_category#19 ASC NULLS FIRST, sumsales#33 DESC NULLS LAST], false, 0

(25) WindowGroupLimit
Input [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33]
Arguments: [i_category#19], [sumsales#33 DESC NULLS LAST], rank(sumsales#33), 100, Partial

(26) Exchange
Input [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33]
Arguments: hashpartitioning(i_category#19, 5), ENSURE_REQUIREMENTS, [plan_id=2]

(27) Sort [codegen id : 3]
Input [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33]
Arguments: [i_category#19 ASC NULLS FIRST, sumsales#33 DESC NULLS LAST], false, 0

(28) WindowGroupLimit
Input [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33]
Arguments: [i_category#19], [sumsales#33 DESC NULLS LAST], rank(sumsales#33), 100, Final

(29) Window
Input [9]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33]
Arguments: [rank(sumsales#33) windowspecdefinition(i_category#19, sumsales#33 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#34], [i_category#19], [sumsales#33 DESC NULLS LAST]

(30) Filter [codegen id : 4]
Input [10]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33, rk#34]
Condition : (rk#34 <= 100)

(31) TakeOrderedAndProject
Input [10]: [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33, rk#34]
Arguments: 100, [i_category#19 ASC NULLS FIRST, i_class#20 ASC NULLS FIRST, i_brand#21 ASC NULLS FIRST, i_product_name#22 ASC NULLS FIRST, d_year#23 ASC NULLS FIRST, d_qoy#24 ASC NULLS FIRST, d_moy#25 ASC NULLS FIRST, s_store_id#26 ASC NULLS FIRST, sumsales#33 ASC NULLS FIRST, rk#34 ASC NULLS FIRST], [i_category#19, i_class#20, i_brand#21, i_product_name#22, d_year#23, d_qoy#24, d_moy#25, s_store_id#26, sumsales#33, rk#34]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
BroadcastExchange (36)
+- * ColumnarToRow (35)
   +- CometProject (34)
      +- CometFilter (33)
         +- CometScan parquet spark_catalog.default.date_dim (32)


(32) CometScan parquet spark_catalog.default.date_dim
Output [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int,d_year:int,d_moy:int,d_qoy:int>

(33) CometFilter
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Condition : (((isnotnull(d_month_seq#8) AND (d_month_seq#8 >= 1200)) AND (d_month_seq#8 <= 1211)) AND isnotnull(d_date_sk#7))

(34) CometProject
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Arguments: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11], [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(35) ColumnarToRow [codegen id : 1]
Input [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(36) BroadcastExchange
Input [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]


