== Physical Plan ==
TakeOrderedAndProject (25)
+- * HashAggregate (24)
   +- * CometColumnarToRow (23)
      +- CometColumnarExchange (22)
         +- * HashAggregate (21)
            +- * CometColumnarToRow (20)
               +- CometExpand (19)
                  +- CometProject (18)
                     +- CometBroadcastHashJoin (17)
                        :- CometProject (13)
                        :  +- CometBroadcastHashJoin (12)
                        :     :- CometProject (8)
                        :     :  +- CometBroadcastHashJoin (7)
                        :     :     :- CometFilter (2)
                        :     :     :  +- CometScan parquet spark_catalog.default.inventory (1)
                        :     :     +- CometBroadcastExchange (6)
                        :     :        +- CometProject (5)
                        :     :           +- CometFilter (4)
                        :     :              +- CometScan parquet spark_catalog.default.date_dim (3)
                        :     +- CometBroadcastExchange (11)
                        :        +- CometFilter (10)
                        :           +- CometScan parquet spark_catalog.default.item (9)
                        +- CometBroadcastExchange (16)
                           +- CometFilter (15)
                              +- CometScan parquet spark_catalog.default.warehouse (14)


(1) CometScan parquet spark_catalog.default.inventory
Output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(inv_date_sk#4), dynamicpruningexpression(inv_date_sk#4 IN dynamicpruning#5)]
PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)]
ReadSchema: struct<inv_item_sk:int,inv_warehouse_sk:int,inv_quantity_on_hand:int>

(2) CometFilter
Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4]
Condition : (isnotnull(inv_item_sk#1) AND isnotnull(inv_warehouse_sk#2))

(3) CometScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#6, d_month_seq#7]
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>

(4) CometFilter
Input [2]: [d_date_sk#6, d_month_seq#7]
Condition : (((isnotnull(d_month_seq#7) AND (d_month_seq#7 >= 1200)) AND (d_month_seq#7 <= 1211)) AND isnotnull(d_date_sk#6))

(5) CometProject
Input [2]: [d_date_sk#6, d_month_seq#7]
Arguments: [d_date_sk#6], [d_date_sk#6]

(6) CometBroadcastExchange
Input [1]: [d_date_sk#6]
Arguments: [d_date_sk#6]

(7) CometBroadcastHashJoin
Left output [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4]
Right output [1]: [d_date_sk#6]
Arguments: [inv_date_sk#4], [d_date_sk#6], Inner, BuildRight

(8) CometProject
Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, d_date_sk#6]
Arguments: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3], [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3]

(9) CometScan parquet spark_catalog.default.item
Output [5]: [i_item_sk#8, i_brand#9, i_class#10, i_category#11, i_product_name#12]
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>

(10) CometFilter
Input [5]: [i_item_sk#8, i_brand#9, i_class#10, i_category#11, i_product_name#12]
Condition : isnotnull(i_item_sk#8)

(11) CometBroadcastExchange
Input [5]: [i_item_sk#8, i_brand#9, i_class#10, i_category#11, i_product_name#12]
Arguments: [i_item_sk#8, i_brand#9, i_class#10, i_category#11, i_product_name#12]

(12) CometBroadcastHashJoin
Left output [3]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3]
Right output [5]: [i_item_sk#8, i_brand#9, i_class#10, i_category#11, i_product_name#12]
Arguments: [inv_item_sk#1], [i_item_sk#8], Inner, BuildRight

(13) CometProject
Input [8]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, i_item_sk#8, i_brand#9, i_class#10, i_category#11, i_product_name#12]
Arguments: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#9, i_class#10, i_category#11, i_product_name#12], [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#9, i_class#10, i_category#11, i_product_name#12]

(14) CometScan parquet spark_catalog.default.warehouse
Output [1]: [w_warehouse_sk#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/warehouse]
PushedFilters: [IsNotNull(w_warehouse_sk)]
ReadSchema: struct<w_warehouse_sk:int>

(15) CometFilter
Input [1]: [w_warehouse_sk#13]
Condition : isnotnull(w_warehouse_sk#13)

(16) CometBroadcastExchange
Input [1]: [w_warehouse_sk#13]
Arguments: [w_warehouse_sk#13]

(17) CometBroadcastHashJoin
Left output [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#9, i_class#10, i_category#11, i_product_name#12]
Right output [1]: [w_warehouse_sk#13]
Arguments: [inv_warehouse_sk#2], [w_warehouse_sk#13], Inner, BuildRight

(18) CometProject
Input [7]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#9, i_class#10, i_category#11, i_product_name#12, w_warehouse_sk#13]
Arguments: [inv_quantity_on_hand#3, i_product_name#12, i_brand#9, i_class#10, i_category#11], [inv_quantity_on_hand#3, i_product_name#12, i_brand#9, i_class#10, i_category#11]

(19) CometExpand
Input [5]: [inv_quantity_on_hand#3, i_product_name#12, i_brand#9, i_class#10, i_category#11]
Arguments: [[inv_quantity_on_hand#3, i_product_name#12, i_brand#9, i_class#10, i_category#11, 0], [inv_quantity_on_hand#3, i_product_name#12, i_brand#9, i_class#10, null, 1], [inv_quantity_on_hand#3, i_product_name#12, i_brand#9, null, null, 3], [inv_quantity_on_hand#3, i_product_name#12, null, null, null, 7], [inv_quantity_on_hand#3, null, null, null, null, 15]], [inv_quantity_on_hand#3, i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]

(20) CometColumnarToRow [codegen id : 1]
Input [6]: [inv_quantity_on_hand#3, i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]

(21) HashAggregate [codegen id : 1]
Input [6]: [inv_quantity_on_hand#3, i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
Keys [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
Functions [1]: [partial_avg(inv_quantity_on_hand#3)]
Aggregate Attributes [2]: [sum#19, count#20]
Results [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]

(22) CometColumnarExchange
Input [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]
Arguments: hashpartitioning(i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(23) CometColumnarToRow [codegen id : 2]
Input [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]

(24) HashAggregate [codegen id : 2]
Input [7]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18, sum#21, count#22]
Keys [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, spark_grouping_id#18]
Functions [1]: [avg(inv_quantity_on_hand#3)]
Aggregate Attributes [1]: [avg(inv_quantity_on_hand#3)#23]
Results [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, avg(inv_quantity_on_hand#3)#23 AS qoh#24]

(25) TakeOrderedAndProject
Input [5]: [i_product_name#14, i_brand#15, i_class#16, i_category#17, qoh#24]
Arguments: 100, [qoh#24 ASC NULLS FIRST, i_product_name#14 ASC NULLS FIRST, i_brand#15 ASC NULLS FIRST, i_class#16 ASC NULLS FIRST, i_category#17 ASC NULLS FIRST], [i_product_name#14, i_brand#15, i_class#16, i_category#17, qoh#24]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5
BroadcastExchange (30)
+- * CometColumnarToRow (29)
   +- CometProject (28)
      +- CometFilter (27)
         +- CometScan parquet spark_catalog.default.date_dim (26)


(26) CometScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#6, d_month_seq#7]
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>

(27) CometFilter
Input [2]: [d_date_sk#6, d_month_seq#7]
Condition : (((isnotnull(d_month_seq#7) AND (d_month_seq#7 >= 1200)) AND (d_month_seq#7 <= 1211)) AND isnotnull(d_date_sk#6))

(28) CometProject
Input [2]: [d_date_sk#6, d_month_seq#7]
Arguments: [d_date_sk#6], [d_date_sk#6]

(29) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#6]

(30) BroadcastExchange
Input [1]: [d_date_sk#6]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]


