== Physical Plan ==
TakeOrderedAndProject (23)
+- * HashAggregate (22)
   +- Exchange (21)
      +- * HashAggregate (20)
         +- * Expand (19)
            +- * Project (18)
               +- * BroadcastHashJoin Inner BuildRight (17)
                  :- * Project (12)
                  :  +- * BroadcastHashJoin Inner BuildRight (11)
                  :     :- * Project (6)
                  :     :  +- * BroadcastHashJoin Inner BuildRight (5)
                  :     :     :- * Filter (3)
                  :     :     :  +- * ColumnarToRow (2)
                  :     :     :     +- Scan parquet spark_catalog.default.inventory (1)
                  :     :     +- ReusedExchange (4)
                  :     +- BroadcastExchange (10)
                  :        +- * Filter (9)
                  :           +- * ColumnarToRow (8)
                  :              +- Scan parquet spark_catalog.default.item (7)
                  +- BroadcastExchange (16)
                     +- * Filter (15)
                        +- * ColumnarToRow (14)
                           +- Scan parquet spark_catalog.default.warehouse (13)


(1) Scan 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) ColumnarToRow [codegen id : 4]
Input [4]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4]

(3) Filter [codegen id : 4]
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))

(4) ReusedExchange [Reuses operator id: 28]
Output [1]: [d_date_sk#6]

(5) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [inv_date_sk#4]
Right keys [1]: [d_date_sk#6]
Join type: Inner
Join condition: None

(6) Project [codegen id : 4]
Output [3]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3]
Input [5]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, d_date_sk#6]

(7) Scan parquet spark_catalog.default.item
Output [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
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>

(8) ColumnarToRow [codegen id : 2]
Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]

(9) Filter [codegen id : 2]
Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Condition : isnotnull(i_item_sk#7)

(10) BroadcastExchange
Input [5]: [i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(11) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [inv_item_sk#1]
Right keys [1]: [i_item_sk#7]
Join type: Inner
Join condition: None

(12) Project [codegen id : 4]
Output [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11]
Input [8]: [inv_item_sk#1, inv_warehouse_sk#2, inv_quantity_on_hand#3, i_item_sk#7, i_brand#8, i_class#9, i_category#10, i_product_name#11]

(13) Scan parquet spark_catalog.default.warehouse
Output [1]: [w_warehouse_sk#12]
Batched: true
Location [not included in comparison]/{warehouse_dir}/warehouse]
PushedFilters: [IsNotNull(w_warehouse_sk)]
ReadSchema: struct<w_warehouse_sk:int>

(14) ColumnarToRow [codegen id : 3]
Input [1]: [w_warehouse_sk#12]

(15) Filter [codegen id : 3]
Input [1]: [w_warehouse_sk#12]
Condition : isnotnull(w_warehouse_sk#12)

(16) BroadcastExchange
Input [1]: [w_warehouse_sk#12]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(17) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [inv_warehouse_sk#2]
Right keys [1]: [w_warehouse_sk#12]
Join type: Inner
Join condition: None

(18) Project [codegen id : 4]
Output [5]: [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10]
Input [7]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, i_brand#8, i_class#9, i_category#10, i_product_name#11, w_warehouse_sk#12]

(19) Expand [codegen id : 4]
Input [5]: [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10]
Arguments: [[inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, i_category#10, 0], [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, i_class#9, null, 1], [inv_quantity_on_hand#3, i_product_name#11, i_brand#8, null, null, 3], [inv_quantity_on_hand#3, i_product_name#11, null, null, null, 7], [inv_quantity_on_hand#3, null, null, null, null, 15]], [inv_quantity_on_hand#3, i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17]

(20) HashAggregate [codegen id : 4]
Input [6]: [inv_quantity_on_hand#3, i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17]
Keys [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17]
Functions [1]: [partial_avg(inv_quantity_on_hand#3)]
Aggregate Attributes [2]: [sum#18, count#19]
Results [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21]

(21) Exchange
Input [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21]
Arguments: hashpartitioning(i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, 5), ENSURE_REQUIREMENTS, [plan_id=3]

(22) HashAggregate [codegen id : 5]
Input [7]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17, sum#20, count#21]
Keys [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, spark_grouping_id#17]
Functions [1]: [avg(inv_quantity_on_hand#3)]
Aggregate Attributes [1]: [avg(inv_quantity_on_hand#3)#22]
Results [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, avg(inv_quantity_on_hand#3)#22 AS qoh#23]

(23) TakeOrderedAndProject
Input [5]: [i_product_name#13, i_brand#14, i_class#15, i_category#16, qoh#23]
Arguments: 100, [qoh#23 ASC NULLS FIRST, i_product_name#13 ASC NULLS FIRST, i_brand#14 ASC NULLS FIRST, i_class#15 ASC NULLS FIRST, i_category#16 ASC NULLS FIRST], [i_product_name#13, i_brand#14, i_class#15, i_category#16, qoh#23]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5
BroadcastExchange (28)
+- * Project (27)
   +- * Filter (26)
      +- * ColumnarToRow (25)
         +- Scan parquet spark_catalog.default.date_dim (24)


(24) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#6, d_month_seq#24]
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>

(25) ColumnarToRow [codegen id : 1]
Input [2]: [d_date_sk#6, d_month_seq#24]

(26) Filter [codegen id : 1]
Input [2]: [d_date_sk#6, d_month_seq#24]
Condition : (((isnotnull(d_month_seq#24) AND (d_month_seq#24 >= 1200)) AND (d_month_seq#24 <= 1211)) AND isnotnull(d_date_sk#6))

(27) Project [codegen id : 1]
Output [1]: [d_date_sk#6]
Input [2]: [d_date_sk#6, d_month_seq#24]

(28) BroadcastExchange
Input [1]: [d_date_sk#6]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]


