== Physical Plan ==
* CometColumnarToRow (26)
+- CometTakeOrderedAndProject (25)
   +- CometHashAggregate (24)
      +- CometColumnarExchange (23)
         +- * HashAggregate (22)
            +- * Project (21)
               +- * BroadcastHashJoin Inner BuildLeft (20)
                  :- BroadcastExchange (15)
                  :  +- * Project (14)
                  :     +- * BroadcastHashJoin Inner BuildRight (13)
                  :        :- * Project (11)
                  :        :  +- * BroadcastHashJoin Inner BuildRight (10)
                  :        :     :- * CometColumnarToRow (4)
                  :        :     :  +- CometProject (3)
                  :        :     :     +- CometFilter (2)
                  :        :     :        +- CometNativeScan parquet spark_catalog.default.item (1)
                  :        :     +- BroadcastExchange (9)
                  :        :        +- * Project (8)
                  :        :           +- * Filter (7)
                  :        :              +- * ColumnarToRow (6)
                  :        :                 +- Scan parquet spark_catalog.default.inventory (5)
                  :        +- ReusedExchange (12)
                  +- * CometColumnarToRow (19)
                     +- CometProject (18)
                        +- CometFilter (17)
                           +- CometNativeScan parquet spark_catalog.default.store_sales (16)


(1) CometNativeScan parquet spark_catalog.default.item
Output [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_current_price), GreaterThanOrEqual(i_current_price,62.00), LessThanOrEqual(i_current_price,92.00), In(i_manufact_id, [129,270,423,821]), IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string,i_item_desc:string,i_current_price:decimal(7,2),i_manufact_id:int>

(2) CometFilter
Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5]
Condition : ((((isnotnull(i_current_price#4) AND (i_current_price#4 >= 62.00)) AND (i_current_price#4 <= 92.00)) AND i_manufact_id#5 IN (129,270,821,423)) AND isnotnull(i_item_sk#1))

(3) CometProject
Input [5]: [i_item_sk#1, i_item_id#2, i_item_desc#3, i_current_price#4, i_manufact_id#5]
Arguments: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4], [i_item_sk#1, static_invoke(CharVarcharCodegenUtils.readSidePadding(i_item_id#2, 16)) AS i_item_id#6, i_item_desc#3, i_current_price#4]

(4) CometColumnarToRow [codegen id : 3]
Input [4]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4]

(5) Scan parquet spark_catalog.default.inventory
Output [3]: [inv_item_sk#7, inv_quantity_on_hand#8, inv_date_sk#9]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(inv_date_sk#9), dynamicpruningexpression(inv_date_sk#9 IN dynamicpruning#10)]
PushedFilters: [IsNotNull(inv_quantity_on_hand), GreaterThanOrEqual(inv_quantity_on_hand,100), LessThanOrEqual(inv_quantity_on_hand,500), IsNotNull(inv_item_sk)]
ReadSchema: struct<inv_item_sk:int,inv_quantity_on_hand:int>

(6) ColumnarToRow [codegen id : 1]
Input [3]: [inv_item_sk#7, inv_quantity_on_hand#8, inv_date_sk#9]

(7) Filter [codegen id : 1]
Input [3]: [inv_item_sk#7, inv_quantity_on_hand#8, inv_date_sk#9]
Condition : (((isnotnull(inv_quantity_on_hand#8) AND (inv_quantity_on_hand#8 >= 100)) AND (inv_quantity_on_hand#8 <= 500)) AND isnotnull(inv_item_sk#7))

(8) Project [codegen id : 1]
Output [2]: [inv_item_sk#7, inv_date_sk#9]
Input [3]: [inv_item_sk#7, inv_quantity_on_hand#8, inv_date_sk#9]

(9) BroadcastExchange
Input [2]: [inv_item_sk#7, inv_date_sk#9]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(10) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [i_item_sk#1]
Right keys [1]: [inv_item_sk#7]
Join type: Inner
Join condition: None

(11) Project [codegen id : 3]
Output [5]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4, inv_date_sk#9]
Input [6]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4, inv_item_sk#7, inv_date_sk#9]

(12) ReusedExchange [Reuses operator id: 31]
Output [1]: [d_date_sk#11]

(13) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [inv_date_sk#9]
Right keys [1]: [d_date_sk#11]
Join type: Inner
Join condition: None

(14) Project [codegen id : 3]
Output [4]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4]
Input [6]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4, inv_date_sk#9, d_date_sk#11]

(15) BroadcastExchange
Input [4]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(16) CometNativeScan parquet spark_catalog.default.store_sales
Output [2]: [ss_item_sk#12, ss_sold_date_sk#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store_sales]
PushedFilters: [IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int>

(17) CometFilter
Input [2]: [ss_item_sk#12, ss_sold_date_sk#13]
Condition : isnotnull(ss_item_sk#12)

(18) CometProject
Input [2]: [ss_item_sk#12, ss_sold_date_sk#13]
Arguments: [ss_item_sk#12], [ss_item_sk#12]

(19) CometColumnarToRow
Input [1]: [ss_item_sk#12]

(20) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [i_item_sk#1]
Right keys [1]: [ss_item_sk#12]
Join type: Inner
Join condition: None

(21) Project [codegen id : 4]
Output [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Input [5]: [i_item_sk#1, i_item_id#6, i_item_desc#3, i_current_price#4, ss_item_sk#12]

(22) HashAggregate [codegen id : 4]
Input [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Keys [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Functions: []
Aggregate Attributes: []
Results [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]

(23) CometColumnarExchange
Input [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Arguments: hashpartitioning(i_item_id#6, i_item_desc#3, i_current_price#4, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=3]

(24) CometHashAggregate
Input [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Keys [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Functions: []

(25) CometTakeOrderedAndProject
Input [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]
Arguments: TakeOrderedAndProject(limit=100, orderBy=[i_item_id#6 ASC NULLS FIRST], output=[i_item_id#6,i_item_desc#3,i_current_price#4]), [i_item_id#6, i_item_desc#3, i_current_price#4], 100, 0, [i_item_id#6 ASC NULLS FIRST], [i_item_id#6, i_item_desc#3, i_current_price#4]

(26) CometColumnarToRow [codegen id : 5]
Input [3]: [i_item_id#6, i_item_desc#3, i_current_price#4]

===== Subqueries =====

Subquery:1 Hosting operator id = 5 Hosting Expression = inv_date_sk#9 IN dynamicpruning#10
BroadcastExchange (31)
+- * CometColumnarToRow (30)
   +- CometProject (29)
      +- CometFilter (28)
         +- CometNativeScan parquet spark_catalog.default.date_dim (27)


(27) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#11, d_date#14]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date), GreaterThanOrEqual(d_date,2000-05-25), LessThanOrEqual(d_date,2000-07-24), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_date:date>

(28) CometFilter
Input [2]: [d_date_sk#11, d_date#14]
Condition : (((isnotnull(d_date#14) AND (d_date#14 >= 2000-05-25)) AND (d_date#14 <= 2000-07-24)) AND isnotnull(d_date_sk#11))

(29) CometProject
Input [2]: [d_date_sk#11, d_date#14]
Arguments: [d_date_sk#11], [d_date_sk#11]

(30) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#11]

(31) BroadcastExchange
Input [1]: [d_date_sk#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]


