== Physical Plan ==
TakeOrderedAndProject (53)
+- * Project (52)
   +- * BroadcastHashJoin Inner BuildRight (51)
      :- * Project (35)
      :  +- * BroadcastHashJoin Inner BuildRight (34)
      :     :- * Filter (18)
      :     :  +- * HashAggregate (17)
      :     :     +- * CometColumnarToRow (16)
      :     :        +- CometColumnarExchange (15)
      :     :           +- * HashAggregate (14)
      :     :              +- * Project (13)
      :     :                 +- * BroadcastHashJoin Inner BuildRight (12)
      :     :                    :- * Project (10)
      :     :                    :  +- * BroadcastHashJoin Inner BuildRight (9)
      :     :                    :     :- * Filter (3)
      :     :                    :     :  +- * ColumnarToRow (2)
      :     :                    :     :     +- Scan parquet spark_catalog.default.store_sales (1)
      :     :                    :     +- BroadcastExchange (8)
      :     :                    :        +- * CometColumnarToRow (7)
      :     :                    :           +- CometProject (6)
      :     :                    :              +- CometFilter (5)
      :     :                    :                 +- CometNativeScan parquet spark_catalog.default.item (4)
      :     :                    +- ReusedExchange (11)
      :     +- BroadcastExchange (33)
      :        +- * Filter (32)
      :           +- * HashAggregate (31)
      :              +- * CometColumnarToRow (30)
      :                 +- CometColumnarExchange (29)
      :                    +- * HashAggregate (28)
      :                       +- * Project (27)
      :                          +- * BroadcastHashJoin Inner BuildRight (26)
      :                             :- * Project (24)
      :                             :  +- * BroadcastHashJoin Inner BuildRight (23)
      :                             :     :- * Filter (21)
      :                             :     :  +- * ColumnarToRow (20)
      :                             :     :     +- Scan parquet spark_catalog.default.catalog_sales (19)
      :                             :     +- ReusedExchange (22)
      :                             +- ReusedExchange (25)
      +- BroadcastExchange (50)
         +- * Filter (49)
            +- * HashAggregate (48)
               +- * CometColumnarToRow (47)
                  +- CometColumnarExchange (46)
                     +- * HashAggregate (45)
                        +- * Project (44)
                           +- * BroadcastHashJoin Inner BuildRight (43)
                              :- * Project (41)
                              :  +- * BroadcastHashJoin Inner BuildRight (40)
                              :     :- * Filter (38)
                              :     :  +- * ColumnarToRow (37)
                              :     :     +- Scan parquet spark_catalog.default.web_sales (36)
                              :     +- ReusedExchange (39)
                              +- ReusedExchange (42)


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

(2) ColumnarToRow [codegen id : 3]
Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3]

(3) Filter [codegen id : 3]
Input [3]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3]
Condition : isnotnull(ss_item_sk#1)

(4) CometNativeScan parquet spark_catalog.default.item
Output [2]: [i_item_sk#5, i_item_id#6]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(5) CometFilter
Input [2]: [i_item_sk#5, i_item_id#6]
Condition : (isnotnull(i_item_sk#5) AND isnotnull(staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_item_id#6, 16, true, false, true)))

(6) CometProject
Input [2]: [i_item_sk#5, i_item_id#6]
Arguments: [i_item_sk#5, i_item_id#7], [i_item_sk#5, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_item_id#6, 16, true, false, true) AS i_item_id#7]

(7) CometColumnarToRow [codegen id : 1]
Input [2]: [i_item_sk#5, i_item_id#7]

(8) BroadcastExchange
Input [2]: [i_item_sk#5, i_item_id#7]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(9) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#5]
Join type: Inner
Join condition: None

(10) Project [codegen id : 3]
Output [3]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#7]
Input [5]: [ss_item_sk#1, ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_sk#5, i_item_id#7]

(11) ReusedExchange [Reuses operator id: 63]
Output [1]: [d_date_sk#8]

(12) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [ss_sold_date_sk#3]
Right keys [1]: [d_date_sk#8]
Join type: Inner
Join condition: None

(13) Project [codegen id : 3]
Output [2]: [ss_ext_sales_price#2, i_item_id#7]
Input [4]: [ss_ext_sales_price#2, ss_sold_date_sk#3, i_item_id#7, d_date_sk#8]

(14) HashAggregate [codegen id : 3]
Input [2]: [ss_ext_sales_price#2, i_item_id#7]
Keys [1]: [i_item_id#7]
Functions [1]: [partial_sum(UnscaledValue(ss_ext_sales_price#2))]
Aggregate Attributes [1]: [sum#9]
Results [2]: [i_item_id#7, sum#10]

(15) CometColumnarExchange
Input [2]: [i_item_id#7, sum#10]
Arguments: hashpartitioning(i_item_id#7, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(16) CometColumnarToRow [codegen id : 12]
Input [2]: [i_item_id#7, sum#10]

(17) HashAggregate [codegen id : 12]
Input [2]: [i_item_id#7, sum#10]
Keys [1]: [i_item_id#7]
Functions [1]: [sum(UnscaledValue(ss_ext_sales_price#2))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_ext_sales_price#2))#11]
Results [2]: [i_item_id#7 AS item_id#12, MakeDecimal(sum(UnscaledValue(ss_ext_sales_price#2))#11,17,2) AS ss_item_rev#13]

(18) Filter [codegen id : 12]
Input [2]: [item_id#12, ss_item_rev#13]
Condition : isnotnull(ss_item_rev#13)

(19) Scan parquet spark_catalog.default.catalog_sales
Output [3]: [cs_item_sk#14, cs_ext_sales_price#15, cs_sold_date_sk#16]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#16), dynamicpruningexpression(cs_sold_date_sk#16 IN dynamicpruning#17)]
PushedFilters: [IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_item_sk:int,cs_ext_sales_price:decimal(7,2)>

(20) ColumnarToRow [codegen id : 6]
Input [3]: [cs_item_sk#14, cs_ext_sales_price#15, cs_sold_date_sk#16]

(21) Filter [codegen id : 6]
Input [3]: [cs_item_sk#14, cs_ext_sales_price#15, cs_sold_date_sk#16]
Condition : isnotnull(cs_item_sk#14)

(22) ReusedExchange [Reuses operator id: 8]
Output [2]: [i_item_sk#18, i_item_id#19]

(23) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [cs_item_sk#14]
Right keys [1]: [i_item_sk#18]
Join type: Inner
Join condition: None

(24) Project [codegen id : 6]
Output [3]: [cs_ext_sales_price#15, cs_sold_date_sk#16, i_item_id#19]
Input [5]: [cs_item_sk#14, cs_ext_sales_price#15, cs_sold_date_sk#16, i_item_sk#18, i_item_id#19]

(25) ReusedExchange [Reuses operator id: 77]
Output [1]: [d_date_sk#20]

(26) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [cs_sold_date_sk#16]
Right keys [1]: [d_date_sk#20]
Join type: Inner
Join condition: None

(27) Project [codegen id : 6]
Output [2]: [cs_ext_sales_price#15, i_item_id#19]
Input [4]: [cs_ext_sales_price#15, cs_sold_date_sk#16, i_item_id#19, d_date_sk#20]

(28) HashAggregate [codegen id : 6]
Input [2]: [cs_ext_sales_price#15, i_item_id#19]
Keys [1]: [i_item_id#19]
Functions [1]: [partial_sum(UnscaledValue(cs_ext_sales_price#15))]
Aggregate Attributes [1]: [sum#21]
Results [2]: [i_item_id#19, sum#22]

(29) CometColumnarExchange
Input [2]: [i_item_id#19, sum#22]
Arguments: hashpartitioning(i_item_id#19, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=3]

(30) CometColumnarToRow [codegen id : 7]
Input [2]: [i_item_id#19, sum#22]

(31) HashAggregate [codegen id : 7]
Input [2]: [i_item_id#19, sum#22]
Keys [1]: [i_item_id#19]
Functions [1]: [sum(UnscaledValue(cs_ext_sales_price#15))]
Aggregate Attributes [1]: [sum(UnscaledValue(cs_ext_sales_price#15))#23]
Results [2]: [i_item_id#19 AS item_id#24, MakeDecimal(sum(UnscaledValue(cs_ext_sales_price#15))#23,17,2) AS cs_item_rev#25]

(32) Filter [codegen id : 7]
Input [2]: [item_id#24, cs_item_rev#25]
Condition : isnotnull(cs_item_rev#25)

(33) BroadcastExchange
Input [2]: [item_id#24, cs_item_rev#25]
Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=4]

(34) BroadcastHashJoin [codegen id : 12]
Left keys [1]: [item_id#12]
Right keys [1]: [item_id#24]
Join type: Inner
Join condition: ((((cast(ss_item_rev#13 as decimal(19,3)) >= (0.9 * cs_item_rev#25)) AND (cast(ss_item_rev#13 as decimal(20,3)) <= (1.1 * cs_item_rev#25))) AND (cast(cs_item_rev#25 as decimal(19,3)) >= (0.9 * ss_item_rev#13))) AND (cast(cs_item_rev#25 as decimal(20,3)) <= (1.1 * ss_item_rev#13)))

(35) Project [codegen id : 12]
Output [3]: [item_id#12, ss_item_rev#13, cs_item_rev#25]
Input [4]: [item_id#12, ss_item_rev#13, item_id#24, cs_item_rev#25]

(36) Scan parquet spark_catalog.default.web_sales
Output [3]: [ws_item_sk#26, ws_ext_sales_price#27, ws_sold_date_sk#28]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ws_sold_date_sk#28), dynamicpruningexpression(ws_sold_date_sk#28 IN dynamicpruning#17)]
PushedFilters: [IsNotNull(ws_item_sk)]
ReadSchema: struct<ws_item_sk:int,ws_ext_sales_price:decimal(7,2)>

(37) ColumnarToRow [codegen id : 10]
Input [3]: [ws_item_sk#26, ws_ext_sales_price#27, ws_sold_date_sk#28]

(38) Filter [codegen id : 10]
Input [3]: [ws_item_sk#26, ws_ext_sales_price#27, ws_sold_date_sk#28]
Condition : isnotnull(ws_item_sk#26)

(39) ReusedExchange [Reuses operator id: 8]
Output [2]: [i_item_sk#29, i_item_id#30]

(40) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [ws_item_sk#26]
Right keys [1]: [i_item_sk#29]
Join type: Inner
Join condition: None

(41) Project [codegen id : 10]
Output [3]: [ws_ext_sales_price#27, ws_sold_date_sk#28, i_item_id#30]
Input [5]: [ws_item_sk#26, ws_ext_sales_price#27, ws_sold_date_sk#28, i_item_sk#29, i_item_id#30]

(42) ReusedExchange [Reuses operator id: 77]
Output [1]: [d_date_sk#31]

(43) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [ws_sold_date_sk#28]
Right keys [1]: [d_date_sk#31]
Join type: Inner
Join condition: None

(44) Project [codegen id : 10]
Output [2]: [ws_ext_sales_price#27, i_item_id#30]
Input [4]: [ws_ext_sales_price#27, ws_sold_date_sk#28, i_item_id#30, d_date_sk#31]

(45) HashAggregate [codegen id : 10]
Input [2]: [ws_ext_sales_price#27, i_item_id#30]
Keys [1]: [i_item_id#30]
Functions [1]: [partial_sum(UnscaledValue(ws_ext_sales_price#27))]
Aggregate Attributes [1]: [sum#32]
Results [2]: [i_item_id#30, sum#33]

(46) CometColumnarExchange
Input [2]: [i_item_id#30, sum#33]
Arguments: hashpartitioning(i_item_id#30, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(47) CometColumnarToRow [codegen id : 11]
Input [2]: [i_item_id#30, sum#33]

(48) HashAggregate [codegen id : 11]
Input [2]: [i_item_id#30, sum#33]
Keys [1]: [i_item_id#30]
Functions [1]: [sum(UnscaledValue(ws_ext_sales_price#27))]
Aggregate Attributes [1]: [sum(UnscaledValue(ws_ext_sales_price#27))#34]
Results [2]: [i_item_id#30 AS item_id#35, MakeDecimal(sum(UnscaledValue(ws_ext_sales_price#27))#34,17,2) AS ws_item_rev#36]

(49) Filter [codegen id : 11]
Input [2]: [item_id#35, ws_item_rev#36]
Condition : isnotnull(ws_item_rev#36)

(50) BroadcastExchange
Input [2]: [item_id#35, ws_item_rev#36]
Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=6]

(51) BroadcastHashJoin [codegen id : 12]
Left keys [1]: [item_id#12]
Right keys [1]: [item_id#35]
Join type: Inner
Join condition: ((((((((cast(ss_item_rev#13 as decimal(19,3)) >= (0.9 * ws_item_rev#36)) AND (cast(ss_item_rev#13 as decimal(20,3)) <= (1.1 * ws_item_rev#36))) AND (cast(cs_item_rev#25 as decimal(19,3)) >= (0.9 * ws_item_rev#36))) AND (cast(cs_item_rev#25 as decimal(20,3)) <= (1.1 * ws_item_rev#36))) AND (cast(ws_item_rev#36 as decimal(19,3)) >= (0.9 * ss_item_rev#13))) AND (cast(ws_item_rev#36 as decimal(20,3)) <= (1.1 * ss_item_rev#13))) AND (cast(ws_item_rev#36 as decimal(19,3)) >= (0.9 * cs_item_rev#25))) AND (cast(ws_item_rev#36 as decimal(20,3)) <= (1.1 * cs_item_rev#25)))

(52) Project [codegen id : 12]
Output [8]: [item_id#12, ss_item_rev#13, (((ss_item_rev#13 / ((ss_item_rev#13 + cs_item_rev#25) + ws_item_rev#36)) / 3) * 100) AS ss_dev#37, cs_item_rev#25, (((cs_item_rev#25 / ((ss_item_rev#13 + cs_item_rev#25) + ws_item_rev#36)) / 3) * 100) AS cs_dev#38, ws_item_rev#36, (((ws_item_rev#36 / ((ss_item_rev#13 + cs_item_rev#25) + ws_item_rev#36)) / 3) * 100) AS ws_dev#39, (((ss_item_rev#13 + cs_item_rev#25) + ws_item_rev#36) / 3) AS average#40]
Input [5]: [item_id#12, ss_item_rev#13, cs_item_rev#25, item_id#35, ws_item_rev#36]

(53) TakeOrderedAndProject
Input [8]: [item_id#12, ss_item_rev#13, ss_dev#37, cs_item_rev#25, cs_dev#38, ws_item_rev#36, ws_dev#39, average#40]
Arguments: 100, [item_id#12 ASC NULLS FIRST, ss_item_rev#13 ASC NULLS FIRST], [item_id#12, ss_item_rev#13, ss_dev#37, cs_item_rev#25, cs_dev#38, ws_item_rev#36, ws_dev#39, average#40]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4
BroadcastExchange (63)
+- * CometColumnarToRow (62)
   +- CometProject (61)
      +- CometBroadcastHashJoin (60)
         :- CometFilter (55)
         :  +- CometNativeScan parquet spark_catalog.default.date_dim (54)
         +- CometBroadcastExchange (59)
            +- CometProject (58)
               +- CometFilter (57)
                  +- CometNativeScan parquet spark_catalog.default.date_dim (56)


(54) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#8, d_date#41]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_date:date>

(55) CometFilter
Input [2]: [d_date_sk#8, d_date#41]
Condition : isnotnull(d_date_sk#8)

(56) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date#41, d_week_seq#42]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_week_seq)]
ReadSchema: struct<d_date:date,d_week_seq:int>

(57) CometFilter
Input [2]: [d_date#41, d_week_seq#42]
Condition : (isnotnull(d_week_seq#42) AND (d_week_seq#42 = Subquery scalar-subquery#43, [id=#44]))

(58) CometProject
Input [2]: [d_date#41, d_week_seq#42]
Arguments: [d_date#41#45], [d_date#41 AS d_date#41#45]

(59) CometBroadcastExchange
Input [1]: [d_date#41#45]
Arguments: [d_date#41#45]

(60) CometBroadcastHashJoin
Left output [2]: [d_date_sk#8, d_date#41]
Right output [1]: [d_date#41#45]
Arguments: [d_date#41], [d_date#41#45], LeftSemi, BuildRight

(61) CometProject
Input [2]: [d_date_sk#8, d_date#41]
Arguments: [d_date_sk#8], [d_date_sk#8]

(62) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#8]

(63) BroadcastExchange
Input [1]: [d_date_sk#8]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7]

Subquery:2 Hosting operator id = 57 Hosting Expression = Subquery scalar-subquery#43, [id=#44]
* CometColumnarToRow (67)
+- CometProject (66)
   +- CometFilter (65)
      +- CometNativeScan parquet spark_catalog.default.date_dim (64)


(64) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date#41, d_week_seq#42]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date), EqualTo(d_date,2000-01-03)]
ReadSchema: struct<d_date:date,d_week_seq:int>

(65) CometFilter
Input [2]: [d_date#41, d_week_seq#42]
Condition : (isnotnull(d_date#41) AND (d_date#41 = 2000-01-03))

(66) CometProject
Input [2]: [d_date#41, d_week_seq#42]
Arguments: [d_week_seq#42], [d_week_seq#42]

(67) CometColumnarToRow [codegen id : 1]
Input [1]: [d_week_seq#42]

Subquery:3 Hosting operator id = 19 Hosting Expression = cs_sold_date_sk#16 IN dynamicpruning#17
BroadcastExchange (77)
+- * CometColumnarToRow (76)
   +- CometProject (75)
      +- CometBroadcastHashJoin (74)
         :- CometFilter (69)
         :  +- CometNativeScan parquet spark_catalog.default.date_dim (68)
         +- CometBroadcastExchange (73)
            +- CometProject (72)
               +- CometFilter (71)
                  +- CometNativeScan parquet spark_catalog.default.date_dim (70)


(68) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#20, d_date#46]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_date:date>

(69) CometFilter
Input [2]: [d_date_sk#20, d_date#46]
Condition : isnotnull(d_date_sk#20)

(70) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date#41, d_week_seq#42]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_week_seq)]
ReadSchema: struct<d_date:date,d_week_seq:int>

(71) CometFilter
Input [2]: [d_date#41, d_week_seq#42]
Condition : (isnotnull(d_week_seq#42) AND (d_week_seq#42 = ReusedSubquery Subquery scalar-subquery#43, [id=#44]))

(72) CometProject
Input [2]: [d_date#41, d_week_seq#42]
Arguments: [d_date#41], [d_date#41]

(73) CometBroadcastExchange
Input [1]: [d_date#41]
Arguments: [d_date#41]

(74) CometBroadcastHashJoin
Left output [2]: [d_date_sk#20, d_date#46]
Right output [1]: [d_date#41]
Arguments: [d_date#46], [d_date#41], LeftSemi, BuildRight

(75) CometProject
Input [2]: [d_date_sk#20, d_date#46]
Arguments: [d_date_sk#20], [d_date_sk#20]

(76) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#20]

(77) BroadcastExchange
Input [1]: [d_date_sk#20]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=8]

Subquery:4 Hosting operator id = 71 Hosting Expression = ReusedSubquery Subquery scalar-subquery#43, [id=#44]

Subquery:5 Hosting operator id = 36 Hosting Expression = ws_sold_date_sk#28 IN dynamicpruning#17


