== Physical Plan ==
* ColumnarToRow (54)
+- CometSort (53)
   +- CometColumnarExchange (52)
      +- RowToColumnar (51)
         +- * BroadcastHashJoin Inner BuildRight (50)
            :- * Project (26)
            :  +- * Filter (25)
            :     +- * HashAggregate (24)
            :        +- * ColumnarToRow (23)
            :           +- CometColumnarExchange (22)
            :              +- RowToColumnar (21)
            :                 +- * HashAggregate (20)
            :                    +- * ColumnarToRow (19)
            :                       +- CometProject (18)
            :                          +- CometBroadcastHashJoin (17)
            :                             :- CometProject (12)
            :                             :  +- CometBroadcastHashJoin (11)
            :                             :     :- CometProject (7)
            :                             :     :  +- CometBroadcastHashJoin (6)
            :                             :     :     :- CometFilter (2)
            :                             :     :     :  +- CometScan parquet spark_catalog.default.inventory (1)
            :                             :     :     +- CometBroadcastExchange (5)
            :                             :     :        +- CometFilter (4)
            :                             :     :           +- CometScan parquet spark_catalog.default.item (3)
            :                             :     +- CometBroadcastExchange (10)
            :                             :        +- CometFilter (9)
            :                             :           +- CometScan parquet spark_catalog.default.warehouse (8)
            :                             +- CometBroadcastExchange (16)
            :                                +- CometProject (15)
            :                                   +- CometFilter (14)
            :                                      +- CometScan parquet spark_catalog.default.date_dim (13)
            +- BroadcastExchange (49)
               +- * Project (48)
                  +- * Filter (47)
                     +- * HashAggregate (46)
                        +- * ColumnarToRow (45)
                           +- CometColumnarExchange (44)
                              +- RowToColumnar (43)
                                 +- * HashAggregate (42)
                                    +- * ColumnarToRow (41)
                                       +- CometProject (40)
                                          +- CometBroadcastHashJoin (39)
                                             :- CometProject (34)
                                             :  +- CometBroadcastHashJoin (33)
                                             :     :- CometProject (31)
                                             :     :  +- CometBroadcastHashJoin (30)
                                             :     :     :- CometFilter (28)
                                             :     :     :  +- CometScan parquet spark_catalog.default.inventory (27)
                                             :     :     +- ReusedExchange (29)
                                             :     +- ReusedExchange (32)
                                             +- CometBroadcastExchange (38)
                                                +- CometProject (37)
                                                   +- CometFilter (36)
                                                      +- CometScan parquet spark_catalog.default.date_dim (35)


(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) 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) Scan parquet spark_catalog.default.item
Output [1]: [i_item_sk#6]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int>

(4) CometFilter
Input [1]: [i_item_sk#6]
Condition : isnotnull(i_item_sk#6)

(5) CometBroadcastExchange
Input [1]: [i_item_sk#6]
Arguments: [i_item_sk#6]

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

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

(8) Scan parquet spark_catalog.default.warehouse
Output [2]: [w_warehouse_sk#7, w_warehouse_name#8]
Batched: true
Location [not included in comparison]/{warehouse_dir}/warehouse]
PushedFilters: [IsNotNull(w_warehouse_sk)]
ReadSchema: struct<w_warehouse_sk:int,w_warehouse_name:string>

(9) CometFilter
Input [2]: [w_warehouse_sk#7, w_warehouse_name#8]
Condition : isnotnull(w_warehouse_sk#7)

(10) CometBroadcastExchange
Input [2]: [w_warehouse_sk#7, w_warehouse_name#8]
Arguments: [w_warehouse_sk#7, w_warehouse_name#8]

(11) CometBroadcastHashJoin
Left output [4]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6]
Right output [2]: [w_warehouse_sk#7, w_warehouse_name#8]
Arguments: [inv_warehouse_sk#2], [w_warehouse_sk#7], Inner, BuildRight

(12) CometProject
Input [6]: [inv_warehouse_sk#2, inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8]
Arguments: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8], [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8]

(13) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#9, d_year#10, d_moy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(14) CometFilter
Input [3]: [d_date_sk#9, d_year#10, d_moy#11]
Condition : ((((isnotnull(d_year#10) AND isnotnull(d_moy#11)) AND (d_year#10 = 2001)) AND (d_moy#11 = 1)) AND isnotnull(d_date_sk#9))

(15) CometProject
Input [3]: [d_date_sk#9, d_year#10, d_moy#11]
Arguments: [d_date_sk#9, d_moy#11], [d_date_sk#9, d_moy#11]

(16) CometBroadcastExchange
Input [2]: [d_date_sk#9, d_moy#11]
Arguments: [d_date_sk#9, d_moy#11]

(17) CometBroadcastHashJoin
Left output [5]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8]
Right output [2]: [d_date_sk#9, d_moy#11]
Arguments: [inv_date_sk#4], [d_date_sk#9], Inner, BuildRight

(18) CometProject
Input [7]: [inv_quantity_on_hand#3, inv_date_sk#4, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_date_sk#9, d_moy#11]
Arguments: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#11], [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#11]

(19) ColumnarToRow [codegen id : 1]
Input [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#11]

(20) HashAggregate [codegen id : 1]
Input [5]: [inv_quantity_on_hand#3, i_item_sk#6, w_warehouse_sk#7, w_warehouse_name#8, d_moy#11]
Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11]
Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#3 as double)), partial_avg(inv_quantity_on_hand#3)]
Aggregate Attributes [5]: [n#12, avg#13, m2#14, sum#15, count#16]
Results [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11, n#17, avg#18, m2#19, sum#20, count#21]

(21) RowToColumnar
Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11, n#17, avg#18, m2#19, sum#20, count#21]

(22) CometColumnarExchange
Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11, n#17, avg#18, m2#19, sum#20, count#21]
Arguments: hashpartitioning(w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=1]

(23) ColumnarToRow [codegen id : 4]
Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11, n#17, avg#18, m2#19, sum#20, count#21]

(24) HashAggregate [codegen id : 4]
Input [9]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11, n#17, avg#18, m2#19, sum#20, count#21]
Keys [4]: [w_warehouse_name#8, w_warehouse_sk#7, i_item_sk#6, d_moy#11]
Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double)), avg(inv_quantity_on_hand#3)]
Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#3 as double))#22, avg(inv_quantity_on_hand#3)#23]
Results [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, stddev_samp(cast(inv_quantity_on_hand#3 as double))#22 AS stdev#24, avg(inv_quantity_on_hand#3)#23 AS mean#25]

(25) Filter [codegen id : 4]
Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, stdev#24, mean#25]
Condition : (CASE WHEN (mean#25 = 0.0) THEN false ELSE ((stdev#24 / mean#25) > 1.0) END AND CASE WHEN (mean#25 = 0.0) THEN false ELSE ((stdev#24 / mean#25) > 1.5) END)

(26) Project [codegen id : 4]
Output [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, mean#25, CASE WHEN (mean#25 = 0.0) THEN null ELSE (stdev#24 / mean#25) END AS cov#26]
Input [5]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, stdev#24, mean#25]

(27) Scan parquet spark_catalog.default.inventory
Output [4]: [inv_item_sk#27, inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(inv_date_sk#30), dynamicpruningexpression(inv_date_sk#30 IN dynamicpruning#31)]
PushedFilters: [IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)]
ReadSchema: struct<inv_item_sk:int,inv_warehouse_sk:int,inv_quantity_on_hand:int>

(28) CometFilter
Input [4]: [inv_item_sk#27, inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30]
Condition : (isnotnull(inv_item_sk#27) AND isnotnull(inv_warehouse_sk#28))

(29) ReusedExchange [Reuses operator id: 5]
Output [1]: [i_item_sk#32]

(30) CometBroadcastHashJoin
Left output [4]: [inv_item_sk#27, inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30]
Right output [1]: [i_item_sk#32]
Arguments: [inv_item_sk#27], [i_item_sk#32], Inner, BuildRight

(31) CometProject
Input [5]: [inv_item_sk#27, inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32]
Arguments: [inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32], [inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32]

(32) ReusedExchange [Reuses operator id: 10]
Output [2]: [w_warehouse_sk#33, w_warehouse_name#34]

(33) CometBroadcastHashJoin
Left output [4]: [inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32]
Right output [2]: [w_warehouse_sk#33, w_warehouse_name#34]
Arguments: [inv_warehouse_sk#28], [w_warehouse_sk#33], Inner, BuildRight

(34) CometProject
Input [6]: [inv_warehouse_sk#28, inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34]
Arguments: [inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34], [inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34]

(35) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#35, d_year#36, d_moy#37]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(36) CometFilter
Input [3]: [d_date_sk#35, d_year#36, d_moy#37]
Condition : ((((isnotnull(d_year#36) AND isnotnull(d_moy#37)) AND (d_year#36 = 2001)) AND (d_moy#37 = 2)) AND isnotnull(d_date_sk#35))

(37) CometProject
Input [3]: [d_date_sk#35, d_year#36, d_moy#37]
Arguments: [d_date_sk#35, d_moy#37], [d_date_sk#35, d_moy#37]

(38) CometBroadcastExchange
Input [2]: [d_date_sk#35, d_moy#37]
Arguments: [d_date_sk#35, d_moy#37]

(39) CometBroadcastHashJoin
Left output [5]: [inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34]
Right output [2]: [d_date_sk#35, d_moy#37]
Arguments: [inv_date_sk#30], [d_date_sk#35], Inner, BuildRight

(40) CometProject
Input [7]: [inv_quantity_on_hand#29, inv_date_sk#30, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34, d_date_sk#35, d_moy#37]
Arguments: [inv_quantity_on_hand#29, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34, d_moy#37], [inv_quantity_on_hand#29, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34, d_moy#37]

(41) ColumnarToRow [codegen id : 2]
Input [5]: [inv_quantity_on_hand#29, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34, d_moy#37]

(42) HashAggregate [codegen id : 2]
Input [5]: [inv_quantity_on_hand#29, i_item_sk#32, w_warehouse_sk#33, w_warehouse_name#34, d_moy#37]
Keys [4]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37]
Functions [2]: [partial_stddev_samp(cast(inv_quantity_on_hand#29 as double)), partial_avg(inv_quantity_on_hand#29)]
Aggregate Attributes [5]: [n#38, avg#39, m2#40, sum#41, count#42]
Results [9]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37, n#43, avg#44, m2#45, sum#46, count#47]

(43) RowToColumnar
Input [9]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37, n#43, avg#44, m2#45, sum#46, count#47]

(44) CometColumnarExchange
Input [9]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37, n#43, avg#44, m2#45, sum#46, count#47]
Arguments: hashpartitioning(w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(45) ColumnarToRow [codegen id : 3]
Input [9]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37, n#43, avg#44, m2#45, sum#46, count#47]

(46) HashAggregate [codegen id : 3]
Input [9]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37, n#43, avg#44, m2#45, sum#46, count#47]
Keys [4]: [w_warehouse_name#34, w_warehouse_sk#33, i_item_sk#32, d_moy#37]
Functions [2]: [stddev_samp(cast(inv_quantity_on_hand#29 as double)), avg(inv_quantity_on_hand#29)]
Aggregate Attributes [2]: [stddev_samp(cast(inv_quantity_on_hand#29 as double))#22, avg(inv_quantity_on_hand#29)#23]
Results [5]: [w_warehouse_sk#33, i_item_sk#32, d_moy#37, stddev_samp(cast(inv_quantity_on_hand#29 as double))#22 AS stdev#48, avg(inv_quantity_on_hand#29)#23 AS mean#49]

(47) Filter [codegen id : 3]
Input [5]: [w_warehouse_sk#33, i_item_sk#32, d_moy#37, stdev#48, mean#49]
Condition : CASE WHEN (mean#49 = 0.0) THEN false ELSE ((stdev#48 / mean#49) > 1.0) END

(48) Project [codegen id : 3]
Output [5]: [w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, CASE WHEN (mean#49 = 0.0) THEN null ELSE (stdev#48 / mean#49) END AS cov#50]
Input [5]: [w_warehouse_sk#33, i_item_sk#32, d_moy#37, stdev#48, mean#49]

(49) BroadcastExchange
Input [5]: [w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, cov#50]
Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, true] as bigint), 32) | (cast(input[0, int, true] as bigint) & 4294967295))),false), [plan_id=3]

(50) BroadcastHashJoin [codegen id : 4]
Left keys [2]: [i_item_sk#6, w_warehouse_sk#7]
Right keys [2]: [i_item_sk#32, w_warehouse_sk#33]
Join type: Inner
Join condition: None

(51) RowToColumnar
Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, mean#25, cov#26, w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, cov#50]

(52) CometColumnarExchange
Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, mean#25, cov#26, w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, cov#50]
Arguments: rangepartitioning(w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, mean#25 ASC NULLS FIRST, cov#26 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST, mean#49 ASC NULLS FIRST, cov#50 ASC NULLS FIRST, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(53) CometSort
Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, mean#25, cov#26, w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, cov#50]
Arguments: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, mean#25, cov#26, w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, cov#50], [w_warehouse_sk#7 ASC NULLS FIRST, i_item_sk#6 ASC NULLS FIRST, d_moy#11 ASC NULLS FIRST, mean#25 ASC NULLS FIRST, cov#26 ASC NULLS FIRST, d_moy#37 ASC NULLS FIRST, mean#49 ASC NULLS FIRST, cov#50 ASC NULLS FIRST]

(54) ColumnarToRow [codegen id : 5]
Input [10]: [w_warehouse_sk#7, i_item_sk#6, d_moy#11, mean#25, cov#26, w_warehouse_sk#33, i_item_sk#32, d_moy#37, mean#49, cov#50]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = inv_date_sk#4 IN dynamicpruning#5
BroadcastExchange (59)
+- * ColumnarToRow (58)
   +- CometProject (57)
      +- CometFilter (56)
         +- CometScan parquet spark_catalog.default.date_dim (55)


(55) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#9, d_year#10, d_moy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,1), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(56) CometFilter
Input [3]: [d_date_sk#9, d_year#10, d_moy#11]
Condition : ((((isnotnull(d_year#10) AND isnotnull(d_moy#11)) AND (d_year#10 = 2001)) AND (d_moy#11 = 1)) AND isnotnull(d_date_sk#9))

(57) CometProject
Input [3]: [d_date_sk#9, d_year#10, d_moy#11]
Arguments: [d_date_sk#9, d_moy#11], [d_date_sk#9, d_moy#11]

(58) ColumnarToRow [codegen id : 1]
Input [2]: [d_date_sk#9, d_moy#11]

(59) BroadcastExchange
Input [2]: [d_date_sk#9, d_moy#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]

Subquery:2 Hosting operator id = 27 Hosting Expression = inv_date_sk#30 IN dynamicpruning#31
BroadcastExchange (64)
+- * ColumnarToRow (63)
   +- CometProject (62)
      +- CometFilter (61)
         +- CometScan parquet spark_catalog.default.date_dim (60)


(60) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#35, d_year#36, d_moy#37]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), IsNotNull(d_moy), EqualTo(d_year,2001), EqualTo(d_moy,2), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(61) CometFilter
Input [3]: [d_date_sk#35, d_year#36, d_moy#37]
Condition : ((((isnotnull(d_year#36) AND isnotnull(d_moy#37)) AND (d_year#36 = 2001)) AND (d_moy#37 = 2)) AND isnotnull(d_date_sk#35))

(62) CometProject
Input [3]: [d_date_sk#35, d_year#36, d_moy#37]
Arguments: [d_date_sk#35, d_moy#37], [d_date_sk#35, d_moy#37]

(63) ColumnarToRow [codegen id : 1]
Input [2]: [d_date_sk#35, d_moy#37]

(64) BroadcastExchange
Input [2]: [d_date_sk#35, d_moy#37]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]


