== Physical Plan ==
TakeOrderedAndProject (70)
+- * HashAggregate (69)
   +- Exchange (68)
      +- * HashAggregate (67)
         +- * Project (66)
            +- * SortMergeJoin LeftOuter (65)
               :- * Sort (58)
               :  +- Exchange (57)
               :     +- * Project (56)
               :        +- * BroadcastHashJoin LeftOuter BuildRight (55)
               :           :- * Project (50)
               :           :  +- * BroadcastHashJoin Inner BuildRight (49)
               :           :     :- * Project (44)
               :           :     :  +- * BroadcastHashJoin Inner BuildRight (43)
               :           :     :     :- * Project (38)
               :           :     :     :  +- * BroadcastHashJoin Inner BuildRight (37)
               :           :     :     :     :- * Project (35)
               :           :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (34)
               :           :     :     :     :     :- * Project (28)
               :           :     :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (27)
               :           :     :     :     :     :     :- * Project (21)
               :           :     :     :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (20)
               :           :     :     :     :     :     :     :- * Project (15)
               :           :     :     :     :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (14)
               :           :     :     :     :     :     :     :     :- * Project (9)
               :           :     :     :     :     :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (8)
               :           :     :     :     :     :     :     :     :     :- * Filter (3)
               :           :     :     :     :     :     :     :     :     :  +- * ColumnarToRow (2)
               :           :     :     :     :     :     :     :     :     :     +- Scan parquet spark_catalog.default.catalog_sales (1)
               :           :     :     :     :     :     :     :     :     +- BroadcastExchange (7)
               :           :     :     :     :     :     :     :     :        +- * Filter (6)
               :           :     :     :     :     :     :     :     :           +- * ColumnarToRow (5)
               :           :     :     :     :     :     :     :     :              +- Scan parquet spark_catalog.default.inventory (4)
               :           :     :     :     :     :     :     :     +- BroadcastExchange (13)
               :           :     :     :     :     :     :     :        +- * Filter (12)
               :           :     :     :     :     :     :     :           +- * ColumnarToRow (11)
               :           :     :     :     :     :     :     :              +- Scan parquet spark_catalog.default.warehouse (10)
               :           :     :     :     :     :     :     +- BroadcastExchange (19)
               :           :     :     :     :     :     :        +- * Filter (18)
               :           :     :     :     :     :     :           +- * ColumnarToRow (17)
               :           :     :     :     :     :     :              +- Scan parquet spark_catalog.default.item (16)
               :           :     :     :     :     :     +- BroadcastExchange (26)
               :           :     :     :     :     :        +- * Project (25)
               :           :     :     :     :     :           +- * Filter (24)
               :           :     :     :     :     :              +- * ColumnarToRow (23)
               :           :     :     :     :     :                 +- Scan parquet spark_catalog.default.customer_demographics (22)
               :           :     :     :     :     +- BroadcastExchange (33)
               :           :     :     :     :        +- * Project (32)
               :           :     :     :     :           +- * Filter (31)
               :           :     :     :     :              +- * ColumnarToRow (30)
               :           :     :     :     :                 +- Scan parquet spark_catalog.default.household_demographics (29)
               :           :     :     :     +- ReusedExchange (36)
               :           :     :     +- BroadcastExchange (42)
               :           :     :        +- * Filter (41)
               :           :     :           +- * ColumnarToRow (40)
               :           :     :              +- Scan parquet spark_catalog.default.date_dim (39)
               :           :     +- BroadcastExchange (48)
               :           :        +- * Filter (47)
               :           :           +- * ColumnarToRow (46)
               :           :              +- Scan parquet spark_catalog.default.date_dim (45)
               :           +- BroadcastExchange (54)
               :              +- * Filter (53)
               :                 +- * ColumnarToRow (52)
               :                    +- Scan parquet spark_catalog.default.promotion (51)
               +- * Sort (64)
                  +- Exchange (63)
                     +- * Project (62)
                        +- * Filter (61)
                           +- * ColumnarToRow (60)
                              +- Scan parquet spark_catalog.default.catalog_returns (59)


(1) Scan parquet spark_catalog.default.catalog_sales
Output [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#8), dynamicpruningexpression(cs_sold_date_sk#8 IN dynamicpruning#9)]
PushedFilters: [IsNotNull(cs_quantity), IsNotNull(cs_item_sk), IsNotNull(cs_bill_cdemo_sk), IsNotNull(cs_bill_hdemo_sk), IsNotNull(cs_ship_date_sk)]
ReadSchema: struct<cs_ship_date_sk:int,cs_bill_cdemo_sk:int,cs_bill_hdemo_sk:int,cs_item_sk:int,cs_promo_sk:int,cs_order_number:int,cs_quantity:int>

(2) ColumnarToRow [codegen id : 10]
Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8]

(3) Filter [codegen id : 10]
Input [8]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8]
Condition : ((((isnotnull(cs_quantity#7) AND isnotnull(cs_item_sk#4)) AND isnotnull(cs_bill_cdemo_sk#2)) AND isnotnull(cs_bill_hdemo_sk#3)) AND isnotnull(cs_ship_date_sk#1))

(4) Scan parquet spark_catalog.default.inventory
Output [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(inv_date_sk#13)]
PushedFilters: [IsNotNull(inv_quantity_on_hand), IsNotNull(inv_item_sk), IsNotNull(inv_warehouse_sk)]
ReadSchema: struct<inv_item_sk:int,inv_warehouse_sk:int,inv_quantity_on_hand:int>

(5) ColumnarToRow [codegen id : 1]
Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13]

(6) Filter [codegen id : 1]
Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13]
Condition : ((isnotnull(inv_quantity_on_hand#12) AND isnotnull(inv_item_sk#10)) AND isnotnull(inv_warehouse_sk#11))

(7) BroadcastExchange
Input [4]: [inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(8) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_item_sk#4]
Right keys [1]: [inv_item_sk#10]
Join type: Inner
Join condition: (inv_quantity_on_hand#12 < cs_quantity#7)

(9) Project [codegen id : 10]
Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13]
Input [12]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_quantity#7, cs_sold_date_sk#8, inv_item_sk#10, inv_warehouse_sk#11, inv_quantity_on_hand#12, inv_date_sk#13]

(10) Scan parquet spark_catalog.default.warehouse
Output [2]: [w_warehouse_sk#14, w_warehouse_name#15]
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>

(11) ColumnarToRow [codegen id : 2]
Input [2]: [w_warehouse_sk#14, w_warehouse_name#15]

(12) Filter [codegen id : 2]
Input [2]: [w_warehouse_sk#14, w_warehouse_name#15]
Condition : isnotnull(w_warehouse_sk#14)

(13) BroadcastExchange
Input [2]: [w_warehouse_sk#14, w_warehouse_name#15]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=2]

(14) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [inv_warehouse_sk#11]
Right keys [1]: [w_warehouse_sk#14]
Join type: Inner
Join condition: None

(15) Project [codegen id : 10]
Output [9]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15]
Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_warehouse_sk#11, inv_date_sk#13, w_warehouse_sk#14, w_warehouse_name#15]

(16) Scan parquet spark_catalog.default.item
Output [2]: [i_item_sk#16, i_item_desc#17]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_desc:string>

(17) ColumnarToRow [codegen id : 3]
Input [2]: [i_item_sk#16, i_item_desc#17]

(18) Filter [codegen id : 3]
Input [2]: [i_item_sk#16, i_item_desc#17]
Condition : isnotnull(i_item_sk#16)

(19) BroadcastExchange
Input [2]: [i_item_sk#16, i_item_desc#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(20) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_item_sk#4]
Right keys [1]: [i_item_sk#16]
Join type: Inner
Join condition: None

(21) Project [codegen id : 10]
Output [10]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17]
Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_sk#16, i_item_desc#17]

(22) Scan parquet spark_catalog.default.customer_demographics
Output [2]: [cd_demo_sk#18, cd_marital_status#19]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_marital_status), EqualTo(cd_marital_status,D), IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_marital_status:string>

(23) ColumnarToRow [codegen id : 4]
Input [2]: [cd_demo_sk#18, cd_marital_status#19]

(24) Filter [codegen id : 4]
Input [2]: [cd_demo_sk#18, cd_marital_status#19]
Condition : ((isnotnull(cd_marital_status#19) AND (cd_marital_status#19 = D)) AND isnotnull(cd_demo_sk#18))

(25) Project [codegen id : 4]
Output [1]: [cd_demo_sk#18]
Input [2]: [cd_demo_sk#18, cd_marital_status#19]

(26) BroadcastExchange
Input [1]: [cd_demo_sk#18]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]

(27) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_bill_cdemo_sk#2]
Right keys [1]: [cd_demo_sk#18]
Join type: Inner
Join condition: None

(28) Project [codegen id : 10]
Output [9]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17]
Input [11]: [cs_ship_date_sk#1, cs_bill_cdemo_sk#2, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, cd_demo_sk#18]

(29) Scan parquet spark_catalog.default.household_demographics
Output [2]: [hd_demo_sk#20, hd_buy_potential#21]
Batched: true
Location [not included in comparison]/{warehouse_dir}/household_demographics]
PushedFilters: [IsNotNull(hd_buy_potential), EqualTo(hd_buy_potential,>10000         ), IsNotNull(hd_demo_sk)]
ReadSchema: struct<hd_demo_sk:int,hd_buy_potential:string>

(30) ColumnarToRow [codegen id : 5]
Input [2]: [hd_demo_sk#20, hd_buy_potential#21]

(31) Filter [codegen id : 5]
Input [2]: [hd_demo_sk#20, hd_buy_potential#21]
Condition : ((isnotnull(hd_buy_potential#21) AND (hd_buy_potential#21 = >10000         )) AND isnotnull(hd_demo_sk#20))

(32) Project [codegen id : 5]
Output [1]: [hd_demo_sk#20]
Input [2]: [hd_demo_sk#20, hd_buy_potential#21]

(33) BroadcastExchange
Input [1]: [hd_demo_sk#20]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]

(34) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_bill_hdemo_sk#3]
Right keys [1]: [hd_demo_sk#20]
Join type: Inner
Join condition: None

(35) Project [codegen id : 10]
Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17]
Input [10]: [cs_ship_date_sk#1, cs_bill_hdemo_sk#3, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, hd_demo_sk#20]

(36) ReusedExchange [Reuses operator id: 75]
Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24]

(37) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_sold_date_sk#8]
Right keys [1]: [d_date_sk#22]
Join type: Inner
Join condition: None

(38) Project [codegen id : 10]
Output [9]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24]
Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, cs_sold_date_sk#8, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date_sk#22, d_date#23, d_week_seq#24]

(39) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#25, d_week_seq#26]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_week_seq), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_week_seq:int>

(40) ColumnarToRow [codegen id : 7]
Input [2]: [d_date_sk#25, d_week_seq#26]

(41) Filter [codegen id : 7]
Input [2]: [d_date_sk#25, d_week_seq#26]
Condition : (isnotnull(d_week_seq#26) AND isnotnull(d_date_sk#25))

(42) BroadcastExchange
Input [2]: [d_date_sk#25, d_week_seq#26]
Arguments: HashedRelationBroadcastMode(List((shiftleft(cast(input[1, int, false] as bigint), 32) | (cast(input[0, int, false] as bigint) & 4294967295))),false), [plan_id=6]

(43) BroadcastHashJoin [codegen id : 10]
Left keys [2]: [d_week_seq#24, inv_date_sk#13]
Right keys [2]: [d_week_seq#26, d_date_sk#25]
Join type: Inner
Join condition: None

(44) Project [codegen id : 10]
Output [8]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24]
Input [11]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, inv_date_sk#13, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#25, d_week_seq#26]

(45) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#27, d_date#28]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_date:date>

(46) ColumnarToRow [codegen id : 8]
Input [2]: [d_date_sk#27, d_date#28]

(47) Filter [codegen id : 8]
Input [2]: [d_date_sk#27, d_date#28]
Condition : (isnotnull(d_date#28) AND isnotnull(d_date_sk#27))

(48) BroadcastExchange
Input [2]: [d_date_sk#27, d_date#28]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=7]

(49) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_ship_date_sk#1]
Right keys [1]: [d_date_sk#27]
Join type: Inner
Join condition: (d_date#28 > date_add(d_date#23, 5))

(50) Project [codegen id : 10]
Output [6]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24]
Input [10]: [cs_ship_date_sk#1, cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_date#23, d_week_seq#24, d_date_sk#27, d_date#28]

(51) Scan parquet spark_catalog.default.promotion
Output [1]: [p_promo_sk#29]
Batched: true
Location [not included in comparison]/{warehouse_dir}/promotion]
PushedFilters: [IsNotNull(p_promo_sk)]
ReadSchema: struct<p_promo_sk:int>

(52) ColumnarToRow [codegen id : 9]
Input [1]: [p_promo_sk#29]

(53) Filter [codegen id : 9]
Input [1]: [p_promo_sk#29]
Condition : isnotnull(p_promo_sk#29)

(54) BroadcastExchange
Input [1]: [p_promo_sk#29]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=8]

(55) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [cs_promo_sk#5]
Right keys [1]: [p_promo_sk#29]
Join type: LeftOuter
Join condition: None

(56) Project [codegen id : 10]
Output [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24]
Input [7]: [cs_item_sk#4, cs_promo_sk#5, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, p_promo_sk#29]

(57) Exchange
Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24]
Arguments: hashpartitioning(cs_item_sk#4, cs_order_number#6, 5), ENSURE_REQUIREMENTS, [plan_id=9]

(58) Sort [codegen id : 11]
Input [5]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24]
Arguments: [cs_item_sk#4 ASC NULLS FIRST, cs_order_number#6 ASC NULLS FIRST], false, 0

(59) Scan parquet spark_catalog.default.catalog_returns
Output [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32]
Batched: true
Location [not included in comparison]/{warehouse_dir}/catalog_returns]
PushedFilters: [IsNotNull(cr_item_sk), IsNotNull(cr_order_number)]
ReadSchema: struct<cr_item_sk:int,cr_order_number:int>

(60) ColumnarToRow [codegen id : 12]
Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32]

(61) Filter [codegen id : 12]
Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32]
Condition : (isnotnull(cr_item_sk#30) AND isnotnull(cr_order_number#31))

(62) Project [codegen id : 12]
Output [2]: [cr_item_sk#30, cr_order_number#31]
Input [3]: [cr_item_sk#30, cr_order_number#31, cr_returned_date_sk#32]

(63) Exchange
Input [2]: [cr_item_sk#30, cr_order_number#31]
Arguments: hashpartitioning(cr_item_sk#30, cr_order_number#31, 5), ENSURE_REQUIREMENTS, [plan_id=10]

(64) Sort [codegen id : 13]
Input [2]: [cr_item_sk#30, cr_order_number#31]
Arguments: [cr_item_sk#30 ASC NULLS FIRST, cr_order_number#31 ASC NULLS FIRST], false, 0

(65) SortMergeJoin [codegen id : 14]
Left keys [2]: [cs_item_sk#4, cs_order_number#6]
Right keys [2]: [cr_item_sk#30, cr_order_number#31]
Join type: LeftOuter
Join condition: None

(66) Project [codegen id : 14]
Output [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24]
Input [7]: [cs_item_sk#4, cs_order_number#6, w_warehouse_name#15, i_item_desc#17, d_week_seq#24, cr_item_sk#30, cr_order_number#31]

(67) HashAggregate [codegen id : 14]
Input [3]: [w_warehouse_name#15, i_item_desc#17, d_week_seq#24]
Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24]
Functions [1]: [partial_count(1)]
Aggregate Attributes [1]: [count#33]
Results [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34]

(68) Exchange
Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34]
Arguments: hashpartitioning(i_item_desc#17, w_warehouse_name#15, d_week_seq#24, 5), ENSURE_REQUIREMENTS, [plan_id=11]

(69) HashAggregate [codegen id : 15]
Input [4]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count#34]
Keys [3]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24]
Functions [1]: [count(1)]
Aggregate Attributes [1]: [count(1)#35]
Results [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, count(1)#35 AS no_promo#36, count(1)#35 AS promo#37, count(1)#35 AS total_cnt#38]

(70) TakeOrderedAndProject
Input [6]: [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38]
Arguments: 100, [total_cnt#38 DESC NULLS LAST, i_item_desc#17 ASC NULLS FIRST, w_warehouse_name#15 ASC NULLS FIRST, d_week_seq#24 ASC NULLS FIRST], [i_item_desc#17, w_warehouse_name#15, d_week_seq#24, no_promo#36, promo#37, total_cnt#38]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = cs_sold_date_sk#8 IN dynamicpruning#9
BroadcastExchange (75)
+- * Project (74)
   +- * Filter (73)
      +- * ColumnarToRow (72)
         +- Scan parquet spark_catalog.default.date_dim (71)


(71) Scan parquet spark_catalog.default.date_dim
Output [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,1999), IsNotNull(d_date_sk), IsNotNull(d_week_seq), IsNotNull(d_date)]
ReadSchema: struct<d_date_sk:int,d_date:date,d_week_seq:int,d_year:int>

(72) ColumnarToRow [codegen id : 1]
Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39]

(73) Filter [codegen id : 1]
Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39]
Condition : ((((isnotnull(d_year#39) AND (d_year#39 = 1999)) AND isnotnull(d_date_sk#22)) AND isnotnull(d_week_seq#24)) AND isnotnull(d_date#23))

(74) Project [codegen id : 1]
Output [3]: [d_date_sk#22, d_date#23, d_week_seq#24]
Input [4]: [d_date_sk#22, d_date#23, d_week_seq#24, d_year#39]

(75) BroadcastExchange
Input [3]: [d_date_sk#22, d_date#23, d_week_seq#24]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=12]


