== Physical Plan ==
TakeOrderedAndProject (43)
+- * Project (42)
   +- * BroadcastHashJoin Inner BuildRight (41)
      :- * Project (39)
      :  +- * BroadcastHashJoin Inner BuildRight (38)
      :     :- * HashAggregate (33)
      :     :  +- Exchange (32)
      :     :     +- * HashAggregate (31)
      :     :        +- * Project (30)
      :     :           +- * BroadcastHashJoin Inner BuildRight (29)
      :     :              :- * Project (24)
      :     :              :  +- * BroadcastHashJoin Inner BuildRight (23)
      :     :              :     :- * Project (17)
      :     :              :     :  +- * BroadcastHashJoin Inner BuildRight (16)
      :     :              :     :     :- * Project (10)
      :     :              :     :     :  +- * BroadcastHashJoin Inner BuildRight (9)
      :     :              :     :     :     :- * Filter (3)
      :     :              :     :     :     :  +- * ColumnarToRow (2)
      :     :              :     :     :     :     +- Scan parquet spark_catalog.default.store_sales (1)
      :     :              :     :     :     +- BroadcastExchange (8)
      :     :              :     :     :        +- * Project (7)
      :     :              :     :     :           +- * Filter (6)
      :     :              :     :     :              +- * ColumnarToRow (5)
      :     :              :     :     :                 +- Scan parquet spark_catalog.default.date_dim (4)
      :     :              :     :     +- BroadcastExchange (15)
      :     :              :     :        +- * Project (14)
      :     :              :     :           +- * Filter (13)
      :     :              :     :              +- * ColumnarToRow (12)
      :     :              :     :                 +- Scan parquet spark_catalog.default.store (11)
      :     :              :     +- BroadcastExchange (22)
      :     :              :        +- * Project (21)
      :     :              :           +- * Filter (20)
      :     :              :              +- * ColumnarToRow (19)
      :     :              :                 +- Scan parquet spark_catalog.default.household_demographics (18)
      :     :              +- BroadcastExchange (28)
      :     :                 +- * Filter (27)
      :     :                    +- * ColumnarToRow (26)
      :     :                       +- Scan parquet spark_catalog.default.customer_address (25)
      :     +- BroadcastExchange (37)
      :        +- * Filter (36)
      :           +- * ColumnarToRow (35)
      :              +- Scan parquet spark_catalog.default.customer (34)
      +- ReusedExchange (40)


(1) Scan parquet spark_catalog.default.store_sales
Output [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#8)]
PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_hdemo_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_customer_sk)]
ReadSchema: struct<ss_customer_sk:int,ss_hdemo_sk:int,ss_addr_sk:int,ss_store_sk:int,ss_ticket_number:int,ss_coupon_amt:decimal(7,2),ss_net_profit:decimal(7,2)>

(2) ColumnarToRow [codegen id : 5]
Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8]

(3) Filter [codegen id : 5]
Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8]
Condition : (((isnotnull(ss_store_sk#4) AND isnotnull(ss_hdemo_sk#2)) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_customer_sk#1))

(4) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#9, d_year#10, d_dow#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [In(d_dow, [0,6]), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_dow:int>

(5) ColumnarToRow [codegen id : 1]
Input [3]: [d_date_sk#9, d_year#10, d_dow#11]

(6) Filter [codegen id : 1]
Input [3]: [d_date_sk#9, d_year#10, d_dow#11]
Condition : ((d_dow#11 IN (6,0) AND d_year#10 IN (1999,2000,2001)) AND isnotnull(d_date_sk#9))

(7) Project [codegen id : 1]
Output [1]: [d_date_sk#9]
Input [3]: [d_date_sk#9, d_year#10, d_dow#11]

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

(9) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_sold_date_sk#8]
Right keys [1]: [d_date_sk#9]
Join type: Inner
Join condition: None

(10) Project [codegen id : 5]
Output [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7]
Input [9]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ss_sold_date_sk#8, d_date_sk#9]

(11) Scan parquet spark_catalog.default.store
Output [2]: [s_store_sk#12, s_city#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [In(s_city, [Fairview,Midway]), IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_city:string>

(12) ColumnarToRow [codegen id : 2]
Input [2]: [s_store_sk#12, s_city#13]

(13) Filter [codegen id : 2]
Input [2]: [s_store_sk#12, s_city#13]
Condition : (s_city#13 IN (Fairview,Midway) AND isnotnull(s_store_sk#12))

(14) Project [codegen id : 2]
Output [1]: [s_store_sk#12]
Input [2]: [s_store_sk#12, s_city#13]

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

(16) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_store_sk#4]
Right keys [1]: [s_store_sk#12]
Join type: Inner
Join condition: None

(17) Project [codegen id : 5]
Output [6]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7]
Input [8]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, s_store_sk#12]

(18) Scan parquet spark_catalog.default.household_demographics
Output [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16]
Batched: true
Location [not included in comparison]/{warehouse_dir}/household_demographics]
PushedFilters: [Or(EqualTo(hd_dep_count,4),EqualTo(hd_vehicle_count,3)), IsNotNull(hd_demo_sk)]
ReadSchema: struct<hd_demo_sk:int,hd_dep_count:int,hd_vehicle_count:int>

(19) ColumnarToRow [codegen id : 3]
Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16]

(20) Filter [codegen id : 3]
Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16]
Condition : (((hd_dep_count#15 = 4) OR (hd_vehicle_count#16 = 3)) AND isnotnull(hd_demo_sk#14))

(21) Project [codegen id : 3]
Output [1]: [hd_demo_sk#14]
Input [3]: [hd_demo_sk#14, hd_dep_count#15, hd_vehicle_count#16]

(22) BroadcastExchange
Input [1]: [hd_demo_sk#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(23) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_hdemo_sk#2]
Right keys [1]: [hd_demo_sk#14]
Join type: Inner
Join condition: None

(24) Project [codegen id : 5]
Output [5]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7]
Input [7]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, hd_demo_sk#14]

(25) Scan parquet spark_catalog.default.customer_address
Output [2]: [ca_address_sk#17, ca_city#18]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer_address]
PushedFilters: [IsNotNull(ca_address_sk), IsNotNull(ca_city)]
ReadSchema: struct<ca_address_sk:int,ca_city:string>

(26) ColumnarToRow [codegen id : 4]
Input [2]: [ca_address_sk#17, ca_city#18]

(27) Filter [codegen id : 4]
Input [2]: [ca_address_sk#17, ca_city#18]
Condition : (isnotnull(ca_address_sk#17) AND isnotnull(ca_city#18))

(28) BroadcastExchange
Input [2]: [ca_address_sk#17, ca_city#18]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4]

(29) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_addr_sk#3]
Right keys [1]: [ca_address_sk#17]
Join type: Inner
Join condition: None

(30) Project [codegen id : 5]
Output [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_city#18]
Input [7]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_address_sk#17, ca_city#18]

(31) HashAggregate [codegen id : 5]
Input [6]: [ss_customer_sk#1, ss_addr_sk#3, ss_ticket_number#5, ss_coupon_amt#6, ss_net_profit#7, ca_city#18]
Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18]
Functions [2]: [partial_sum(UnscaledValue(ss_coupon_amt#6)), partial_sum(UnscaledValue(ss_net_profit#7))]
Aggregate Attributes [2]: [sum#19, sum#20]
Results [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#21, sum#22]

(32) Exchange
Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#21, sum#22]
Arguments: hashpartitioning(ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, 5), ENSURE_REQUIREMENTS, [plan_id=5]

(33) HashAggregate [codegen id : 8]
Input [6]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18, sum#21, sum#22]
Keys [4]: [ss_ticket_number#5, ss_customer_sk#1, ss_addr_sk#3, ca_city#18]
Functions [2]: [sum(UnscaledValue(ss_coupon_amt#6)), sum(UnscaledValue(ss_net_profit#7))]
Aggregate Attributes [2]: [sum(UnscaledValue(ss_coupon_amt#6))#23, sum(UnscaledValue(ss_net_profit#7))#24]
Results [5]: [ss_ticket_number#5, ss_customer_sk#1, ca_city#18 AS bought_city#25, MakeDecimal(sum(UnscaledValue(ss_coupon_amt#6))#23,17,2) AS amt#26, MakeDecimal(sum(UnscaledValue(ss_net_profit#7))#24,17,2) AS profit#27]

(34) Scan parquet spark_catalog.default.customer
Output [4]: [c_customer_sk#28, c_current_addr_sk#29, c_first_name#30, c_last_name#31]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer]
PushedFilters: [IsNotNull(c_customer_sk), IsNotNull(c_current_addr_sk)]
ReadSchema: struct<c_customer_sk:int,c_current_addr_sk:int,c_first_name:string,c_last_name:string>

(35) ColumnarToRow [codegen id : 6]
Input [4]: [c_customer_sk#28, c_current_addr_sk#29, c_first_name#30, c_last_name#31]

(36) Filter [codegen id : 6]
Input [4]: [c_customer_sk#28, c_current_addr_sk#29, c_first_name#30, c_last_name#31]
Condition : (isnotnull(c_customer_sk#28) AND isnotnull(c_current_addr_sk#29))

(37) BroadcastExchange
Input [4]: [c_customer_sk#28, c_current_addr_sk#29, c_first_name#30, c_last_name#31]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6]

(38) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [ss_customer_sk#1]
Right keys [1]: [c_customer_sk#28]
Join type: Inner
Join condition: None

(39) Project [codegen id : 8]
Output [7]: [ss_ticket_number#5, bought_city#25, amt#26, profit#27, c_current_addr_sk#29, c_first_name#30, c_last_name#31]
Input [9]: [ss_ticket_number#5, ss_customer_sk#1, bought_city#25, amt#26, profit#27, c_customer_sk#28, c_current_addr_sk#29, c_first_name#30, c_last_name#31]

(40) ReusedExchange [Reuses operator id: 28]
Output [2]: [ca_address_sk#32, ca_city#33]

(41) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [c_current_addr_sk#29]
Right keys [1]: [ca_address_sk#32]
Join type: Inner
Join condition: NOT (ca_city#33 = bought_city#25)

(42) Project [codegen id : 8]
Output [7]: [c_last_name#31, c_first_name#30, ca_city#33, bought_city#25, ss_ticket_number#5, amt#26, profit#27]
Input [9]: [ss_ticket_number#5, bought_city#25, amt#26, profit#27, c_current_addr_sk#29, c_first_name#30, c_last_name#31, ca_address_sk#32, ca_city#33]

(43) TakeOrderedAndProject
Input [7]: [c_last_name#31, c_first_name#30, ca_city#33, bought_city#25, ss_ticket_number#5, amt#26, profit#27]
Arguments: 100, [c_last_name#31 ASC NULLS FIRST, c_first_name#30 ASC NULLS FIRST, ca_city#33 ASC NULLS FIRST, bought_city#25 ASC NULLS FIRST, ss_ticket_number#5 ASC NULLS FIRST], [c_last_name#31, c_first_name#30, ca_city#33, bought_city#25, ss_ticket_number#5, amt#26, profit#27]

