== Physical Plan ==
* HashAggregate (36)
+- * CometColumnarToRow (35)
   +- CometColumnarExchange (34)
      +- * HashAggregate (33)
         +- * Project (32)
            +- * BroadcastHashJoin Inner BuildRight (31)
               :- * Project (26)
               :  +- * BroadcastHashJoin Inner BuildRight (25)
               :     :- * Project (19)
               :     :  +- * BroadcastHashJoin Inner BuildRight (18)
               :     :     :- * Project (16)
               :     :     :  +- * BroadcastHashJoin Inner BuildRight (15)
               :     :     :     :- * Project (9)
               :     :     :     :  +- * BroadcastHashJoin Inner BuildRight (8)
               :     :     :     :     :- * Filter (3)
               :     :     :     :     :  +- * ColumnarToRow (2)
               :     :     :     :     :     +- Scan parquet spark_catalog.default.store_sales (1)
               :     :     :     :     +- BroadcastExchange (7)
               :     :     :     :        +- * CometColumnarToRow (6)
               :     :     :     :           +- CometFilter (5)
               :     :     :     :              +- CometNativeScan parquet spark_catalog.default.store (4)
               :     :     :     +- BroadcastExchange (14)
               :     :     :        +- * CometColumnarToRow (13)
               :     :     :           +- CometProject (12)
               :     :     :              +- CometFilter (11)
               :     :     :                 +- CometNativeScan parquet spark_catalog.default.customer_address (10)
               :     :     +- ReusedExchange (17)
               :     +- BroadcastExchange (24)
               :        +- * CometColumnarToRow (23)
               :           +- CometProject (22)
               :              +- CometFilter (21)
               :                 +- CometNativeScan parquet spark_catalog.default.customer_demographics (20)
               +- BroadcastExchange (30)
                  +- * CometColumnarToRow (29)
                     +- CometFilter (28)
                        +- CometNativeScan parquet spark_catalog.default.household_demographics (27)


(1) Scan parquet spark_catalog.default.store_sales
Output [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#10), dynamicpruningexpression(ss_sold_date_sk#10 IN dynamicpruning#11)]
PushedFilters: [IsNotNull(ss_store_sk), IsNotNull(ss_addr_sk), IsNotNull(ss_cdemo_sk), IsNotNull(ss_hdemo_sk), Or(Or(And(GreaterThanOrEqual(ss_net_profit,100.00),LessThanOrEqual(ss_net_profit,200.00)),And(GreaterThanOrEqual(ss_net_profit,150.00),LessThanOrEqual(ss_net_profit,300.00))),And(GreaterThanOrEqual(ss_net_profit,50.00),LessThanOrEqual(ss_net_profit,250.00))), Or(Or(And(GreaterThanOrEqual(ss_sales_price,100.00),LessThanOrEqual(ss_sales_price,150.00)),And(GreaterThanOrEqual(ss_sales_price,50.00),LessThanOrEqual(ss_sales_price,100.00))),And(GreaterThanOrEqual(ss_sales_price,150.00),LessThanOrEqual(ss_sales_price,200.00)))]
ReadSchema: struct<ss_cdemo_sk:int,ss_hdemo_sk:int,ss_addr_sk:int,ss_store_sk:int,ss_quantity:int,ss_sales_price:decimal(7,2),ss_ext_sales_price:decimal(7,2),ss_ext_wholesale_cost:decimal(7,2),ss_net_profit:decimal(7,2)>

(2) ColumnarToRow [codegen id : 6]
Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10]

(3) Filter [codegen id : 6]
Input [10]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10]
Condition : (((((isnotnull(ss_store_sk#4) AND isnotnull(ss_addr_sk#3)) AND isnotnull(ss_cdemo_sk#1)) AND isnotnull(ss_hdemo_sk#2)) AND ((((ss_net_profit#9 >= 100.00) AND (ss_net_profit#9 <= 200.00)) OR ((ss_net_profit#9 >= 150.00) AND (ss_net_profit#9 <= 300.00))) OR ((ss_net_profit#9 >= 50.00) AND (ss_net_profit#9 <= 250.00)))) AND ((((ss_sales_price#6 >= 100.00) AND (ss_sales_price#6 <= 150.00)) OR ((ss_sales_price#6 >= 50.00) AND (ss_sales_price#6 <= 100.00))) OR ((ss_sales_price#6 >= 150.00) AND (ss_sales_price#6 <= 200.00))))

(4) CometNativeScan parquet spark_catalog.default.store
Output [1]: [s_store_sk#12]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int>

(5) CometFilter
Input [1]: [s_store_sk#12]
Condition : isnotnull(s_store_sk#12)

(6) CometColumnarToRow [codegen id : 1]
Input [1]: [s_store_sk#12]

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

(8) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_store_sk#4]
Right keys [1]: [s_store_sk#12]
Join type: Inner
Join condition: None

(9) Project [codegen id : 6]
Output [9]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10]
Input [11]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_store_sk#4, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10, s_store_sk#12]

(10) CometNativeScan parquet spark_catalog.default.customer_address
Output [3]: [ca_address_sk#13, ca_state#14, ca_country#15]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer_address]
PushedFilters: [IsNotNull(ca_country), EqualTo(ca_country,United States), IsNotNull(ca_address_sk)]
ReadSchema: struct<ca_address_sk:int,ca_state:string,ca_country:string>

(11) CometFilter
Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15]
Condition : (((isnotnull(ca_country#15) AND (ca_country#15 = United States)) AND isnotnull(ca_address_sk#13)) AND ((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, ca_state#14, 2, true, false, true) IN (TX,OH) OR staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, ca_state#14, 2, true, false, true) IN (OR,NM,KY)) OR staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, ca_state#14, 2, true, false, true) IN (VA,TX,MS)))

(12) CometProject
Input [3]: [ca_address_sk#13, ca_state#14, ca_country#15]
Arguments: [ca_address_sk#13, ca_state#16], [ca_address_sk#13, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, ca_state#14, 2, true, false, true) AS ca_state#16]

(13) CometColumnarToRow [codegen id : 2]
Input [2]: [ca_address_sk#13, ca_state#16]

(14) BroadcastExchange
Input [2]: [ca_address_sk#13, ca_state#16]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(15) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_addr_sk#3]
Right keys [1]: [ca_address_sk#13]
Join type: Inner
Join condition: ((((ca_state#16 IN (TX,OH) AND (ss_net_profit#9 >= 100.00)) AND (ss_net_profit#9 <= 200.00)) OR ((ca_state#16 IN (OR,NM,KY) AND (ss_net_profit#9 >= 150.00)) AND (ss_net_profit#9 <= 300.00))) OR ((ca_state#16 IN (VA,TX,MS) AND (ss_net_profit#9 >= 50.00)) AND (ss_net_profit#9 <= 250.00)))

(16) Project [codegen id : 6]
Output [7]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_sold_date_sk#10]
Input [11]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_addr_sk#3, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_net_profit#9, ss_sold_date_sk#10, ca_address_sk#13, ca_state#16]

(17) ReusedExchange [Reuses operator id: 41]
Output [1]: [d_date_sk#17]

(18) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_sold_date_sk#10]
Right keys [1]: [d_date_sk#17]
Join type: Inner
Join condition: None

(19) Project [codegen id : 6]
Output [6]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8]
Input [8]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, ss_sold_date_sk#10, d_date_sk#17]

(20) CometNativeScan parquet spark_catalog.default.customer_demographics
Output [3]: [cd_demo_sk#18, cd_marital_status#19, cd_education_status#20]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_marital_status:string,cd_education_status:string>

(21) CometFilter
Input [3]: [cd_demo_sk#18, cd_marital_status#19, cd_education_status#20]
Condition : (isnotnull(cd_demo_sk#18) AND ((((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_marital_status#19, 1, true, false, true) = M) AND (staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_education_status#20, 20, true, false, true) = Advanced Degree     )) OR ((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_marital_status#19, 1, true, false, true) = S) AND (staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_education_status#20, 20, true, false, true) = College             ))) OR ((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_marital_status#19, 1, true, false, true) = W) AND (staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_education_status#20, 20, true, false, true) = 2 yr Degree         ))))

(22) CometProject
Input [3]: [cd_demo_sk#18, cd_marital_status#19, cd_education_status#20]
Arguments: [cd_demo_sk#18, cd_marital_status#21, cd_education_status#22], [cd_demo_sk#18, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_marital_status#19, 1, true, false, true) AS cd_marital_status#21, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_education_status#20, 20, true, false, true) AS cd_education_status#22]

(23) CometColumnarToRow [codegen id : 4]
Input [3]: [cd_demo_sk#18, cd_marital_status#21, cd_education_status#22]

(24) BroadcastExchange
Input [3]: [cd_demo_sk#18, cd_marital_status#21, cd_education_status#22]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(25) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_cdemo_sk#1]
Right keys [1]: [cd_demo_sk#18]
Join type: Inner
Join condition: ((((((cd_marital_status#21 = M) AND (cd_education_status#22 = Advanced Degree     )) AND (ss_sales_price#6 >= 100.00)) AND (ss_sales_price#6 <= 150.00)) OR ((((cd_marital_status#21 = S) AND (cd_education_status#22 = College             )) AND (ss_sales_price#6 >= 50.00)) AND (ss_sales_price#6 <= 100.00))) OR ((((cd_marital_status#21 = W) AND (cd_education_status#22 = 2 yr Degree         )) AND (ss_sales_price#6 >= 150.00)) AND (ss_sales_price#6 <= 200.00)))

(26) Project [codegen id : 6]
Output [7]: [ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_marital_status#21, cd_education_status#22]
Input [9]: [ss_cdemo_sk#1, ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_demo_sk#18, cd_marital_status#21, cd_education_status#22]

(27) CometNativeScan parquet spark_catalog.default.household_demographics
Output [2]: [hd_demo_sk#23, hd_dep_count#24]
Batched: true
Location [not included in comparison]/{warehouse_dir}/household_demographics]
PushedFilters: [IsNotNull(hd_demo_sk), Or(EqualTo(hd_dep_count,3),EqualTo(hd_dep_count,1))]
ReadSchema: struct<hd_demo_sk:int,hd_dep_count:int>

(28) CometFilter
Input [2]: [hd_demo_sk#23, hd_dep_count#24]
Condition : (isnotnull(hd_demo_sk#23) AND ((hd_dep_count#24 = 3) OR (hd_dep_count#24 = 1)))

(29) CometColumnarToRow [codegen id : 5]
Input [2]: [hd_demo_sk#23, hd_dep_count#24]

(30) BroadcastExchange
Input [2]: [hd_demo_sk#23, hd_dep_count#24]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=4]

(31) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_hdemo_sk#2]
Right keys [1]: [hd_demo_sk#23]
Join type: Inner
Join condition: (((((((cd_marital_status#21 = M) AND (cd_education_status#22 = Advanced Degree     )) AND (ss_sales_price#6 >= 100.00)) AND (ss_sales_price#6 <= 150.00)) AND (hd_dep_count#24 = 3)) OR (((((cd_marital_status#21 = S) AND (cd_education_status#22 = College             )) AND (ss_sales_price#6 >= 50.00)) AND (ss_sales_price#6 <= 100.00)) AND (hd_dep_count#24 = 1))) OR (((((cd_marital_status#21 = W) AND (cd_education_status#22 = 2 yr Degree         )) AND (ss_sales_price#6 >= 150.00)) AND (ss_sales_price#6 <= 200.00)) AND (hd_dep_count#24 = 1)))

(32) Project [codegen id : 6]
Output [3]: [ss_quantity#5, ss_ext_sales_price#7, ss_ext_wholesale_cost#8]
Input [9]: [ss_hdemo_sk#2, ss_quantity#5, ss_sales_price#6, ss_ext_sales_price#7, ss_ext_wholesale_cost#8, cd_marital_status#21, cd_education_status#22, hd_demo_sk#23, hd_dep_count#24]

(33) HashAggregate [codegen id : 6]
Input [3]: [ss_quantity#5, ss_ext_sales_price#7, ss_ext_wholesale_cost#8]
Keys: []
Functions [4]: [partial_avg(ss_quantity#5), partial_avg(UnscaledValue(ss_ext_sales_price#7)), partial_avg(UnscaledValue(ss_ext_wholesale_cost#8)), partial_sum(UnscaledValue(ss_ext_wholesale_cost#8))]
Aggregate Attributes [7]: [sum#25, count#26, sum#27, count#28, sum#29, count#30, sum#31]
Results [7]: [sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38]

(34) CometColumnarExchange
Input [7]: [sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(35) CometColumnarToRow [codegen id : 7]
Input [7]: [sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38]

(36) HashAggregate [codegen id : 7]
Input [7]: [sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38]
Keys: []
Functions [4]: [avg(ss_quantity#5), avg(UnscaledValue(ss_ext_sales_price#7)), avg(UnscaledValue(ss_ext_wholesale_cost#8)), sum(UnscaledValue(ss_ext_wholesale_cost#8))]
Aggregate Attributes [4]: [avg(ss_quantity#5)#39, avg(UnscaledValue(ss_ext_sales_price#7))#40, avg(UnscaledValue(ss_ext_wholesale_cost#8))#41, sum(UnscaledValue(ss_ext_wholesale_cost#8))#42]
Results [4]: [avg(ss_quantity#5)#39 AS avg(ss_quantity)#43, cast((avg(UnscaledValue(ss_ext_sales_price#7))#40 / 100.0) as decimal(11,6)) AS avg(ss_ext_sales_price)#44, cast((avg(UnscaledValue(ss_ext_wholesale_cost#8))#41 / 100.0) as decimal(11,6)) AS avg(ss_ext_wholesale_cost)#45, MakeDecimal(sum(UnscaledValue(ss_ext_wholesale_cost#8))#42,17,2) AS sum(ss_ext_wholesale_cost)#46]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#10 IN dynamicpruning#11
BroadcastExchange (41)
+- * CometColumnarToRow (40)
   +- CometProject (39)
      +- CometFilter (38)
         +- CometNativeScan parquet spark_catalog.default.date_dim (37)


(37) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#17, d_year#47]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2001), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(38) CometFilter
Input [2]: [d_date_sk#17, d_year#47]
Condition : ((isnotnull(d_year#47) AND (d_year#47 = 2001)) AND isnotnull(d_date_sk#17))

(39) CometProject
Input [2]: [d_date_sk#17, d_year#47]
Arguments: [d_date_sk#17], [d_date_sk#17]

(40) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#17]

(41) BroadcastExchange
Input [1]: [d_date_sk#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]


