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


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

(2) ColumnarToRow [codegen id : 4]
Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_sold_date_sk#5]

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

(4) ReusedExchange [Reuses operator id: 40]
Output [1]: [d_date_sk#7]

(5) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_sold_date_sk#5]
Right keys [1]: [d_date_sk#7]
Join type: Inner
Join condition: None

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

(7) CometNativeScan parquet spark_catalog.default.store
Output [2]: [s_store_sk#8, s_county#9]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [In(s_county, [Bronx County,Franklin Parish,Orange County,Williamson County]), IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_county:string>

(8) CometFilter
Input [2]: [s_store_sk#8, s_county#9]
Condition : (s_county#9 IN (Williamson County,Franklin Parish,Bronx County,Orange County) AND isnotnull(s_store_sk#8))

(9) CometProject
Input [2]: [s_store_sk#8, s_county#9]
Arguments: [s_store_sk#8], [s_store_sk#8]

(10) CometColumnarToRow [codegen id : 2]
Input [1]: [s_store_sk#8]

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

(12) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_store_sk#3]
Right keys [1]: [s_store_sk#8]
Join type: Inner
Join condition: None

(13) Project [codegen id : 4]
Output [3]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4]
Input [5]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_store_sk#3, ss_ticket_number#4, s_store_sk#8]

(14) CometNativeScan parquet spark_catalog.default.household_demographics
Output [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/household_demographics]
PushedFilters: [IsNotNull(hd_vehicle_count), GreaterThan(hd_vehicle_count,0), IsNotNull(hd_demo_sk)]
ReadSchema: struct<hd_demo_sk:int,hd_buy_potential:string,hd_dep_count:int,hd_vehicle_count:int>

(15) CometFilter
Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13]
Condition : ((((isnotnull(hd_vehicle_count#13) AND ((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, hd_buy_potential#11, 15, true, false, true) = >10000         ) OR (staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, hd_buy_potential#11, 15, true, false, true) = unknown        ))) AND (hd_vehicle_count#13 > 0)) AND CASE WHEN (hd_vehicle_count#13 > 0) THEN (knownfloatingpointnormalized(normalizenanandzero((cast(hd_dep_count#12 as double) / knownfloatingpointnormalized(normalizenanandzero(cast(hd_vehicle_count#13 as double)))))) > 1.0) END) AND isnotnull(hd_demo_sk#10))

(16) CometProject
Input [4]: [hd_demo_sk#10, hd_buy_potential#11, hd_dep_count#12, hd_vehicle_count#13]
Arguments: [hd_demo_sk#10], [hd_demo_sk#10]

(17) CometColumnarToRow [codegen id : 3]
Input [1]: [hd_demo_sk#10]

(18) BroadcastExchange
Input [1]: [hd_demo_sk#10]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(19) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_hdemo_sk#2]
Right keys [1]: [hd_demo_sk#10]
Join type: Inner
Join condition: None

(20) Project [codegen id : 4]
Output [2]: [ss_customer_sk#1, ss_ticket_number#4]
Input [4]: [ss_customer_sk#1, ss_hdemo_sk#2, ss_ticket_number#4, hd_demo_sk#10]

(21) HashAggregate [codegen id : 4]
Input [2]: [ss_customer_sk#1, ss_ticket_number#4]
Keys [2]: [ss_ticket_number#4, ss_customer_sk#1]
Functions [1]: [partial_count(1)]
Aggregate Attributes [1]: [count#14]
Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15]

(22) CometColumnarExchange
Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15]
Arguments: hashpartitioning(ss_ticket_number#4, ss_customer_sk#1, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=3]

(23) CometColumnarToRow [codegen id : 6]
Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15]

(24) HashAggregate [codegen id : 6]
Input [3]: [ss_ticket_number#4, ss_customer_sk#1, count#15]
Keys [2]: [ss_ticket_number#4, ss_customer_sk#1]
Functions [1]: [count(1)]
Aggregate Attributes [1]: [count(1)#16]
Results [3]: [ss_ticket_number#4, ss_customer_sk#1, count(1)#16 AS cnt#17]

(25) Filter [codegen id : 6]
Input [3]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17]
Condition : ((cnt#17 >= 1) AND (cnt#17 <= 5))

(26) CometNativeScan parquet spark_catalog.default.customer
Output [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer]
PushedFilters: [IsNotNull(c_customer_sk)]
ReadSchema: struct<c_customer_sk:int,c_salutation:string,c_first_name:string,c_last_name:string,c_preferred_cust_flag:string>

(27) CometFilter
Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22]
Condition : isnotnull(c_customer_sk#18)

(28) CometProject
Input [5]: [c_customer_sk#18, c_salutation#19, c_first_name#20, c_last_name#21, c_preferred_cust_flag#22]
Arguments: [c_customer_sk#18, c_salutation#23, c_first_name#24, c_last_name#25, c_preferred_cust_flag#26], [c_customer_sk#18, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, c_salutation#19, 10, true, false, true) AS c_salutation#23, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, c_first_name#20, 20, true, false, true) AS c_first_name#24, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, c_last_name#21, 30, true, false, true) AS c_last_name#25, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, c_preferred_cust_flag#22, 1, true, false, true) AS c_preferred_cust_flag#26]

(29) CometColumnarToRow [codegen id : 5]
Input [5]: [c_customer_sk#18, c_salutation#23, c_first_name#24, c_last_name#25, c_preferred_cust_flag#26]

(30) BroadcastExchange
Input [5]: [c_customer_sk#18, c_salutation#23, c_first_name#24, c_last_name#25, c_preferred_cust_flag#26]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]

(31) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_customer_sk#1]
Right keys [1]: [c_customer_sk#18]
Join type: Inner
Join condition: None

(32) Project [codegen id : 6]
Output [6]: [c_last_name#25, c_first_name#24, c_salutation#23, c_preferred_cust_flag#26, ss_ticket_number#4, cnt#17]
Input [8]: [ss_ticket_number#4, ss_customer_sk#1, cnt#17, c_customer_sk#18, c_salutation#23, c_first_name#24, c_last_name#25, c_preferred_cust_flag#26]

(33) CometColumnarExchange
Input [6]: [c_last_name#25, c_first_name#24, c_salutation#23, c_preferred_cust_flag#26, ss_ticket_number#4, cnt#17]
Arguments: rangepartitioning(cnt#17 DESC NULLS LAST, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(34) CometSort
Input [6]: [c_last_name#25, c_first_name#24, c_salutation#23, c_preferred_cust_flag#26, ss_ticket_number#4, cnt#17]
Arguments: [c_last_name#25, c_first_name#24, c_salutation#23, c_preferred_cust_flag#26, ss_ticket_number#4, cnt#17], [cnt#17 DESC NULLS LAST]

(35) CometColumnarToRow [codegen id : 7]
Input [6]: [c_last_name#25, c_first_name#24, c_salutation#23, c_preferred_cust_flag#26, ss_ticket_number#4, cnt#17]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
BroadcastExchange (40)
+- * CometColumnarToRow (39)
   +- CometProject (38)
      +- CometFilter (37)
         +- CometNativeScan parquet spark_catalog.default.date_dim (36)


(36) CometNativeScan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#7, d_year#27, d_dom#28]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_dom), GreaterThanOrEqual(d_dom,1), LessThanOrEqual(d_dom,2), In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_dom:int>

(37) CometFilter
Input [3]: [d_date_sk#7, d_year#27, d_dom#28]
Condition : ((((isnotnull(d_dom#28) AND (d_dom#28 >= 1)) AND (d_dom#28 <= 2)) AND d_year#27 IN (1999,2000,2001)) AND isnotnull(d_date_sk#7))

(38) CometProject
Input [3]: [d_date_sk#7, d_year#27, d_dom#28]
Arguments: [d_date_sk#7], [d_date_sk#7]

(39) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#7]

(40) BroadcastExchange
Input [1]: [d_date_sk#7]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=6]


