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


(1) Scan parquet spark_catalog.default.store_sales
Output [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#8), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)]
PushedFilters: [IsNotNull(ss_cdemo_sk), IsNotNull(ss_store_sk), IsNotNull(ss_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_cdemo_sk:int,ss_store_sk:int,ss_quantity:int,ss_list_price:decimal(7,2),ss_sales_price:decimal(7,2),ss_coupon_amt:decimal(7,2)>

(2) ColumnarToRow [codegen id : 5]
Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]

(3) Filter [codegen id : 5]
Input [8]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Condition : ((isnotnull(ss_cdemo_sk#2) AND isnotnull(ss_store_sk#3)) AND isnotnull(ss_item_sk#1))

(4) CometNativeScan parquet spark_catalog.default.customer_demographics
Output [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Batched: true
Location [not included in comparison]/{warehouse_dir}/customer_demographics]
PushedFilters: [IsNotNull(cd_demo_sk)]
ReadSchema: struct<cd_demo_sk:int,cd_gender:string,cd_marital_status:string,cd_education_status:string>

(5) CometFilter
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Condition : ((((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_gender#11, 1, true, false, true) = M) AND (staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_marital_status#12, 1, true, false, true) = S)) AND (staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, cd_education_status#13, 20, true, false, true) = College             )) AND isnotnull(cd_demo_sk#10))

(6) CometProject
Input [4]: [cd_demo_sk#10, cd_gender#11, cd_marital_status#12, cd_education_status#13]
Arguments: [cd_demo_sk#10], [cd_demo_sk#10]

(7) CometColumnarToRow [codegen id : 1]
Input [1]: [cd_demo_sk#10]

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

(9) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_cdemo_sk#2]
Right keys [1]: [cd_demo_sk#10]
Join type: Inner
Join condition: None

(10) Project [codegen id : 5]
Output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8]
Input [9]: [ss_item_sk#1, ss_cdemo_sk#2, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, cd_demo_sk#10]

(11) ReusedExchange [Reuses operator id: 38]
Output [1]: [d_date_sk#14]

(12) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_sold_date_sk#8]
Right keys [1]: [d_date_sk#14]
Join type: Inner
Join condition: None

(13) Project [codegen id : 5]
Output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7]
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, ss_sold_date_sk#8, d_date_sk#14]

(14) CometNativeScan parquet spark_catalog.default.store
Output [2]: [s_store_sk#15, s_state#16]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_state:string>

(15) CometFilter
Input [2]: [s_store_sk#15, s_state#16]
Condition : ((staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, s_state#16, 2, true, false, true) = TN) AND isnotnull(s_store_sk#15))

(16) CometProject
Input [2]: [s_store_sk#15, s_state#16]
Arguments: [s_store_sk#15, s_state#17], [s_store_sk#15, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, s_state#16, 2, true, false, true) AS s_state#17]

(17) CometColumnarToRow [codegen id : 3]
Input [2]: [s_store_sk#15, s_state#17]

(18) BroadcastExchange
Input [2]: [s_store_sk#15, s_state#17]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

(19) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_store_sk#3]
Right keys [1]: [s_store_sk#15]
Join type: Inner
Join condition: None

(20) Project [codegen id : 5]
Output [6]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#17]
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_store_sk#15, s_state#17]

(21) CometNativeScan parquet spark_catalog.default.item
Output [2]: [i_item_sk#18, i_item_id#19]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string>

(22) CometFilter
Input [2]: [i_item_sk#18, i_item_id#19]
Condition : isnotnull(i_item_sk#18)

(23) CometProject
Input [2]: [i_item_sk#18, i_item_id#19]
Arguments: [i_item_sk#18, i_item_id#20], [i_item_sk#18, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_item_id#19, 16, true, false, true) AS i_item_id#20]

(24) CometColumnarToRow [codegen id : 4]
Input [2]: [i_item_sk#18, i_item_id#20]

(25) BroadcastExchange
Input [2]: [i_item_sk#18, i_item_id#20]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

(26) BroadcastHashJoin [codegen id : 5]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#18]
Join type: Inner
Join condition: None

(27) Project [codegen id : 5]
Output [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#20, s_state#17]
Input [8]: [ss_item_sk#1, ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, s_state#17, i_item_sk#18, i_item_id#20]

(28) Expand [codegen id : 5]
Input [6]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#20, s_state#17]
Arguments: [[ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#20, s_state#17, 0], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#20, null, 1], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, null, null, 3]], [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#21, s_state#22, spark_grouping_id#23]

(29) HashAggregate [codegen id : 5]
Input [7]: [ss_quantity#4, ss_list_price#5, ss_sales_price#6, ss_coupon_amt#7, i_item_id#21, s_state#22, spark_grouping_id#23]
Keys [3]: [i_item_id#21, s_state#22, spark_grouping_id#23]
Functions [4]: [partial_avg(ss_quantity#4), partial_avg(UnscaledValue(ss_list_price#5)), partial_avg(UnscaledValue(ss_coupon_amt#7)), partial_avg(UnscaledValue(ss_sales_price#6))]
Aggregate Attributes [8]: [sum#24, count#25, sum#26, count#27, sum#28, count#29, sum#30, count#31]
Results [11]: [i_item_id#21, s_state#22, spark_grouping_id#23, sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38, count#39]

(30) CometColumnarExchange
Input [11]: [i_item_id#21, s_state#22, spark_grouping_id#23, sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38, count#39]
Arguments: hashpartitioning(i_item_id#21, s_state#22, spark_grouping_id#23, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=4]

(31) CometColumnarToRow [codegen id : 6]
Input [11]: [i_item_id#21, s_state#22, spark_grouping_id#23, sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38, count#39]

(32) HashAggregate [codegen id : 6]
Input [11]: [i_item_id#21, s_state#22, spark_grouping_id#23, sum#32, count#33, sum#34, count#35, sum#36, count#37, sum#38, count#39]
Keys [3]: [i_item_id#21, s_state#22, spark_grouping_id#23]
Functions [4]: [avg(ss_quantity#4), avg(UnscaledValue(ss_list_price#5)), avg(UnscaledValue(ss_coupon_amt#7)), avg(UnscaledValue(ss_sales_price#6))]
Aggregate Attributes [4]: [avg(ss_quantity#4)#40, avg(UnscaledValue(ss_list_price#5))#41, avg(UnscaledValue(ss_coupon_amt#7))#42, avg(UnscaledValue(ss_sales_price#6))#43]
Results [7]: [i_item_id#21, s_state#22, cast((shiftright(spark_grouping_id#23, 0) & 1) as tinyint) AS g_state#44, avg(ss_quantity#4)#40 AS agg1#45, cast((avg(UnscaledValue(ss_list_price#5))#41 / 100.0) as decimal(11,6)) AS agg2#46, cast((avg(UnscaledValue(ss_coupon_amt#7))#42 / 100.0) as decimal(11,6)) AS agg3#47, cast((avg(UnscaledValue(ss_sales_price#6))#43 / 100.0) as decimal(11,6)) AS agg4#48]

(33) TakeOrderedAndProject
Input [7]: [i_item_id#21, s_state#22, g_state#44, agg1#45, agg2#46, agg3#47, agg4#48]
Arguments: 100, [i_item_id#21 ASC NULLS FIRST, s_state#22 ASC NULLS FIRST], [i_item_id#21, s_state#22, g_state#44, agg1#45, agg2#46, agg3#47, agg4#48]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9
BroadcastExchange (38)
+- * CometColumnarToRow (37)
   +- CometProject (36)
      +- CometFilter (35)
         +- CometNativeScan parquet spark_catalog.default.date_dim (34)


(34) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#14, d_year#49]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2002), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(35) CometFilter
Input [2]: [d_date_sk#14, d_year#49]
Condition : ((isnotnull(d_year#49) AND (d_year#49 = 2002)) AND isnotnull(d_date_sk#14))

(36) CometProject
Input [2]: [d_date_sk#14, d_year#49]
Arguments: [d_date_sk#14], [d_date_sk#14]

(37) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#14]

(38) BroadcastExchange
Input [1]: [d_date_sk#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=5]


