== Physical Plan ==
TakeOrderedAndProject (64)
+- * Project (63)
   +- Window (62)
      +- * CometColumnarToRow (61)
         +- CometSort (60)
            +- CometExchange (59)
               +- CometHashAggregate (58)
                  +- CometColumnarExchange (57)
                     +- * HashAggregate (56)
                        +- Union (55)
                           :- * HashAggregate (40)
                           :  +- * CometColumnarToRow (39)
                           :     +- CometColumnarExchange (38)
                           :        +- * HashAggregate (37)
                           :           +- * Project (36)
                           :              +- * BroadcastHashJoin Inner BuildRight (35)
                           :                 :- * Project (6)
                           :                 :  +- * BroadcastHashJoin Inner BuildRight (5)
                           :                 :     :- * Filter (3)
                           :                 :     :  +- * ColumnarToRow (2)
                           :                 :     :     +- Scan parquet spark_catalog.default.store_sales (1)
                           :                 :     +- ReusedExchange (4)
                           :                 +- BroadcastExchange (34)
                           :                    +- * Project (33)
                           :                       +- * BroadcastHashJoin LeftSemi BuildRight (32)
                           :                          :- * CometColumnarToRow (9)
                           :                          :  +- CometFilter (8)
                           :                          :     +- CometNativeScan parquet spark_catalog.default.store (7)
                           :                          +- BroadcastExchange (31)
                           :                             +- * Project (30)
                           :                                +- * Filter (29)
                           :                                   +- Window (28)
                           :                                      +- * Sort (27)
                           :                                         +- * HashAggregate (26)
                           :                                            +- * CometColumnarToRow (25)
                           :                                               +- CometColumnarExchange (24)
                           :                                                  +- * HashAggregate (23)
                           :                                                     +- * Project (22)
                           :                                                        +- * BroadcastHashJoin Inner BuildRight (21)
                           :                                                           :- * Project (19)
                           :                                                           :  +- * BroadcastHashJoin Inner BuildRight (18)
                           :                                                           :     :- * Filter (12)
                           :                                                           :     :  +- * ColumnarToRow (11)
                           :                                                           :     :     +- Scan parquet spark_catalog.default.store_sales (10)
                           :                                                           :     +- BroadcastExchange (17)
                           :                                                           :        +- * CometColumnarToRow (16)
                           :                                                           :           +- CometProject (15)
                           :                                                           :              +- CometFilter (14)
                           :                                                           :                 +- CometNativeScan parquet spark_catalog.default.store (13)
                           :                                                           +- ReusedExchange (20)
                           :- * HashAggregate (47)
                           :  +- * CometColumnarToRow (46)
                           :     +- CometColumnarExchange (45)
                           :        +- * HashAggregate (44)
                           :           +- * HashAggregate (43)
                           :              +- * CometColumnarToRow (42)
                           :                 +- ReusedExchange (41)
                           +- * HashAggregate (54)
                              +- * CometColumnarToRow (53)
                                 +- CometColumnarExchange (52)
                                    +- * HashAggregate (51)
                                       +- * HashAggregate (50)
                                          +- * CometColumnarToRow (49)
                                             +- ReusedExchange (48)


(1) Scan parquet spark_catalog.default.store_sales
Output [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#3), dynamicpruningexpression(ss_sold_date_sk#3 IN dynamicpruning#4)]
PushedFilters: [IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_store_sk:int,ss_net_profit:decimal(7,2)>

(2) ColumnarToRow [codegen id : 8]
Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3]

(3) Filter [codegen id : 8]
Input [3]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3]
Condition : isnotnull(ss_store_sk#1)

(4) ReusedExchange [Reuses operator id: 69]
Output [1]: [d_date_sk#5]

(5) BroadcastHashJoin [codegen id : 8]
Left keys [1]: [ss_sold_date_sk#3]
Right keys [1]: [d_date_sk#5]
Join type: Inner
Join condition: None

(6) Project [codegen id : 8]
Output [2]: [ss_store_sk#1, ss_net_profit#2]
Input [4]: [ss_store_sk#1, ss_net_profit#2, ss_sold_date_sk#3, d_date_sk#5]

(7) CometNativeScan parquet spark_catalog.default.store
Output [3]: [s_store_sk#6, s_county#7, s_state#8]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_county:string,s_state:string>

(8) CometFilter
Input [3]: [s_store_sk#6, s_county#7, s_state#8]
Condition : isnotnull(s_store_sk#6)

(9) CometColumnarToRow [codegen id : 7]
Input [3]: [s_store_sk#6, s_county#7, s_state#8]

(10) Scan parquet spark_catalog.default.store_sales
Output [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#11), dynamicpruningexpression(ss_sold_date_sk#11 IN dynamicpruning#4)]
PushedFilters: [IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_store_sk:int,ss_net_profit:decimal(7,2)>

(11) ColumnarToRow [codegen id : 4]
Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11]

(12) Filter [codegen id : 4]
Input [3]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11]
Condition : isnotnull(ss_store_sk#9)

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

(14) CometFilter
Input [2]: [s_store_sk#12, s_state#13]
Condition : isnotnull(s_store_sk#12)

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

(16) CometColumnarToRow [codegen id : 2]
Input [2]: [s_store_sk#12, s_state#14]

(17) BroadcastExchange
Input [2]: [s_store_sk#12, s_state#14]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=1]

(18) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_store_sk#9]
Right keys [1]: [s_store_sk#12]
Join type: Inner
Join condition: None

(19) Project [codegen id : 4]
Output [3]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14]
Input [5]: [ss_store_sk#9, ss_net_profit#10, ss_sold_date_sk#11, s_store_sk#12, s_state#14]

(20) ReusedExchange [Reuses operator id: 69]
Output [1]: [d_date_sk#15]

(21) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_sold_date_sk#11]
Right keys [1]: [d_date_sk#15]
Join type: Inner
Join condition: None

(22) Project [codegen id : 4]
Output [2]: [ss_net_profit#10, s_state#14]
Input [4]: [ss_net_profit#10, ss_sold_date_sk#11, s_state#14, d_date_sk#15]

(23) HashAggregate [codegen id : 4]
Input [2]: [ss_net_profit#10, s_state#14]
Keys [1]: [s_state#14]
Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#10))]
Aggregate Attributes [1]: [sum#16]
Results [2]: [s_state#14, sum#17]

(24) CometColumnarExchange
Input [2]: [s_state#14, sum#17]
Arguments: hashpartitioning(s_state#14, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=2]

(25) CometColumnarToRow [codegen id : 5]
Input [2]: [s_state#14, sum#17]

(26) HashAggregate [codegen id : 5]
Input [2]: [s_state#14, sum#17]
Keys [1]: [s_state#14]
Functions [1]: [sum(UnscaledValue(ss_net_profit#10))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#10))#18]
Results [3]: [s_state#14, MakeDecimal(sum(UnscaledValue(ss_net_profit#10))#18,17,2) AS _w0#19, s_state#14]

(27) Sort [codegen id : 5]
Input [3]: [s_state#14, _w0#19, s_state#14]
Arguments: [s_state#14 ASC NULLS FIRST, _w0#19 DESC NULLS LAST], false, 0

(28) Window
Input [3]: [s_state#14, _w0#19, s_state#14]
Arguments: [rank(_w0#19) windowspecdefinition(s_state#14, _w0#19 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS ranking#20], [s_state#14], [_w0#19 DESC NULLS LAST]

(29) Filter [codegen id : 6]
Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20]
Condition : (ranking#20 <= 5)

(30) Project [codegen id : 6]
Output [1]: [s_state#14]
Input [4]: [s_state#14, _w0#19, s_state#14, ranking#20]

(31) BroadcastExchange
Input [1]: [s_state#14]
Arguments: HashedRelationBroadcastMode(List(input[0, string, true]),false), [plan_id=3]

(32) BroadcastHashJoin [codegen id : 7]
Left keys [1]: [staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, s_state#8, 2, true, false, true)]
Right keys [1]: [s_state#14]
Join type: LeftSemi
Join condition: None

(33) Project [codegen id : 7]
Output [3]: [s_store_sk#6, s_county#7, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, s_state#8, 2, true, false, true) AS s_state#21]
Input [3]: [s_store_sk#6, s_county#7, s_state#8]

(34) BroadcastExchange
Input [3]: [s_store_sk#6, s_county#7, s_state#21]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]

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

(36) Project [codegen id : 8]
Output [3]: [ss_net_profit#2, s_county#7, s_state#21]
Input [5]: [ss_store_sk#1, ss_net_profit#2, s_store_sk#6, s_county#7, s_state#21]

(37) HashAggregate [codegen id : 8]
Input [3]: [ss_net_profit#2, s_county#7, s_state#21]
Keys [2]: [s_state#21, s_county#7]
Functions [1]: [partial_sum(UnscaledValue(ss_net_profit#2))]
Aggregate Attributes [1]: [sum#22]
Results [3]: [s_state#21, s_county#7, sum#23]

(38) CometColumnarExchange
Input [3]: [s_state#21, s_county#7, sum#23]
Arguments: hashpartitioning(s_state#21, s_county#7, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=5]

(39) CometColumnarToRow [codegen id : 9]
Input [3]: [s_state#21, s_county#7, sum#23]

(40) HashAggregate [codegen id : 9]
Input [3]: [s_state#21, s_county#7, sum#23]
Keys [2]: [s_state#21, s_county#7]
Functions [1]: [sum(UnscaledValue(ss_net_profit#2))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#2))#24]
Results [6]: [cast(MakeDecimal(sum(UnscaledValue(ss_net_profit#2))#24,17,2) as decimal(27,2)) AS total_sum#25, s_state#21 AS s_state#26, s_county#7 AS s_county#27, 0 AS g_state#28, 0 AS g_county#29, 0 AS lochierarchy#30]

(41) ReusedExchange [Reuses operator id: 38]
Output [3]: [s_state#21, s_county#31, sum#32]

(42) CometColumnarToRow [codegen id : 18]
Input [3]: [s_state#21, s_county#31, sum#32]

(43) HashAggregate [codegen id : 18]
Input [3]: [s_state#21, s_county#31, sum#32]
Keys [2]: [s_state#21, s_county#31]
Functions [1]: [sum(UnscaledValue(ss_net_profit#33))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#33))#24]
Results [2]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#33))#24,17,2) AS total_sum#34, s_state#21]

(44) HashAggregate [codegen id : 18]
Input [2]: [total_sum#34, s_state#21]
Keys [1]: [s_state#21]
Functions [1]: [partial_sum(total_sum#34)]
Aggregate Attributes [2]: [sum#35, isEmpty#36]
Results [3]: [s_state#21, sum#37, isEmpty#38]

(45) CometColumnarExchange
Input [3]: [s_state#21, sum#37, isEmpty#38]
Arguments: hashpartitioning(s_state#21, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=6]

(46) CometColumnarToRow [codegen id : 19]
Input [3]: [s_state#21, sum#37, isEmpty#38]

(47) HashAggregate [codegen id : 19]
Input [3]: [s_state#21, sum#37, isEmpty#38]
Keys [1]: [s_state#21]
Functions [1]: [sum(total_sum#34)]
Aggregate Attributes [1]: [sum(total_sum#34)#39]
Results [6]: [sum(total_sum#34)#39 AS total_sum#40, s_state#21, null AS s_county#41, 0 AS g_state#42, 1 AS g_county#43, 1 AS lochierarchy#44]

(48) ReusedExchange [Reuses operator id: 38]
Output [3]: [s_state#21, s_county#45, sum#46]

(49) CometColumnarToRow [codegen id : 28]
Input [3]: [s_state#21, s_county#45, sum#46]

(50) HashAggregate [codegen id : 28]
Input [3]: [s_state#21, s_county#45, sum#46]
Keys [2]: [s_state#21, s_county#45]
Functions [1]: [sum(UnscaledValue(ss_net_profit#47))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_net_profit#47))#24]
Results [1]: [MakeDecimal(sum(UnscaledValue(ss_net_profit#47))#24,17,2) AS total_sum#34]

(51) HashAggregate [codegen id : 28]
Input [1]: [total_sum#34]
Keys: []
Functions [1]: [partial_sum(total_sum#34)]
Aggregate Attributes [2]: [sum#48, isEmpty#49]
Results [2]: [sum#50, isEmpty#51]

(52) CometColumnarExchange
Input [2]: [sum#50, isEmpty#51]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=7]

(53) CometColumnarToRow [codegen id : 29]
Input [2]: [sum#50, isEmpty#51]

(54) HashAggregate [codegen id : 29]
Input [2]: [sum#50, isEmpty#51]
Keys: []
Functions [1]: [sum(total_sum#34)]
Aggregate Attributes [1]: [sum(total_sum#34)#52]
Results [6]: [sum(total_sum#34)#52 AS total_sum#53, null AS s_state#54, null AS s_county#55, 1 AS g_state#56, 1 AS g_county#57, 2 AS lochierarchy#58]

(55) Union

(56) HashAggregate [codegen id : 30]
Input [6]: [total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30]
Keys [6]: [total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30]
Functions: []
Aggregate Attributes: []
Results [6]: [total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30]

(57) CometColumnarExchange
Input [6]: [total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30]
Arguments: hashpartitioning(total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30, 5), ENSURE_REQUIREMENTS, CometColumnarShuffle, [plan_id=8]

(58) CometHashAggregate
Input [6]: [total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30]
Keys [6]: [total_sum#25, s_state#26, s_county#27, g_state#28, g_county#29, lochierarchy#30]
Functions: []

(59) CometExchange
Input [5]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, _w0#59]
Arguments: hashpartitioning(lochierarchy#30, _w0#59, 5), ENSURE_REQUIREMENTS, CometNativeShuffle, [plan_id=9]

(60) CometSort
Input [5]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, _w0#59]
Arguments: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, _w0#59], [lochierarchy#30 ASC NULLS FIRST, _w0#59 ASC NULLS FIRST, total_sum#25 DESC NULLS LAST]

(61) CometColumnarToRow [codegen id : 31]
Input [5]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, _w0#59]

(62) Window
Input [5]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, _w0#59]
Arguments: [rank(total_sum#25) windowspecdefinition(lochierarchy#30, _w0#59, total_sum#25 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rank_within_parent#60], [lochierarchy#30, _w0#59], [total_sum#25 DESC NULLS LAST]

(63) Project [codegen id : 32]
Output [5]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, rank_within_parent#60]
Input [6]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, _w0#59, rank_within_parent#60]

(64) TakeOrderedAndProject
Input [5]: [total_sum#25, s_state#26, s_county#27, lochierarchy#30, rank_within_parent#60]
Arguments: 100, [lochierarchy#30 DESC NULLS LAST, CASE WHEN (lochierarchy#30 = 0) THEN s_state#26 END ASC NULLS FIRST, rank_within_parent#60 ASC NULLS FIRST], [total_sum#25, s_state#26, s_county#27, lochierarchy#30, rank_within_parent#60]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#3 IN dynamicpruning#4
BroadcastExchange (69)
+- * CometColumnarToRow (68)
   +- CometProject (67)
      +- CometFilter (66)
         +- CometNativeScan parquet spark_catalog.default.date_dim (65)


(65) CometNativeScan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#5, d_month_seq#61]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1212), LessThanOrEqual(d_month_seq,1223), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int>

(66) CometFilter
Input [2]: [d_date_sk#5, d_month_seq#61]
Condition : (((isnotnull(d_month_seq#61) AND (d_month_seq#61 >= 1212)) AND (d_month_seq#61 <= 1223)) AND isnotnull(d_date_sk#5))

(67) CometProject
Input [2]: [d_date_sk#5, d_month_seq#61]
Arguments: [d_date_sk#5], [d_date_sk#5]

(68) CometColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#5]

(69) BroadcastExchange
Input [1]: [d_date_sk#5]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=10]

Subquery:2 Hosting operator id = 10 Hosting Expression = ss_sold_date_sk#11 IN dynamicpruning#4


