== Physical Plan ==
TakeOrderedAndProject (30)
+- * Filter (29)
   +- Window (28)
      +- * CometColumnarToRow (27)
         +- CometSort (26)
            +- CometExchange (25)
               +- CometHashAggregate (24)
                  +- CometExchange (23)
                     +- CometHashAggregate (22)
                        +- CometExpand (21)
                           +- CometProject (20)
                              +- CometBroadcastHashJoin (19)
                                 :- CometProject (14)
                                 :  +- CometBroadcastHashJoin (13)
                                 :     :- CometProject (8)
                                 :     :  +- CometBroadcastHashJoin (7)
                                 :     :     :- CometFilter (2)
                                 :     :     :  +- CometScan [native_iceberg_compat] parquet spark_catalog.default.store_sales (1)
                                 :     :     +- CometBroadcastExchange (6)
                                 :     :        +- CometProject (5)
                                 :     :           +- CometFilter (4)
                                 :     :              +- CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim (3)
                                 :     +- CometBroadcastExchange (12)
                                 :        +- CometProject (11)
                                 :           +- CometFilter (10)
                                 :              +- CometScan [native_iceberg_compat] parquet spark_catalog.default.store (9)
                                 +- CometBroadcastExchange (18)
                                    +- CometProject (17)
                                       +- CometFilter (16)
                                          +- CometScan [native_iceberg_compat] parquet spark_catalog.default.item (15)


(1) CometScan [native_iceberg_compat] parquet spark_catalog.default.store_sales
Output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#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_item_sk)]
ReadSchema: struct<ss_item_sk:int,ss_store_sk:int,ss_quantity:int,ss_sales_price:decimal(7,2)>

(2) CometFilter
Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5]
Condition : (isnotnull(ss_store_sk#2) AND isnotnull(ss_item_sk#1))

(3) CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim
Output [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int,d_year:int,d_moy:int,d_qoy:int>

(4) CometFilter
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Condition : (((isnotnull(d_month_seq#8) AND (d_month_seq#8 >= 1200)) AND (d_month_seq#8 <= 1211)) AND isnotnull(d_date_sk#7))

(5) CometProject
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Arguments: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11], [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(6) CometBroadcastExchange
Input [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(7) CometBroadcastHashJoin
Left output [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5]
Right output [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: [ss_sold_date_sk#5], [d_date_sk#7], Inner, BuildRight

(8) CometProject
Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5, d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11], [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11]

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

(10) CometFilter
Input [2]: [s_store_sk#12, s_store_id#13]
Condition : isnotnull(s_store_sk#12)

(11) CometProject
Input [2]: [s_store_sk#12, s_store_id#13]
Arguments: [s_store_sk#12, s_store_id#14], [s_store_sk#12, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, s_store_id#13, 16, true, false, true) AS s_store_id#14]

(12) CometBroadcastExchange
Input [2]: [s_store_sk#12, s_store_id#14]
Arguments: [s_store_sk#12, s_store_id#14]

(13) CometBroadcastHashJoin
Left output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11]
Right output [2]: [s_store_sk#12, s_store_id#14]
Arguments: [ss_store_sk#2], [s_store_sk#12], Inner, BuildRight

(14) CometProject
Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_sk#12, s_store_id#14]
Arguments: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#14], [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#14]

(15) CometScan [native_iceberg_compat] parquet spark_catalog.default.item
Output [5]: [i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand:string,i_class:string,i_category:string,i_product_name:string>

(16) CometFilter
Input [5]: [i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]
Condition : isnotnull(i_item_sk#15)

(17) CometProject
Input [5]: [i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]
Arguments: [i_item_sk#15, i_brand#20, i_class#21, i_category#22, i_product_name#23], [i_item_sk#15, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_brand#16, 50, true, false, true) AS i_brand#20, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_class#17, 50, true, false, true) AS i_class#21, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_category#18, 50, true, false, true) AS i_category#22, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, i_product_name#19, 50, true, false, true) AS i_product_name#23]

(18) CometBroadcastExchange
Input [5]: [i_item_sk#15, i_brand#20, i_class#21, i_category#22, i_product_name#23]
Arguments: [i_item_sk#15, i_brand#20, i_class#21, i_category#22, i_product_name#23]

(19) CometBroadcastHashJoin
Left output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#14]
Right output [5]: [i_item_sk#15, i_brand#20, i_class#21, i_category#22, i_product_name#23]
Arguments: [ss_item_sk#1], [i_item_sk#15], Inner, BuildRight

(20) CometProject
Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#9, d_moy#10, d_qoy#11, s_store_id#14, i_item_sk#15, i_brand#20, i_class#21, i_category#22, i_product_name#23]
Arguments: [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, d_qoy#11, d_moy#10, s_store_id#14], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, d_qoy#11, d_moy#10, s_store_id#14]

(21) CometExpand
Input [10]: [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, d_qoy#11, d_moy#10, s_store_id#14]
Arguments: [[ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, d_qoy#11, d_moy#10, s_store_id#14, 0], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, d_qoy#11, d_moy#10, null, 1], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, d_qoy#11, null, null, 3], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, d_year#9, null, null, null, 7], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, i_product_name#23, null, null, null, null, 15], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, i_brand#20, null, null, null, null, null, 31], [ss_quantity#3, ss_sales_price#4, i_category#22, i_class#21, null, null, null, null, null, null, 63], [ss_quantity#3, ss_sales_price#4, i_category#22, null, null, null, null, null, null, null, 127], [ss_quantity#3, ss_sales_price#4, null, null, null, null, null, null, null, null, 255]], [ss_quantity#3, ss_sales_price#4, i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32]

(22) CometHashAggregate
Input [11]: [ss_quantity#3, ss_sales_price#4, i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32]
Keys [9]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32]
Functions [1]: [partial_sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))]

(23) CometExchange
Input [11]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32, sum#33, isEmpty#34]
Arguments: hashpartitioning(i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32, 5), ENSURE_REQUIREMENTS, CometNativeShuffle, [plan_id=1]

(24) CometHashAggregate
Input [11]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32, sum#33, isEmpty#34]
Keys [9]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, spark_grouping_id#32]
Functions [1]: [sum(coalesce((ss_sales_price#4 * cast(ss_quantity#3 as decimal(10,0))), 0.00))]

(25) CometExchange
Input [9]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35]
Arguments: hashpartitioning(i_category#24, 5), ENSURE_REQUIREMENTS, CometNativeShuffle, [plan_id=2]

(26) CometSort
Input [9]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35]
Arguments: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35], [i_category#24 ASC NULLS FIRST, sumsales#35 DESC NULLS LAST]

(27) CometColumnarToRow [codegen id : 1]
Input [9]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35]

(28) Window
Input [9]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35]
Arguments: [rank(sumsales#35) windowspecdefinition(i_category#24, sumsales#35 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#36], [i_category#24], [sumsales#35 DESC NULLS LAST]

(29) Filter [codegen id : 2]
Input [10]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35, rk#36]
Condition : (rk#36 <= 100)

(30) TakeOrderedAndProject
Input [10]: [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35, rk#36]
Arguments: 100, [i_category#24 ASC NULLS FIRST, i_class#25 ASC NULLS FIRST, i_brand#26 ASC NULLS FIRST, i_product_name#27 ASC NULLS FIRST, d_year#28 ASC NULLS FIRST, d_qoy#29 ASC NULLS FIRST, d_moy#30 ASC NULLS FIRST, s_store_id#31 ASC NULLS FIRST, sumsales#35 ASC NULLS FIRST, rk#36 ASC NULLS FIRST], [i_category#24, i_class#25, i_brand#26, i_product_name#27, d_year#28, d_qoy#29, d_moy#30, s_store_id#31, sumsales#35, rk#36]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
BroadcastExchange (35)
+- * CometColumnarToRow (34)
   +- CometProject (33)
      +- CometFilter (32)
         +- CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim (31)


(31) CometScan [native_iceberg_compat] parquet spark_catalog.default.date_dim
Output [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1200), LessThanOrEqual(d_month_seq,1211), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_month_seq:int,d_year:int,d_moy:int,d_qoy:int>

(32) CometFilter
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Condition : (((isnotnull(d_month_seq#8) AND (d_month_seq#8 >= 1200)) AND (d_month_seq#8 <= 1211)) AND isnotnull(d_date_sk#7))

(33) CometProject
Input [5]: [d_date_sk#7, d_month_seq#8, d_year#9, d_moy#10, d_qoy#11]
Arguments: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11], [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(34) CometColumnarToRow [codegen id : 1]
Input [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]

(35) BroadcastExchange
Input [4]: [d_date_sk#7, d_year#9, d_moy#10, d_qoy#11]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]


