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


(1) Scan parquet 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) ColumnarToRow [codegen id : 3]
Input [5]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, ss_sold_date_sk#5]

(3) Filter [codegen id : 3]
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))

(4) ReusedExchange [Reuses operator id: 35]
Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10]

(5) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [ss_sold_date_sk#5]
Right keys [1]: [d_date_sk#7]
Join condition: None

(6) Project [codegen id : 3]
Output [7]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10]
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#8, d_moy#9, d_qoy#10]

(7) Scan parquet default.store
Output [2]: [s_store_sk#11, s_store_id#12]
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>

(8) ColumnarToRow [codegen id : 2]
Input [2]: [s_store_sk#11, s_store_id#12]

(9) Filter [codegen id : 2]
Input [2]: [s_store_sk#11, s_store_id#12]
Condition : isnotnull(s_store_sk#11)

(10) BroadcastExchange
Input [2]: [s_store_sk#11, s_store_id#12]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [id=#13]

(11) BroadcastHashJoin [codegen id : 3]
Left keys [1]: [ss_store_sk#2]
Right keys [1]: [s_store_sk#11]
Join condition: None

(12) Project [codegen id : 3]
Output [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12]
Input [9]: [ss_item_sk#1, ss_store_sk#2, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_sk#11, s_store_id#12]

(13) Exchange
Input [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12]
Arguments: hashpartitioning(ss_item_sk#1, 5), ENSURE_REQUIREMENTS, [id=#14]

(14) Sort [codegen id : 4]
Input [7]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12]
Arguments: [ss_item_sk#1 ASC NULLS FIRST], false, 0

(15) Scan parquet 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) ColumnarToRow [codegen id : 5]
Input [5]: [i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]

(17) Filter [codegen id : 5]
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)

(18) Exchange
Input [5]: [i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]
Arguments: hashpartitioning(i_item_sk#15, 5), ENSURE_REQUIREMENTS, [id=#20]

(19) Sort [codegen id : 6]
Input [5]: [i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]
Arguments: [i_item_sk#15 ASC NULLS FIRST], false, 0

(20) SortMergeJoin [codegen id : 7]
Left keys [1]: [ss_item_sk#1]
Right keys [1]: [i_item_sk#15]
Join condition: None

(21) Project [codegen id : 7]
Output [10]: [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, d_year#8, d_qoy#10, d_moy#9, s_store_id#12]
Input [12]: [ss_item_sk#1, ss_quantity#3, ss_sales_price#4, d_year#8, d_moy#9, d_qoy#10, s_store_id#12, i_item_sk#15, i_brand#16, i_class#17, i_category#18, i_product_name#19]

(22) Expand [codegen id : 7]
Input [10]: [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, d_year#8, d_qoy#10, d_moy#9, s_store_id#12]
Arguments: [[ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, d_year#8, d_qoy#10, d_moy#9, s_store_id#12, 0], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, d_year#8, d_qoy#10, d_moy#9, null, 1], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, d_year#8, d_qoy#10, null, null, 3], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, d_year#8, null, null, null, 7], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, i_product_name#19, null, null, null, null, 15], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, i_brand#16, null, null, null, null, null, 31], [ss_quantity#3, ss_sales_price#4, i_category#18, i_class#17, null, null, null, null, null, null, 63], [ss_quantity#3, ss_sales_price#4, i_category#18, 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#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29]

(23) HashAggregate [codegen id : 7]
Input [11]: [ss_quantity#3, ss_sales_price#4, i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29]
Keys [9]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29]
Functions [1]: [partial_sum(coalesce(CheckOverflow((promote_precision(cast(ss_sales_price#4 as decimal(12,2))) * promote_precision(cast(ss_quantity#3 as decimal(12,2)))), DecimalType(18,2)), 0.00))]
Aggregate Attributes [2]: [sum#30, isEmpty#31]
Results [11]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29, sum#32, isEmpty#33]

(24) Exchange
Input [11]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29, sum#32, isEmpty#33]
Arguments: hashpartitioning(i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29, 5), ENSURE_REQUIREMENTS, [id=#34]

(25) HashAggregate [codegen id : 8]
Input [11]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29, sum#32, isEmpty#33]
Keys [9]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, spark_grouping_id#29]
Functions [1]: [sum(coalesce(CheckOverflow((promote_precision(cast(ss_sales_price#4 as decimal(12,2))) * promote_precision(cast(ss_quantity#3 as decimal(12,2)))), DecimalType(18,2)), 0.00))]
Aggregate Attributes [1]: [sum(coalesce(CheckOverflow((promote_precision(cast(ss_sales_price#4 as decimal(12,2))) * promote_precision(cast(ss_quantity#3 as decimal(12,2)))), DecimalType(18,2)), 0.00))#35]
Results [9]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sum(coalesce(CheckOverflow((promote_precision(cast(ss_sales_price#4 as decimal(12,2))) * promote_precision(cast(ss_quantity#3 as decimal(12,2)))), DecimalType(18,2)), 0.00))#35 AS sumsales#36]

(26) Exchange
Input [9]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sumsales#36]
Arguments: hashpartitioning(i_category#21, 5), ENSURE_REQUIREMENTS, [id=#37]

(27) Sort [codegen id : 9]
Input [9]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sumsales#36]
Arguments: [i_category#21 ASC NULLS FIRST, sumsales#36 DESC NULLS LAST], false, 0

(28) Window
Input [9]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sumsales#36]
Arguments: [rank(sumsales#36) windowspecdefinition(i_category#21, sumsales#36 DESC NULLS LAST, specifiedwindowframe(RowFrame, unboundedpreceding$(), currentrow$())) AS rk#38], [i_category#21], [sumsales#36 DESC NULLS LAST]

(29) Filter [codegen id : 10]
Input [10]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sumsales#36, rk#38]
Condition : (rk#38 <= 100)

(30) TakeOrderedAndProject
Input [10]: [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sumsales#36, rk#38]
Arguments: 100, [i_category#21 ASC NULLS FIRST, i_class#22 ASC NULLS FIRST, i_brand#23 ASC NULLS FIRST, i_product_name#24 ASC NULLS FIRST, d_year#25 ASC NULLS FIRST, d_qoy#26 ASC NULLS FIRST, d_moy#27 ASC NULLS FIRST, s_store_id#28 ASC NULLS FIRST, sumsales#36 ASC NULLS FIRST, rk#38 ASC NULLS FIRST], [i_category#21, i_class#22, i_brand#23, i_product_name#24, d_year#25, d_qoy#26, d_moy#27, s_store_id#28, sumsales#36, rk#38]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#5 IN dynamicpruning#6
BroadcastExchange (35)
+- * Project (34)
   +- * Filter (33)
      +- * ColumnarToRow (32)
         +- Scan parquet default.date_dim (31)


(31) Scan parquet default.date_dim
Output [5]: [d_date_sk#7, d_month_seq#39, d_year#8, d_moy#9, d_qoy#10]
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) ColumnarToRow [codegen id : 1]
Input [5]: [d_date_sk#7, d_month_seq#39, d_year#8, d_moy#9, d_qoy#10]

(33) Filter [codegen id : 1]
Input [5]: [d_date_sk#7, d_month_seq#39, d_year#8, d_moy#9, d_qoy#10]
Condition : (((isnotnull(d_month_seq#39) AND (d_month_seq#39 >= 1200)) AND (d_month_seq#39 <= 1211)) AND isnotnull(d_date_sk#7))

(34) Project [codegen id : 1]
Output [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10]
Input [5]: [d_date_sk#7, d_month_seq#39, d_year#8, d_moy#9, d_qoy#10]

(35) BroadcastExchange
Input [4]: [d_date_sk#7, d_year#8, d_moy#9, d_qoy#10]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [id=#40]


