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


(1) Scan parquet default.item
Output [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [Or(And(In(i_category, [Books                                             ,Electronics                                       ,Home                                              ]),In(i_class, [musical                                           ,parenting                                         ,wallpaper                                         ])),And(In(i_category, [Jewelry                                           ,Men                                               ,Shoes                                             ]),In(i_class, [birdal                                            ,pants                                             ,womens                                            ]))), IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_brand:string,i_class:string,i_category:string>

(2) ColumnarToRow [codegen id : 4]
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]

(3) Filter [codegen id : 4]
Input [4]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4]
Condition : (((i_category#4 IN (Home                                              ,Books                                             ,Electronics                                       ) AND i_class#3 IN (wallpaper                                         ,parenting                                         ,musical                                           )) OR (i_category#4 IN (Shoes                                             ,Jewelry                                           ,Men                                               ) AND i_class#3 IN (womens                                            ,birdal                                            ,pants                                             ))) AND isnotnull(i_item_sk#1))

(4) Scan parquet default.store_sales
Output [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#8), (ss_sold_date_sk#8 >= 2451545), (ss_sold_date_sk#8 <= 2451910), dynamicpruningexpression(ss_sold_date_sk#8 IN dynamicpruning#9)]
PushedFilters: [IsNotNull(ss_item_sk), IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_item_sk:int,ss_store_sk:int,ss_sales_price:decimal(7,2)>

(5) ColumnarToRow [codegen id : 1]
Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]

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

(7) BroadcastExchange
Input [4]: [ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [id=#10]

(8) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [i_item_sk#1]
Right keys [1]: [ss_item_sk#5]
Join condition: None

(9) Project [codegen id : 4]
Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]
Input [8]: [i_item_sk#1, i_brand#2, i_class#3, i_category#4, ss_item_sk#5, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8]

(10) ReusedExchange [Reuses operator id: 32]
Output [2]: [d_date_sk#11, d_moy#12]

(11) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_sold_date_sk#8]
Right keys [1]: [d_date_sk#11]
Join condition: None

(12) Project [codegen id : 4]
Output [6]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#12]
Input [8]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, ss_sold_date_sk#8, d_date_sk#11, d_moy#12]

(13) Scan parquet default.store
Output [3]: [s_store_sk#13, s_store_name#14, s_company_name#15]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk)]
ReadSchema: struct<s_store_sk:int,s_store_name:string,s_company_name:string>

(14) ColumnarToRow [codegen id : 3]
Input [3]: [s_store_sk#13, s_store_name#14, s_company_name#15]

(15) Filter [codegen id : 3]
Input [3]: [s_store_sk#13, s_store_name#14, s_company_name#15]
Condition : isnotnull(s_store_sk#13)

(16) BroadcastExchange
Input [3]: [s_store_sk#13, s_store_name#14, s_company_name#15]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [id=#16]

(17) BroadcastHashJoin [codegen id : 4]
Left keys [1]: [ss_store_sk#6]
Right keys [1]: [s_store_sk#13]
Join condition: None

(18) Project [codegen id : 4]
Output [7]: [i_brand#2, i_class#3, i_category#4, ss_sales_price#7, d_moy#12, s_store_name#14, s_company_name#15]
Input [9]: [i_brand#2, i_class#3, i_category#4, ss_store_sk#6, ss_sales_price#7, d_moy#12, s_store_sk#13, s_store_name#14, s_company_name#15]

(19) HashAggregate [codegen id : 4]
Input [7]: [i_brand#2, i_class#3, i_category#4, ss_sales_price#7, d_moy#12, s_store_name#14, s_company_name#15]
Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12]
Functions [1]: [partial_sum(UnscaledValue(ss_sales_price#7))]
Aggregate Attributes [1]: [sum#17]
Results [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum#18]

(20) Exchange
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum#18]
Arguments: hashpartitioning(i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, 5), ENSURE_REQUIREMENTS, [id=#19]

(21) HashAggregate [codegen id : 5]
Input [7]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum#18]
Keys [6]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12]
Functions [1]: [sum(UnscaledValue(ss_sales_price#7))]
Aggregate Attributes [1]: [sum(UnscaledValue(ss_sales_price#7))#20]
Results [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#20,17,2) AS sum_sales#21, MakeDecimal(sum(UnscaledValue(ss_sales_price#7))#20,17,2) AS _w0#22]

(22) Exchange
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, _w0#22]
Arguments: hashpartitioning(i_category#4, i_brand#2, s_store_name#14, s_company_name#15, 5), ENSURE_REQUIREMENTS, [id=#23]

(23) Sort [codegen id : 6]
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, _w0#22]
Arguments: [i_category#4 ASC NULLS FIRST, i_brand#2 ASC NULLS FIRST, s_store_name#14 ASC NULLS FIRST, s_company_name#15 ASC NULLS FIRST], false, 0

(24) Window
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, _w0#22]
Arguments: [avg(_w0#22) windowspecdefinition(i_category#4, i_brand#2, s_store_name#14, s_company_name#15, specifiedwindowframe(RowFrame, unboundedpreceding$(), unboundedfollowing$())) AS avg_monthly_sales#24], [i_category#4, i_brand#2, s_store_name#14, s_company_name#15]

(25) Filter [codegen id : 7]
Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, _w0#22, avg_monthly_sales#24]
Condition : (isnotnull(avg_monthly_sales#24) AND (NOT (avg_monthly_sales#24 = 0.000000) AND (CheckOverflow((promote_precision(abs(CheckOverflow((promote_precision(cast(sum_sales#21 as decimal(22,6))) - promote_precision(cast(avg_monthly_sales#24 as decimal(22,6)))), DecimalType(22,6)))) / promote_precision(cast(avg_monthly_sales#24 as decimal(22,6)))), DecimalType(38,16)) > 0.1000000000000000)))

(26) Project [codegen id : 7]
Output [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, avg_monthly_sales#24]
Input [9]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, _w0#22, avg_monthly_sales#24]

(27) TakeOrderedAndProject
Input [8]: [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, avg_monthly_sales#24]
Arguments: 100, [CheckOverflow((promote_precision(cast(sum_sales#21 as decimal(22,6))) - promote_precision(cast(avg_monthly_sales#24 as decimal(22,6)))), DecimalType(22,6)) ASC NULLS FIRST, s_store_name#14 ASC NULLS FIRST], [i_category#4, i_class#3, i_brand#2, s_store_name#14, s_company_name#15, d_moy#12, sum_sales#21, avg_monthly_sales#24]

===== Subqueries =====

Subquery:1 Hosting operator id = 4 Hosting Expression = ss_sold_date_sk#8 IN dynamicpruning#9
BroadcastExchange (32)
+- * Project (31)
   +- * Filter (30)
      +- * ColumnarToRow (29)
         +- Scan parquet default.date_dim (28)


(28) Scan parquet default.date_dim
Output [3]: [d_date_sk#11, d_year#25, d_moy#12]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_year), EqualTo(d_year,2000), GreaterThanOrEqual(d_date_sk,2451545), LessThanOrEqual(d_date_sk,2451910), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(29) ColumnarToRow [codegen id : 1]
Input [3]: [d_date_sk#11, d_year#25, d_moy#12]

(30) Filter [codegen id : 1]
Input [3]: [d_date_sk#11, d_year#25, d_moy#12]
Condition : ((((isnotnull(d_year#25) AND (d_year#25 = 2000)) AND (d_date_sk#11 >= 2451545)) AND (d_date_sk#11 <= 2451910)) AND isnotnull(d_date_sk#11))

(31) Project [codegen id : 1]
Output [2]: [d_date_sk#11, d_moy#12]
Input [3]: [d_date_sk#11, d_year#25, d_moy#12]

(32) BroadcastExchange
Input [2]: [d_date_sk#11, d_moy#12]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [id=#26]


