== Physical Plan ==
TakeOrderedAndProject (51)
+- * Project (50)
   +- * BroadcastHashJoin Inner BuildRight (49)
      :- * Project (25)
      :  +- * BroadcastHashJoin Inner BuildRight (24)
      :     :- * Project (18)
      :     :  +- * BroadcastHashJoin Inner BuildRight (17)
      :     :     :- * HashAggregate (12)
      :     :     :  +- Exchange (11)
      :     :     :     +- * HashAggregate (10)
      :     :     :        +- * Project (9)
      :     :     :           +- * BroadcastHashJoin Inner BuildRight (8)
      :     :     :              :- * Filter (3)
      :     :     :              :  +- * ColumnarToRow (2)
      :     :     :              :     +- Scan parquet spark_catalog.default.store_sales (1)
      :     :     :              +- BroadcastExchange (7)
      :     :     :                 +- * Filter (6)
      :     :     :                    +- * ColumnarToRow (5)
      :     :     :                       +- Scan parquet spark_catalog.default.date_dim (4)
      :     :     +- BroadcastExchange (16)
      :     :        +- * Filter (15)
      :     :           +- * ColumnarToRow (14)
      :     :              +- Scan parquet spark_catalog.default.store (13)
      :     +- BroadcastExchange (23)
      :        +- * Project (22)
      :           +- * Filter (21)
      :              +- * ColumnarToRow (20)
      :                 +- Scan parquet spark_catalog.default.date_dim (19)
      +- BroadcastExchange (48)
         +- * Project (47)
            +- * BroadcastHashJoin Inner BuildRight (46)
               :- * Project (40)
               :  +- * BroadcastHashJoin Inner BuildRight (39)
               :     :- * HashAggregate (34)
               :     :  +- Exchange (33)
               :     :     +- * HashAggregate (32)
               :     :        +- * Project (31)
               :     :           +- * BroadcastHashJoin Inner BuildRight (30)
               :     :              :- * Filter (28)
               :     :              :  +- * ColumnarToRow (27)
               :     :              :     +- Scan parquet spark_catalog.default.store_sales (26)
               :     :              +- ReusedExchange (29)
               :     +- BroadcastExchange (38)
               :        +- * Filter (37)
               :           +- * ColumnarToRow (36)
               :              +- Scan parquet spark_catalog.default.store (35)
               +- BroadcastExchange (45)
                  +- * Project (44)
                     +- * Filter (43)
                        +- * ColumnarToRow (42)
                           +- Scan parquet spark_catalog.default.date_dim (41)


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

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

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

(4) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_date_sk), IsNotNull(d_week_seq)]
ReadSchema: struct<d_date_sk:int,d_week_seq:int,d_day_name:string>

(5) ColumnarToRow [codegen id : 1]
Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6]

(6) Filter [codegen id : 1]
Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6]
Condition : (isnotnull(d_date_sk#4) AND isnotnull(d_week_seq#5))

(7) BroadcastExchange
Input [3]: [d_date_sk#4, d_week_seq#5, d_day_name#6]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=1]

(8) BroadcastHashJoin [codegen id : 2]
Left keys [1]: [ss_sold_date_sk#3]
Right keys [1]: [d_date_sk#4]
Join type: Inner
Join condition: None

(9) Project [codegen id : 2]
Output [4]: [ss_store_sk#1, ss_sales_price#2, d_week_seq#5, d_day_name#6]
Input [6]: [ss_store_sk#1, ss_sales_price#2, ss_sold_date_sk#3, d_date_sk#4, d_week_seq#5, d_day_name#6]

(10) HashAggregate [codegen id : 2]
Input [4]: [ss_store_sk#1, ss_sales_price#2, d_week_seq#5, d_day_name#6]
Keys [2]: [d_week_seq#5, ss_store_sk#1]
Functions [7]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday   ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday   ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday  ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday   ) THEN ss_sales_price#2 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))]
Aggregate Attributes [7]: [sum#7, sum#8, sum#9, sum#10, sum#11, sum#12, sum#13]
Results [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20]

(11) Exchange
Input [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20]
Arguments: hashpartitioning(d_week_seq#5, ss_store_sk#1, 5), ENSURE_REQUIREMENTS, [plan_id=2]

(12) HashAggregate [codegen id : 10]
Input [9]: [d_week_seq#5, ss_store_sk#1, sum#14, sum#15, sum#16, sum#17, sum#18, sum#19, sum#20]
Keys [2]: [d_week_seq#5, ss_store_sk#1]
Functions [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday   ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday   ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday  ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday   ) THEN ss_sales_price#2 END)), sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))]
Aggregate Attributes [7]: [sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday   ) THEN ss_sales_price#2 END))#21, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday   ) THEN ss_sales_price#2 END))#22, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday  ) THEN ss_sales_price#2 END))#23, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END))#24, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday   ) THEN ss_sales_price#2 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))#27]
Results [9]: [d_week_seq#5, ss_store_sk#1, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Sunday   ) THEN ss_sales_price#2 END))#21,17,2) AS sun_sales#28, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Monday   ) THEN ss_sales_price#2 END))#22,17,2) AS mon_sales#29, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Tuesday  ) THEN ss_sales_price#2 END))#23,17,2) AS tue_sales#30, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Wednesday) THEN ss_sales_price#2 END))#24,17,2) AS wed_sales#31, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Thursday ) THEN ss_sales_price#2 END))#25,17,2) AS thu_sales#32, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Friday   ) THEN ss_sales_price#2 END))#26,17,2) AS fri_sales#33, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#6 = Saturday ) THEN ss_sales_price#2 END))#27,17,2) AS sat_sales#34]

(13) Scan parquet spark_catalog.default.store
Output [3]: [s_store_sk#35, s_store_id#36, s_store_name#37]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)]
ReadSchema: struct<s_store_sk:int,s_store_id:string,s_store_name:string>

(14) ColumnarToRow [codegen id : 3]
Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37]

(15) Filter [codegen id : 3]
Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37]
Condition : (isnotnull(s_store_sk#35) AND isnotnull(s_store_id#36))

(16) BroadcastExchange
Input [3]: [s_store_sk#35, s_store_id#36, s_store_name#37]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=3]

(17) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [ss_store_sk#1]
Right keys [1]: [s_store_sk#35]
Join type: Inner
Join condition: None

(18) Project [codegen id : 10]
Output [10]: [d_week_seq#5, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_id#36, s_store_name#37]
Input [12]: [d_week_seq#5, ss_store_sk#1, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_sk#35, s_store_id#36, s_store_name#37]

(19) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_month_seq#38, d_week_seq#39]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1185), LessThanOrEqual(d_month_seq,1196), IsNotNull(d_week_seq)]
ReadSchema: struct<d_month_seq:int,d_week_seq:int>

(20) ColumnarToRow [codegen id : 4]
Input [2]: [d_month_seq#38, d_week_seq#39]

(21) Filter [codegen id : 4]
Input [2]: [d_month_seq#38, d_week_seq#39]
Condition : (((isnotnull(d_month_seq#38) AND (d_month_seq#38 >= 1185)) AND (d_month_seq#38 <= 1196)) AND isnotnull(d_week_seq#39))

(22) Project [codegen id : 4]
Output [1]: [d_week_seq#39]
Input [2]: [d_month_seq#38, d_week_seq#39]

(23) BroadcastExchange
Input [1]: [d_week_seq#39]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]

(24) BroadcastHashJoin [codegen id : 10]
Left keys [1]: [d_week_seq#5]
Right keys [1]: [d_week_seq#39]
Join type: Inner
Join condition: None

(25) Project [codegen id : 10]
Output [10]: [s_store_name#37 AS s_store_name1#40, d_week_seq#5 AS d_week_seq1#41, s_store_id#36 AS s_store_id1#42, sun_sales#28 AS sun_sales1#43, mon_sales#29 AS mon_sales1#44, tue_sales#30 AS tue_sales1#45, wed_sales#31 AS wed_sales1#46, thu_sales#32 AS thu_sales1#47, fri_sales#33 AS fri_sales1#48, sat_sales#34 AS sat_sales1#49]
Input [11]: [d_week_seq#5, sun_sales#28, mon_sales#29, tue_sales#30, wed_sales#31, thu_sales#32, fri_sales#33, sat_sales#34, s_store_id#36, s_store_name#37, d_week_seq#39]

(26) Scan parquet spark_catalog.default.store_sales
Output [3]: [ss_store_sk#50, ss_sales_price#51, ss_sold_date_sk#52]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#52)]
PushedFilters: [IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_store_sk:int,ss_sales_price:decimal(7,2)>

(27) ColumnarToRow [codegen id : 6]
Input [3]: [ss_store_sk#50, ss_sales_price#51, ss_sold_date_sk#52]

(28) Filter [codegen id : 6]
Input [3]: [ss_store_sk#50, ss_sales_price#51, ss_sold_date_sk#52]
Condition : isnotnull(ss_store_sk#50)

(29) ReusedExchange [Reuses operator id: 7]
Output [3]: [d_date_sk#53, d_week_seq#54, d_day_name#55]

(30) BroadcastHashJoin [codegen id : 6]
Left keys [1]: [ss_sold_date_sk#52]
Right keys [1]: [d_date_sk#53]
Join type: Inner
Join condition: None

(31) Project [codegen id : 6]
Output [4]: [ss_store_sk#50, ss_sales_price#51, d_week_seq#54, d_day_name#55]
Input [6]: [ss_store_sk#50, ss_sales_price#51, ss_sold_date_sk#52, d_date_sk#53, d_week_seq#54, d_day_name#55]

(32) HashAggregate [codegen id : 6]
Input [4]: [ss_store_sk#50, ss_sales_price#51, d_week_seq#54, d_day_name#55]
Keys [2]: [d_week_seq#54, ss_store_sk#50]
Functions [6]: [partial_sum(UnscaledValue(CASE WHEN (d_day_name#55 = Sunday   ) THEN ss_sales_price#51 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#55 = Monday   ) THEN ss_sales_price#51 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#55 = Wednesday) THEN ss_sales_price#51 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#55 = Thursday ) THEN ss_sales_price#51 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#55 = Friday   ) THEN ss_sales_price#51 END)), partial_sum(UnscaledValue(CASE WHEN (d_day_name#55 = Saturday ) THEN ss_sales_price#51 END))]
Aggregate Attributes [6]: [sum#56, sum#57, sum#58, sum#59, sum#60, sum#61]
Results [8]: [d_week_seq#54, ss_store_sk#50, sum#62, sum#63, sum#64, sum#65, sum#66, sum#67]

(33) Exchange
Input [8]: [d_week_seq#54, ss_store_sk#50, sum#62, sum#63, sum#64, sum#65, sum#66, sum#67]
Arguments: hashpartitioning(d_week_seq#54, ss_store_sk#50, 5), ENSURE_REQUIREMENTS, [plan_id=5]

(34) HashAggregate [codegen id : 9]
Input [8]: [d_week_seq#54, ss_store_sk#50, sum#62, sum#63, sum#64, sum#65, sum#66, sum#67]
Keys [2]: [d_week_seq#54, ss_store_sk#50]
Functions [6]: [sum(UnscaledValue(CASE WHEN (d_day_name#55 = Sunday   ) THEN ss_sales_price#51 END)), sum(UnscaledValue(CASE WHEN (d_day_name#55 = Monday   ) THEN ss_sales_price#51 END)), sum(UnscaledValue(CASE WHEN (d_day_name#55 = Wednesday) THEN ss_sales_price#51 END)), sum(UnscaledValue(CASE WHEN (d_day_name#55 = Thursday ) THEN ss_sales_price#51 END)), sum(UnscaledValue(CASE WHEN (d_day_name#55 = Friday   ) THEN ss_sales_price#51 END)), sum(UnscaledValue(CASE WHEN (d_day_name#55 = Saturday ) THEN ss_sales_price#51 END))]
Aggregate Attributes [6]: [sum(UnscaledValue(CASE WHEN (d_day_name#55 = Sunday   ) THEN ss_sales_price#51 END))#21, sum(UnscaledValue(CASE WHEN (d_day_name#55 = Monday   ) THEN ss_sales_price#51 END))#22, sum(UnscaledValue(CASE WHEN (d_day_name#55 = Wednesday) THEN ss_sales_price#51 END))#24, sum(UnscaledValue(CASE WHEN (d_day_name#55 = Thursday ) THEN ss_sales_price#51 END))#25, sum(UnscaledValue(CASE WHEN (d_day_name#55 = Friday   ) THEN ss_sales_price#51 END))#26, sum(UnscaledValue(CASE WHEN (d_day_name#55 = Saturday ) THEN ss_sales_price#51 END))#27]
Results [8]: [d_week_seq#54, ss_store_sk#50, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#55 = Sunday   ) THEN ss_sales_price#51 END))#21,17,2) AS sun_sales#68, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#55 = Monday   ) THEN ss_sales_price#51 END))#22,17,2) AS mon_sales#69, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#55 = Wednesday) THEN ss_sales_price#51 END))#24,17,2) AS wed_sales#70, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#55 = Thursday ) THEN ss_sales_price#51 END))#25,17,2) AS thu_sales#71, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#55 = Friday   ) THEN ss_sales_price#51 END))#26,17,2) AS fri_sales#72, MakeDecimal(sum(UnscaledValue(CASE WHEN (d_day_name#55 = Saturday ) THEN ss_sales_price#51 END))#27,17,2) AS sat_sales#73]

(35) Scan parquet spark_catalog.default.store
Output [2]: [s_store_sk#74, s_store_id#75]
Batched: true
Location [not included in comparison]/{warehouse_dir}/store]
PushedFilters: [IsNotNull(s_store_sk), IsNotNull(s_store_id)]
ReadSchema: struct<s_store_sk:int,s_store_id:string>

(36) ColumnarToRow [codegen id : 7]
Input [2]: [s_store_sk#74, s_store_id#75]

(37) Filter [codegen id : 7]
Input [2]: [s_store_sk#74, s_store_id#75]
Condition : (isnotnull(s_store_sk#74) AND isnotnull(s_store_id#75))

(38) BroadcastExchange
Input [2]: [s_store_sk#74, s_store_id#75]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint)),false), [plan_id=6]

(39) BroadcastHashJoin [codegen id : 9]
Left keys [1]: [ss_store_sk#50]
Right keys [1]: [s_store_sk#74]
Join type: Inner
Join condition: None

(40) Project [codegen id : 9]
Output [8]: [d_week_seq#54, sun_sales#68, mon_sales#69, wed_sales#70, thu_sales#71, fri_sales#72, sat_sales#73, s_store_id#75]
Input [10]: [d_week_seq#54, ss_store_sk#50, sun_sales#68, mon_sales#69, wed_sales#70, thu_sales#71, fri_sales#72, sat_sales#73, s_store_sk#74, s_store_id#75]

(41) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_month_seq#76, d_week_seq#77]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_month_seq), GreaterThanOrEqual(d_month_seq,1197), LessThanOrEqual(d_month_seq,1208), IsNotNull(d_week_seq)]
ReadSchema: struct<d_month_seq:int,d_week_seq:int>

(42) ColumnarToRow [codegen id : 8]
Input [2]: [d_month_seq#76, d_week_seq#77]

(43) Filter [codegen id : 8]
Input [2]: [d_month_seq#76, d_week_seq#77]
Condition : (((isnotnull(d_month_seq#76) AND (d_month_seq#76 >= 1197)) AND (d_month_seq#76 <= 1208)) AND isnotnull(d_week_seq#77))

(44) Project [codegen id : 8]
Output [1]: [d_week_seq#77]
Input [2]: [d_month_seq#76, d_week_seq#77]

(45) BroadcastExchange
Input [1]: [d_week_seq#77]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=7]

(46) BroadcastHashJoin [codegen id : 9]
Left keys [1]: [d_week_seq#54]
Right keys [1]: [d_week_seq#77]
Join type: Inner
Join condition: None

(47) Project [codegen id : 9]
Output [8]: [d_week_seq#54 AS d_week_seq2#78, s_store_id#75 AS s_store_id2#79, sun_sales#68 AS sun_sales2#80, mon_sales#69 AS mon_sales2#81, wed_sales#70 AS wed_sales2#82, thu_sales#71 AS thu_sales2#83, fri_sales#72 AS fri_sales2#84, sat_sales#73 AS sat_sales2#85]
Input [9]: [d_week_seq#54, sun_sales#68, mon_sales#69, wed_sales#70, thu_sales#71, fri_sales#72, sat_sales#73, s_store_id#75, d_week_seq#77]

(48) BroadcastExchange
Input [8]: [d_week_seq2#78, s_store_id2#79, sun_sales2#80, mon_sales2#81, wed_sales2#82, thu_sales2#83, fri_sales2#84, sat_sales2#85]
Arguments: HashedRelationBroadcastMode(List(input[1, string, true], (input[0, int, true] - 52)),false), [plan_id=8]

(49) BroadcastHashJoin [codegen id : 10]
Left keys [2]: [s_store_id1#42, d_week_seq1#41]
Right keys [2]: [s_store_id2#79, (d_week_seq2#78 - 52)]
Join type: Inner
Join condition: None

(50) Project [codegen id : 10]
Output [10]: [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1#43 / sun_sales2#80) AS (sun_sales1 / sun_sales2)#86, (mon_sales1#44 / mon_sales2#81) AS (mon_sales1 / mon_sales2)#87, (tue_sales1#45 / tue_sales1#45) AS (tue_sales1 / tue_sales1)#88, (wed_sales1#46 / wed_sales2#82) AS (wed_sales1 / wed_sales2)#89, (thu_sales1#47 / thu_sales2#83) AS (thu_sales1 / thu_sales2)#90, (fri_sales1#48 / fri_sales2#84) AS (fri_sales1 / fri_sales2)#91, (sat_sales1#49 / sat_sales2#85) AS (sat_sales1 / sat_sales2)#92]
Input [18]: [s_store_name1#40, d_week_seq1#41, s_store_id1#42, sun_sales1#43, mon_sales1#44, tue_sales1#45, wed_sales1#46, thu_sales1#47, fri_sales1#48, sat_sales1#49, d_week_seq2#78, s_store_id2#79, sun_sales2#80, mon_sales2#81, wed_sales2#82, thu_sales2#83, fri_sales2#84, sat_sales2#85]

(51) TakeOrderedAndProject
Input [10]: [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1 / sun_sales2)#86, (mon_sales1 / mon_sales2)#87, (tue_sales1 / tue_sales1)#88, (wed_sales1 / wed_sales2)#89, (thu_sales1 / thu_sales2)#90, (fri_sales1 / fri_sales2)#91, (sat_sales1 / sat_sales2)#92]
Arguments: 100, [s_store_name1#40 ASC NULLS FIRST, s_store_id1#42 ASC NULLS FIRST, d_week_seq1#41 ASC NULLS FIRST], [s_store_name1#40, s_store_id1#42, d_week_seq1#41, (sun_sales1 / sun_sales2)#86, (mon_sales1 / mon_sales2)#87, (tue_sales1 / tue_sales1)#88, (wed_sales1 / wed_sales2)#89, (thu_sales1 / thu_sales2)#90, (fri_sales1 / fri_sales2)#91, (sat_sales1 / sat_sales2)#92]

