== Physical Plan ==
TakeOrderedAndProject (45)
+- * HashAggregate (44)
   +- Exchange (43)
      +- * HashAggregate (42)
         +- * ColumnarToRow (41)
            +- CometProject (40)
               +- CometBroadcastHashJoin (39)
                  :- CometProject (35)
                  :  +- CometBroadcastHashJoin (34)
                  :     :- CometProject (30)
                  :     :  +- CometBroadcastHashJoin (29)
                  :     :     :- CometProject (24)
                  :     :     :  +- CometBroadcastHashJoin (23)
                  :     :     :     :- CometProject (18)
                  :     :     :     :  +- CometBroadcastHashJoin (17)
                  :     :     :     :     :- CometProject (12)
                  :     :     :     :     :  +- CometBroadcastHashJoin (11)
                  :     :     :     :     :     :- CometProject (7)
                  :     :     :     :     :     :  +- CometBroadcastHashJoin (6)
                  :     :     :     :     :     :     :- CometFilter (2)
                  :     :     :     :     :     :     :  +- CometScan parquet spark_catalog.default.store_sales (1)
                  :     :     :     :     :     :     +- CometBroadcastExchange (5)
                  :     :     :     :     :     :        +- CometFilter (4)
                  :     :     :     :     :     :           +- CometScan parquet spark_catalog.default.store_returns (3)
                  :     :     :     :     :     +- CometBroadcastExchange (10)
                  :     :     :     :     :        +- CometFilter (9)
                  :     :     :     :     :           +- CometScan parquet spark_catalog.default.catalog_sales (8)
                  :     :     :     :     +- CometBroadcastExchange (16)
                  :     :     :     :        +- CometProject (15)
                  :     :     :     :           +- CometFilter (14)
                  :     :     :     :              +- CometScan parquet spark_catalog.default.date_dim (13)
                  :     :     :     +- CometBroadcastExchange (22)
                  :     :     :        +- CometProject (21)
                  :     :     :           +- CometFilter (20)
                  :     :     :              +- CometScan parquet spark_catalog.default.date_dim (19)
                  :     :     +- CometBroadcastExchange (28)
                  :     :        +- CometProject (27)
                  :     :           +- CometFilter (26)
                  :     :              +- CometScan parquet spark_catalog.default.date_dim (25)
                  :     +- CometBroadcastExchange (33)
                  :        +- CometFilter (32)
                  :           +- CometScan parquet spark_catalog.default.store (31)
                  +- CometBroadcastExchange (38)
                     +- CometFilter (37)
                        +- CometScan parquet spark_catalog.default.item (36)


(1) Scan parquet spark_catalog.default.store_sales
Output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(ss_sold_date_sk#6), dynamicpruningexpression(ss_sold_date_sk#6 IN dynamicpruning#7)]
PushedFilters: [IsNotNull(ss_customer_sk), IsNotNull(ss_item_sk), IsNotNull(ss_ticket_number), IsNotNull(ss_store_sk)]
ReadSchema: struct<ss_item_sk:int,ss_customer_sk:int,ss_store_sk:int,ss_ticket_number:int,ss_quantity:int>

(2) CometFilter
Input [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6]
Condition : (((isnotnull(ss_customer_sk#2) AND isnotnull(ss_item_sk#1)) AND isnotnull(ss_ticket_number#4)) AND isnotnull(ss_store_sk#3))

(3) Scan parquet spark_catalog.default.store_returns
Output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(sr_returned_date_sk#12), dynamicpruningexpression(sr_returned_date_sk#12 IN dynamicpruning#13)]
PushedFilters: [IsNotNull(sr_customer_sk), IsNotNull(sr_item_sk), IsNotNull(sr_ticket_number)]
ReadSchema: struct<sr_item_sk:int,sr_customer_sk:int,sr_ticket_number:int,sr_return_quantity:int>

(4) CometFilter
Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12]
Condition : ((isnotnull(sr_customer_sk#9) AND isnotnull(sr_item_sk#8)) AND isnotnull(sr_ticket_number#10))

(5) CometBroadcastExchange
Input [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12]
Arguments: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12]

(6) CometBroadcastHashJoin
Left output [6]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6]
Right output [5]: [sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12]
Arguments: [ss_customer_sk#2, ss_item_sk#1, ss_ticket_number#4], [sr_customer_sk#9, sr_item_sk#8, sr_ticket_number#10], Inner, BuildRight

(7) CometProject
Input [11]: [ss_item_sk#1, ss_customer_sk#2, ss_store_sk#3, ss_ticket_number#4, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_ticket_number#10, sr_return_quantity#11, sr_returned_date_sk#12]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12], [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12]

(8) Scan parquet spark_catalog.default.catalog_sales
Output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17]
Batched: true
Location: InMemoryFileIndex []
PartitionFilters: [isnotnull(cs_sold_date_sk#17), dynamicpruningexpression(cs_sold_date_sk#17 IN dynamicpruning#18)]
PushedFilters: [IsNotNull(cs_bill_customer_sk), IsNotNull(cs_item_sk)]
ReadSchema: struct<cs_bill_customer_sk:int,cs_item_sk:int,cs_quantity:int>

(9) CometFilter
Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17]
Condition : (isnotnull(cs_bill_customer_sk#14) AND isnotnull(cs_item_sk#15))

(10) CometBroadcastExchange
Input [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17]
Arguments: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17]

(11) CometBroadcastHashJoin
Left output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12]
Right output [4]: [cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17]
Arguments: [sr_customer_sk#9, sr_item_sk#8], [cs_bill_customer_sk#14, cs_item_sk#15], Inner, BuildRight

(12) CometProject
Input [12]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_item_sk#8, sr_customer_sk#9, sr_return_quantity#11, sr_returned_date_sk#12, cs_bill_customer_sk#14, cs_item_sk#15, cs_quantity#16, cs_sold_date_sk#17]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17], [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17]

(13) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#19, d_year#20, d_moy#21]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,9), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(14) CometFilter
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]
Condition : ((((isnotnull(d_moy#21) AND isnotnull(d_year#20)) AND (d_moy#21 = 9)) AND (d_year#20 = 1999)) AND isnotnull(d_date_sk#19))

(15) CometProject
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]
Arguments: [d_date_sk#19], [d_date_sk#19]

(16) CometBroadcastExchange
Input [1]: [d_date_sk#19]
Arguments: [d_date_sk#19]

(17) CometBroadcastHashJoin
Left output [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17]
Right output [1]: [d_date_sk#19]
Arguments: [ss_sold_date_sk#6], [d_date_sk#19], Inner, BuildRight

(18) CometProject
Input [9]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, ss_sold_date_sk#6, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#19]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17], [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17]

(19) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#22, d_year#23, d_moy#24]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,9), LessThanOrEqual(d_moy,12), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(20) CometFilter
Input [3]: [d_date_sk#22, d_year#23, d_moy#24]
Condition : (((((isnotnull(d_moy#24) AND isnotnull(d_year#23)) AND (d_moy#24 >= 9)) AND (d_moy#24 <= 12)) AND (d_year#23 = 1999)) AND isnotnull(d_date_sk#22))

(21) CometProject
Input [3]: [d_date_sk#22, d_year#23, d_moy#24]
Arguments: [d_date_sk#22], [d_date_sk#22]

(22) CometBroadcastExchange
Input [1]: [d_date_sk#22]
Arguments: [d_date_sk#22]

(23) CometBroadcastHashJoin
Left output [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17]
Right output [1]: [d_date_sk#22]
Arguments: [sr_returned_date_sk#12], [d_date_sk#22], Inner, BuildRight

(24) CometProject
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, sr_returned_date_sk#12, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#22]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17], [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17]

(25) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#25, d_year#26]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(26) CometFilter
Input [2]: [d_date_sk#25, d_year#26]
Condition : (d_year#26 IN (1999,2000,2001) AND isnotnull(d_date_sk#25))

(27) CometProject
Input [2]: [d_date_sk#25, d_year#26]
Arguments: [d_date_sk#25], [d_date_sk#25]

(28) CometBroadcastExchange
Input [1]: [d_date_sk#25]
Arguments: [d_date_sk#25]

(29) CometBroadcastHashJoin
Left output [6]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17]
Right output [1]: [d_date_sk#25]
Arguments: [cs_sold_date_sk#17], [d_date_sk#25], Inner, BuildRight

(30) CometProject
Input [7]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, cs_sold_date_sk#17, d_date_sk#25]
Arguments: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16], [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16]

(31) Scan parquet spark_catalog.default.store
Output [3]: [s_store_sk#27, s_store_id#28, s_store_name#29]
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,s_store_name:string>

(32) CometFilter
Input [3]: [s_store_sk#27, s_store_id#28, s_store_name#29]
Condition : isnotnull(s_store_sk#27)

(33) CometBroadcastExchange
Input [3]: [s_store_sk#27, s_store_id#28, s_store_name#29]
Arguments: [s_store_sk#27, s_store_id#28, s_store_name#29]

(34) CometBroadcastHashJoin
Left output [5]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16]
Right output [3]: [s_store_sk#27, s_store_id#28, s_store_name#29]
Arguments: [ss_store_sk#3], [s_store_sk#27], Inner, BuildRight

(35) CometProject
Input [8]: [ss_item_sk#1, ss_store_sk#3, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_sk#27, s_store_id#28, s_store_name#29]
Arguments: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29], [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29]

(36) Scan parquet spark_catalog.default.item
Output [3]: [i_item_sk#30, i_item_id#31, i_item_desc#32]
Batched: true
Location [not included in comparison]/{warehouse_dir}/item]
PushedFilters: [IsNotNull(i_item_sk)]
ReadSchema: struct<i_item_sk:int,i_item_id:string,i_item_desc:string>

(37) CometFilter
Input [3]: [i_item_sk#30, i_item_id#31, i_item_desc#32]
Condition : isnotnull(i_item_sk#30)

(38) CometBroadcastExchange
Input [3]: [i_item_sk#30, i_item_id#31, i_item_desc#32]
Arguments: [i_item_sk#30, i_item_id#31, i_item_desc#32]

(39) CometBroadcastHashJoin
Left output [6]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29]
Right output [3]: [i_item_sk#30, i_item_id#31, i_item_desc#32]
Arguments: [ss_item_sk#1], [i_item_sk#30], Inner, BuildRight

(40) CometProject
Input [9]: [ss_item_sk#1, ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29, i_item_sk#30, i_item_id#31, i_item_desc#32]
Arguments: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29, i_item_id#31, i_item_desc#32], [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29, i_item_id#31, i_item_desc#32]

(41) ColumnarToRow [codegen id : 1]
Input [7]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29, i_item_id#31, i_item_desc#32]

(42) HashAggregate [codegen id : 1]
Input [7]: [ss_quantity#5, sr_return_quantity#11, cs_quantity#16, s_store_id#28, s_store_name#29, i_item_id#31, i_item_desc#32]
Keys [4]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29]
Functions [3]: [partial_sum(ss_quantity#5), partial_sum(sr_return_quantity#11), partial_sum(cs_quantity#16)]
Aggregate Attributes [3]: [sum#33, sum#34, sum#35]
Results [7]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, sum#36, sum#37, sum#38]

(43) Exchange
Input [7]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, sum#36, sum#37, sum#38]
Arguments: hashpartitioning(i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, 5), ENSURE_REQUIREMENTS, [plan_id=1]

(44) HashAggregate [codegen id : 2]
Input [7]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, sum#36, sum#37, sum#38]
Keys [4]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29]
Functions [3]: [sum(ss_quantity#5), sum(sr_return_quantity#11), sum(cs_quantity#16)]
Aggregate Attributes [3]: [sum(ss_quantity#5)#39, sum(sr_return_quantity#11)#40, sum(cs_quantity#16)#41]
Results [7]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, sum(ss_quantity#5)#39 AS store_sales_quantity#42, sum(sr_return_quantity#11)#40 AS store_returns_quantity#43, sum(cs_quantity#16)#41 AS catalog_sales_quantity#44]

(45) TakeOrderedAndProject
Input [7]: [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, store_sales_quantity#42, store_returns_quantity#43, catalog_sales_quantity#44]
Arguments: 100, [i_item_id#31 ASC NULLS FIRST, i_item_desc#32 ASC NULLS FIRST, s_store_id#28 ASC NULLS FIRST, s_store_name#29 ASC NULLS FIRST], [i_item_id#31, i_item_desc#32, s_store_id#28, s_store_name#29, store_sales_quantity#42, store_returns_quantity#43, catalog_sales_quantity#44]

===== Subqueries =====

Subquery:1 Hosting operator id = 1 Hosting Expression = ss_sold_date_sk#6 IN dynamicpruning#7
BroadcastExchange (50)
+- * ColumnarToRow (49)
   +- CometProject (48)
      +- CometFilter (47)
         +- CometScan parquet spark_catalog.default.date_dim (46)


(46) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#19, d_year#20, d_moy#21]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), EqualTo(d_moy,9), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(47) CometFilter
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]
Condition : ((((isnotnull(d_moy#21) AND isnotnull(d_year#20)) AND (d_moy#21 = 9)) AND (d_year#20 = 1999)) AND isnotnull(d_date_sk#19))

(48) CometProject
Input [3]: [d_date_sk#19, d_year#20, d_moy#21]
Arguments: [d_date_sk#19], [d_date_sk#19]

(49) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#19]

(50) BroadcastExchange
Input [1]: [d_date_sk#19]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=2]

Subquery:2 Hosting operator id = 3 Hosting Expression = sr_returned_date_sk#12 IN dynamicpruning#13
BroadcastExchange (55)
+- * ColumnarToRow (54)
   +- CometProject (53)
      +- CometFilter (52)
         +- CometScan parquet spark_catalog.default.date_dim (51)


(51) Scan parquet spark_catalog.default.date_dim
Output [3]: [d_date_sk#22, d_year#23, d_moy#24]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [IsNotNull(d_moy), IsNotNull(d_year), GreaterThanOrEqual(d_moy,9), LessThanOrEqual(d_moy,12), EqualTo(d_year,1999), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int,d_moy:int>

(52) CometFilter
Input [3]: [d_date_sk#22, d_year#23, d_moy#24]
Condition : (((((isnotnull(d_moy#24) AND isnotnull(d_year#23)) AND (d_moy#24 >= 9)) AND (d_moy#24 <= 12)) AND (d_year#23 = 1999)) AND isnotnull(d_date_sk#22))

(53) CometProject
Input [3]: [d_date_sk#22, d_year#23, d_moy#24]
Arguments: [d_date_sk#22], [d_date_sk#22]

(54) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#22]

(55) BroadcastExchange
Input [1]: [d_date_sk#22]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=3]

Subquery:3 Hosting operator id = 8 Hosting Expression = cs_sold_date_sk#17 IN dynamicpruning#18
BroadcastExchange (60)
+- * ColumnarToRow (59)
   +- CometProject (58)
      +- CometFilter (57)
         +- CometScan parquet spark_catalog.default.date_dim (56)


(56) Scan parquet spark_catalog.default.date_dim
Output [2]: [d_date_sk#25, d_year#26]
Batched: true
Location [not included in comparison]/{warehouse_dir}/date_dim]
PushedFilters: [In(d_year, [1999,2000,2001]), IsNotNull(d_date_sk)]
ReadSchema: struct<d_date_sk:int,d_year:int>

(57) CometFilter
Input [2]: [d_date_sk#25, d_year#26]
Condition : (d_year#26 IN (1999,2000,2001) AND isnotnull(d_date_sk#25))

(58) CometProject
Input [2]: [d_date_sk#25, d_year#26]
Arguments: [d_date_sk#25], [d_date_sk#25]

(59) ColumnarToRow [codegen id : 1]
Input [1]: [d_date_sk#25]

(60) BroadcastExchange
Input [1]: [d_date_sk#25]
Arguments: HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint)),false), [plan_id=4]


