SP1 - Details for Query 7742

Submitted Time: 2026/10/27 21:29:14
Duration: 0.2 s
Succeeded Jobs: 11265 11266

Show the Stage ID and Task ID that corresponds to the max metric

digraph G { 0 [labelType="html" label=" AdaptiveSparkPlan "]; 1 [labelType="html" label="ObjectHashAggregate number of output rows: 440 time in aggregation build: 13 ms spill size: 0.0 B number of sort fallback tasks: 1"]; 2 [labelType="html" label="AQEShuffleRead number of partitions: 1 partition data size: 28.5 KiB number of coalesced partitions: 1"]; 3 [labelType="html" label="Exchange shuffle records written: 447 local merged chunks fetched: 0 shuffle write time total (min, med, max (stageId: taskId)) 12 ms (1 ms, 2 ms, 2 ms (stage 22734.0: task 28309)) remote merged bytes read: 0.0 B local merged blocks fetched: 0 corrupt merged block chunks: 0 remote merged reqs duration: 0 ms remote merged blocks fetched: 0 records read: 447 local bytes read: 27.2 KiB fetch wait time: 0 ms remote bytes read: 0.0 B merged fetch fallback count: 0 local blocks read: 6 remote merged chunks fetched: 0 remote blocks read: 0 data size total (min, med, max (stageId: taskId)) 57.0 KiB (8.4 KiB, 9.7 KiB, 9.8 KiB (stage 22734.0: task 28311)) local merged bytes read: 0.0 B number of partitions: 10 remote reqs duration: 0 ms remote bytes read to disk: 0.0 B shuffle bytes written total (min, med, max (stageId: taskId)) 27.2 KiB (4.2 KiB, 4.6 KiB, 4.8 KiB (stage 22734.0: task 28308))"]; 4 [labelType="html" label="ObjectHashAggregate number of output rows: 447 time in aggregation build total (min, med, max (stageId: taskId)) 110 ms (8 ms, 18 ms, 24 ms (stage 22734.0: task 28307)) spill size total (min, med, max (stageId: taskId)) 0.0 B (0.0 B, 0.0 B, 0.0 B (stage 22734.0: task 28312)) number of sort fallback tasks: 0"]; subgraph cluster5 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: total (min, med, max (stageId: taskId))\n110 ms (8 ms, 18 ms, 24 ms (stage 22734.0: task 28307))"; 6 [labelType="html" label=" Project "]; 7 [labelType="html" label="Filter number of output rows: 1,189"]; 8 [labelType="html" label="ColumnarToRow number of output rows: 1,201 number of input batches: 12"]; } 9 [labelType="html" label="Scan parquet number of files read: 12 scan time total (min, med, max (stageId: taskId)) 46 ms (3 ms, 8 ms, 11 ms (stage 22734.0: task 28308)) metadata time: 0 ms size of files read: 175.2 KiB number of output rows: 1,201"]; 1->0; 2->1; 3->2; 4->3; 6->4; 7->6; 8->7; 9->8; }

AdaptiveSparkPlan isFinalPlan=true

ObjectHashAggregate(keys=[COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591], functions=[collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0), sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)])

AQEShuffleRead coalesced

Exchange hashpartitioning(COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, 10), ENSURE_REQUIREMENTS, [plan_id=1093581]

ObjectHashAggregate(keys=[COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591], functions=[partial_collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0), partial_sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)])

Project [str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT) AS COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, code+LPP#1984768 AS COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, str_to_dec(quantit%C3%A9#1984770, ##.##) AS COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596]

Filter isnotnull(str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT))

ColumnarToRow

WholeStageCodegen (1)

FileScan parquet [N%C2%B0+s%C3%A9jour#1984765,code+LPP#1984768,quantit%C3%A9#1984770] Batched: true, DataFilters: [isnotnull(str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT))], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/excel/cache/SYNTHESE_DMI_20_237789_b7c9fcd90987..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<N%C2%B0+s%C3%A9jour:string,code+LPP:string,quantit%C3%A9:string>

Details

== Physical Plan ==
AdaptiveSparkPlan (16)
+- == Final Plan ==
   ObjectHashAggregate (9)
   +- AQEShuffleRead (8)
      +- ShuffleQueryStage (7), Statistics(sizeInBytes=57.0 KiB, rowCount=447)
         +- Exchange (6)
            +- ObjectHashAggregate (5)
               +- * Project (4)
                  +- * Filter (3)
                     +- * ColumnarToRow (2)
                        +- Scan parquet  (1)
+- == Initial Plan ==
   CollectLimit (15)
   +- ObjectHashAggregate (14)
      +- Exchange (13)
         +- ObjectHashAggregate (12)
            +- Project (11)
               +- Filter (10)
                  +- Scan parquet  (1)


(1) Scan parquet 
Output [3]: [N%C2%B0+s%C3%A9jour#1984765, code+LPP#1984768, quantit%C3%A9#1984770]
Batched: true
Location: InMemoryFileIndex [file:/data/input/depot/excel/cache/SYNTHESE_DMI_20_237789_b7c9fcd90987f45e4002171a5d87dfdd/synthèse-DMI-2025.xls_41d136f5d26b76a99c371a1af7fc9e64]
ReadSchema: struct<N%C2%B0+s%C3%A9jour:string,code+LPP:string,quantit%C3%A9:string>

(2) ColumnarToRow [codegen id : 1]
Input [3]: [N%C2%B0+s%C3%A9jour#1984765, code+LPP#1984768, quantit%C3%A9#1984770]

(3) Filter [codegen id : 1]
Input [3]: [N%C2%B0+s%C3%A9jour#1984765, code+LPP#1984768, quantit%C3%A9#1984770]
Condition : isnotnull(str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT))

(4) Project [codegen id : 1]
Output [3]: [str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT) AS COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, code+LPP#1984768 AS COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, str_to_dec(quantit%C3%A9#1984770, ##.##) AS COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596]
Input [3]: [N%C2%B0+s%C3%A9jour#1984765, code+LPP#1984768, quantit%C3%A9#1984770]

(5) ObjectHashAggregate
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596]
Keys [1]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591]
Functions [2]: [partial_collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0), partial_sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)]
Aggregate Attributes [2]: [buf#1985673, sum#1985674]
Results [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]

(6) Exchange
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]
Arguments: hashpartitioning(COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, 10), ENSURE_REQUIREMENTS, [plan_id=1093581]

(7) ShuffleQueryStage
Output [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]
Arguments: 0

(8) AQEShuffleRead
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]
Arguments: coalesced

(9) ObjectHashAggregate
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]
Keys [1]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591]
Functions [2]: [collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0), sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)]
Aggregate Attributes [2]: [collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0)#1985638, sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)#1985640]
Results [3]: [collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0)#1985638 AS COL_366ECB86_7C6B_4706_8A94_E56AA45C57E8#1985667, bigint_to_str(str_to_bigint(COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591)) AS COL_3EFE5338_508A_40B8_A657_9886B74C9033#1985668, coalesce(dec_to_int(sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)#1985640), 0) AS COL_C7F70CCE_BC78_4FA4_AA37_81FFA69995D5#1985669]

(10) Filter
Input [3]: [N%C2%B0+s%C3%A9jour#1984765, code+LPP#1984768, quantit%C3%A9#1984770]
Condition : isnotnull(str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT))

(11) Project
Output [3]: [str_complete(N%C2%B0+s%C3%A9jour#1984765, 0, 20, LEFT) AS COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, code+LPP#1984768 AS COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, str_to_dec(quantit%C3%A9#1984770, ##.##) AS COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596]
Input [3]: [N%C2%B0+s%C3%A9jour#1984765, code+LPP#1984768, quantit%C3%A9#1984770]

(12) ObjectHashAggregate
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596]
Keys [1]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591]
Functions [2]: [partial_collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0), partial_sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)]
Aggregate Attributes [2]: [buf#1985673, sum#1985674]
Results [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]

(13) Exchange
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]
Arguments: hashpartitioning(COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, 10), ENSURE_REQUIREMENTS, [plan_id=1093558]

(14) ObjectHashAggregate
Input [3]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591, buf#1985675, sum#1985676]
Keys [1]: [COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591]
Functions [2]: [collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0), sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)]
Aggregate Attributes [2]: [collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0)#1985638, sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)#1985640]
Results [3]: [collect_list(COL_02B457D4_211D_4296_9D9B_D989AD1EFF12#1985594, 0, 0)#1985638 AS COL_366ECB86_7C6B_4706_8A94_E56AA45C57E8#1985667, bigint_to_str(str_to_bigint(COL_38C3BE50_A7EE_41B8_BB22_8A6D1B6C1A8A#1985591)) AS COL_3EFE5338_508A_40B8_A657_9886B74C9033#1985668, coalesce(dec_to_int(sum(COL_9F6C8A6D_788E_42DB_A61A_6AA75EF360C7#1985596)#1985640), 0) AS COL_C7F70CCE_BC78_4FA4_AA37_81FFA69995D5#1985669]

(15) CollectLimit
Input [3]: [COL_366ECB86_7C6B_4706_8A94_E56AA45C57E8#1985667, COL_3EFE5338_508A_40B8_A657_9886B74C9033#1985668, COL_C7F70CCE_BC78_4FA4_AA37_81FFA69995D5#1985669]
Arguments: 1500

(16) AdaptiveSparkPlan
Output [3]: [COL_366ECB86_7C6B_4706_8A94_E56AA45C57E8#1985667, COL_3EFE5338_508A_40B8_A657_9886B74C9033#1985668, COL_C7F70CCE_BC78_4FA4_AA37_81FFA69995D5#1985669]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

Name	Value
spark.sql.optimizer.nestedPredicatePushdown.supportedFileSources	parquet,orc,geoparquet