SP1 - Details for Query 1057

Submitted Time: 2026/02/24 11:09:21
Duration: 0.4 s
Succeeded Jobs: 1469 1475

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

digraph G { 0 [labelType="html" label=" AdaptiveSparkPlan "]; subgraph cluster1 { isCluster="true"; label="WholeStageCodegen (2)\n \nduration: 0 ms"; 2 [labelType="html" label="HashAggregate time in aggregation build: 0 ms number of output rows: 1"]; } 3 [labelType="html" label="Exchange shuffle records written: 1 local merged chunks fetched: 0 shuffle write time: 0 ms 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: 1 local bytes read: 59.0 B fetch wait time: 0 ms remote bytes read: 0.0 B merged fetch fallback count: 0 local blocks read: 1 remote merged chunks fetched: 0 remote blocks read: 0 data size: 16.0 B local merged bytes read: 0.0 B number of partitions: 1 remote reqs duration: 0 ms remote bytes read to disk: 0.0 B shuffle bytes written: 59.0 B"]; subgraph cluster4 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: 27 ms"; 5 [labelType="html" label="HashAggregate time in aggregation build: 27 ms number of output rows: 1"]; 6 [labelType="html" label=" Project "]; 7 [labelType="html" label="Filter number of output rows: 12,501"]; 8 [labelType="html" label="ColumnarToRow number of output rows: 20,578 number of input batches: 6"]; } 9 [labelType="html" label="Scan parquet number of files read: 1 scan time: 17 ms metadata time: 0 ms size of files read: 581.3 KiB number of output rows: 20,578"]; 2->0; 3->2; 5->3; 6->5; 7->6; 8->7; 9->8; }

AdaptiveSparkPlan isFinalPlan=true

HashAggregate(keys=[], functions=[sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)])

WholeStageCodegen (2)

Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=49046]

HashAggregate(keys=[], functions=[partial_sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)])

Project [COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508 AS COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800]

Filter (((COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510 <=> Optimisation) AND (COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499 <=> RC-FP* et CFU)) AND (COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501 <=> +))

ColumnarToRow

WholeStageCodegen (1)

FileScan parquet [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499,COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501,COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508,COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510] Batched: true, DataFilters: [(COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510 <=> Optimisation), (COL_2876989F_DEC1_40A8_860A..., Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/output/cache/parquet/datablock/06_COMPILATION__330516], PartitionFilters: [], PushedFilters: [EqualNullSafe(COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3,Optimisation), EqualNullSafe(COL_2876989F..., ReadSchema: struct<COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA:string,COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7:s...

Details

== Physical Plan ==
AdaptiveSparkPlan (14)
+- == Final Plan ==
   * HashAggregate (8)
   +- ShuffleQueryStage (7), Statistics(sizeInBytes=16.0 B, rowCount=1)
      +- Exchange (6)
         +- * HashAggregate (5)
            +- * Project (4)
               +- * Filter (3)
                  +- * ColumnarToRow (2)
                     +- Scan parquet  (1)
+- == Initial Plan ==
   HashAggregate (13)
   +- Exchange (12)
      +- HashAggregate (11)
         +- Project (10)
            +- Filter (9)
               +- Scan parquet  (1)


(1) Scan parquet 
Output [4]: [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499, COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501, COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508, COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510]
Batched: true
Location: InMemoryFileIndex [file:/data/output/cache/parquet/datablock/06_COMPILATION__330516]
PushedFilters: [EqualNullSafe(COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3,Optimisation), EqualNullSafe(COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA,RC-FP* et CFU), EqualNullSafe(COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7,+)]
ReadSchema: struct<COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA:string,COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7:string,COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6:double,COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3:string>

(2) ColumnarToRow [codegen id : 1]
Input [4]: [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499, COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501, COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508, COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510]

(3) Filter [codegen id : 1]
Input [4]: [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499, COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501, COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508, COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510]
Condition : (((COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510 <=> Optimisation) AND (COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499 <=> RC-FP* et CFU)) AND (COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501 <=> +))

(4) Project [codegen id : 1]
Output [1]: [COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508 AS COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800]
Input [4]: [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499, COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501, COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508, COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510]

(5) HashAggregate [codegen id : 1]
Input [1]: [COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800]
Keys: []
Functions [1]: [partial_sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)]
Aggregate Attributes [1]: [sum#357653]
Results [1]: [sum#357654]

(6) Exchange
Input [1]: [sum#357654]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=49046]

(7) ShuffleQueryStage
Output [1]: [sum#357654]
Arguments: 0

(8) HashAggregate [codegen id : 2]
Input [1]: [sum#357654]
Keys: []
Functions [1]: [sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)]
Aggregate Attributes [1]: [sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)#357117]
Results [3]: [round(sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)#357117, 2) AS COL_D7D159AD_30BF_4557_9945_0949EE7FCBCA#357511, str_create(Ajout FP* et CFU (€)) AS COL_C5B435F1_2BF0_4472_8C80_451FC7087109#357281, dec_create(0.0) AS COL_C6466788_3175_4D57_BF2C_AC53106391B9#357327]

(9) Filter
Input [4]: [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499, COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501, COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508, COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510]
Condition : (((COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510 <=> Optimisation) AND (COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499 <=> RC-FP* et CFU)) AND (COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501 <=> +))

(10) Project
Output [1]: [COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508 AS COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800]
Input [4]: [COL_2876989F_DEC1_40A8_860A_830E1DDD6BAA#356499, COL_F7E6B982_AE01_4D61_95F1_A194F4B50FB7#356501, COL_E38AB62F_E896_4A72_BE7E_515F8BC641C6#356508, COL_6348CDD7_7FF9_4337_B9DE_365982DB3BA3#356510]

(11) HashAggregate
Input [1]: [COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800]
Keys: []
Functions [1]: [partial_sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)]
Aggregate Attributes [1]: [sum#357653]
Results [1]: [sum#357654]

(12) Exchange
Input [1]: [sum#357654]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=48994]

(13) HashAggregate
Input [1]: [sum#357654]
Keys: []
Functions [1]: [sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)]
Aggregate Attributes [1]: [sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)#357117]
Results [3]: [round(sum(COL_6C88C0DB_D28A_4ECB_8817_A2A00EE71232#356800)#357117, 2) AS COL_D7D159AD_30BF_4557_9945_0949EE7FCBCA#357511, str_create(Ajout FP* et CFU (€)) AS COL_C5B435F1_2BF0_4472_8C80_451FC7087109#357281, dec_create(0.0) AS COL_C6466788_3175_4D57_BF2C_AC53106391B9#357327]

(14) AdaptiveSparkPlan
Output [3]: [COL_D7D159AD_30BF_4557_9945_0949EE7FCBCA#357511, COL_C5B435F1_2BF0_4472_8C80_451FC7087109#357281, COL_C6466788_3175_4D57_BF2C_AC53106391B9#357327]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

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