SP1 - Details for Query 3106

Submitted Time: 2026/09/24 14:23:26
Duration: 0.3 s
Succeeded Jobs: 4513 4514

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

digraph G { 0 [labelType="html" label=" AdaptiveSparkPlan "]; 1 [labelType="html" label="SortAggregate number of output rows: 1"]; 2 [labelType="html" label="Exchange shuffle records written: 3 local merged chunks fetched: 0 shuffle write time total (min, med, max (stageId: taskId)) 4 ms (0 ms, 0 ms, 3 ms (stage 8937.0: task 12264)) 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: 3 local bytes read: 264.0 B fetch wait time: 0 ms remote bytes read: 0.0 B merged fetch fallback count: 0 local blocks read: 3 remote merged chunks fetched: 0 remote blocks read: 0 data size total (min, med, max (stageId: taskId)) 176.0 B (56.0 B, 56.0 B, 64.0 B (stage 8937.0: task 12264)) 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 total (min, med, max (stageId: taskId)) 264.0 B (84.0 B, 88.0 B, 92.0 B (stage 8937.0: task 12264))"]; 3 [labelType="html" label="SortAggregate number of output rows: 3"]; 4 [labelType="html" label=" Union "]; subgraph cluster5 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: 29 ms"; 6 [labelType="html" label=" Project "]; 7 [labelType="html" label="ColumnarToRow number of output rows: 166 number of input batches: 1"]; } 8 [labelType="html" label="Scan parquet number of files read: 1 scan time: 2 ms metadata time: 0 ms size of files read: 4.3 KiB number of output rows: 166"]; subgraph cluster9 { isCluster="true"; label="WholeStageCodegen (2)\n \nduration: 33 ms"; 10 [labelType="html" label=" Project "]; 11 [labelType="html" label="ColumnarToRow number of output rows: 166 number of input batches: 1"]; } 12 [labelType="html" label="Scan parquet number of files read: 1 scan time: 3 ms metadata time: 0 ms size of files read: 4.3 KiB number of output rows: 166"]; subgraph cluster13 { isCluster="true"; label="WholeStageCodegen (3)\n \nduration: 30 ms"; 14 [labelType="html" label=" Project "]; 15 [labelType="html" label="ColumnarToRow number of output rows: 201 number of input batches: 1"]; } 16 [labelType="html" label="Scan parquet number of files read: 1 scan time: 2 ms metadata time: 0 ms size of files read: 4.4 KiB number of output rows: 201"]; 1->0; 2->1; 3->2; 4->3; 6->4; 7->6; 8->7; 10->4; 11->10; 12->11; 14->4; 15->14; 16->15; }

AdaptiveSparkPlan isFinalPlan=true

SortAggregate(key=[], functions=[count(1), count(COL_TRIGRAMME_216272#729345), min(COL_TRIGRAMME_216272#729345), max(COL_TRIGRAMME_216272#729345)])

Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=444700]

SortAggregate(key=[], functions=[partial_count(1), partial_count(COL_TRIGRAMME_216272#729345), partial_min(COL_TRIGRAMME_216272#729345), partial_max(COL_TRIGRAMME_216272#729345)])

Union

Project [Trigramme#729055 AS COL_TRIGRAMME_216272#729345]

ColumnarToRow

WholeStageCodegen (1)

FileScan parquet [Trigramme#729055] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/excel/cache/TARIF_FORFAIT_S_216188_8c16894e8611..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<Trigramme:string>

Project [Trigramme#729126 AS COL_TRIGRAMME_216272#729392]

ColumnarToRow

WholeStageCodegen (2)

FileScan parquet [Trigramme#729126] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/excel/cache/TARIF_FORFAIT_S_216188_40efcfa797c9..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<Trigramme:string>

Project [Trigramme#729204 AS COL_TRIGRAMME_216272#729393]

ColumnarToRow

WholeStageCodegen (3)

FileScan parquet [Trigramme#729204] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/excel/cache/TARIF_FORFAIT_S_216188_808989d69c5c..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<Trigramme:string>

Details

== Physical Plan ==
AdaptiveSparkPlan (22)
+- == Final Plan ==
   SortAggregate (14)
   +- ShuffleQueryStage (13), Statistics(sizeInBytes=176.0 B, rowCount=3)
      +- Exchange (12)
         +- SortAggregate (11)
            +- Union (10)
               :- * Project (3)
               :  +- * ColumnarToRow (2)
               :     +- Scan parquet  (1)
               :- * Project (6)
               :  +- * ColumnarToRow (5)
               :     +- Scan parquet  (4)
               +- * Project (9)
                  +- * ColumnarToRow (8)
                     +- Scan parquet  (7)
+- == Initial Plan ==
   SortAggregate (21)
   +- Exchange (20)
      +- SortAggregate (19)
         +- Union (18)
            :- Project (15)
            :  +- Scan parquet  (1)
            :- Project (16)
            :  +- Scan parquet  (4)
            +- Project (17)
               +- Scan parquet  (7)


(1) Scan parquet 
Output [1]: [Trigramme#729055]
Batched: true
Location: InMemoryFileIndex [file:/data/input/depot/excel/cache/TARIF_FORFAIT_S_216188_8c16894e8611e2723038563a84e8f82e/Region-PUBGUAMAR_tarifs_forfait_urgences.xlsx_28c6b5cf2e17f093396d9005fd88426d]
ReadSchema: struct<Trigramme:string>

(2) ColumnarToRow [codegen id : 1]
Input [1]: [Trigramme#729055]

(3) Project [codegen id : 1]
Output [1]: [Trigramme#729055 AS COL_TRIGRAMME_216272#729345]
Input [1]: [Trigramme#729055]

(4) Scan parquet 
Output [1]: [Trigramme#729126]
Batched: true
Location: InMemoryFileIndex [file:/data/input/depot/excel/cache/TARIF_FORFAIT_S_216188_40efcfa797c91f7b2d91dc7e15554bab/Region-PUBGUYRE_tarifs_forfait_urgences.xlsx_46d8ee25493717864f5499570cb757fd]
ReadSchema: struct<Trigramme:string>

(5) ColumnarToRow [codegen id : 2]
Input [1]: [Trigramme#729126]

(6) Project [codegen id : 2]
Output [1]: [Trigramme#729126 AS COL_TRIGRAMME_216272#729392]
Input [1]: [Trigramme#729126]

(7) Scan parquet 
Output [1]: [Trigramme#729204]
Batched: true
Location: InMemoryFileIndex [file:/data/input/depot/excel/cache/TARIF_FORFAIT_S_216188_808989d69c5c26978e67dd7f41818400/Region-PUBMET_tarifs_forfait_urgences.xlsx_85117cb97629c9c4984158ba77dd1307]
ReadSchema: struct<Trigramme:string>

(8) ColumnarToRow [codegen id : 3]
Input [1]: [Trigramme#729204]

(9) Project [codegen id : 3]
Output [1]: [Trigramme#729204 AS COL_TRIGRAMME_216272#729393]
Input [1]: [Trigramme#729204]

(10) Union

(11) SortAggregate
Input [1]: [COL_TRIGRAMME_216272#729345]
Keys: []
Functions [4]: [partial_count(1), partial_count(COL_TRIGRAMME_216272#729345), partial_min(COL_TRIGRAMME_216272#729345), partial_max(COL_TRIGRAMME_216272#729345)]
Aggregate Attributes [4]: [count#729394L, count#729395L, min#729396, max#729397]
Results [4]: [count#729398L, count#729399L, min#729400, max#729401]

(12) Exchange
Input [4]: [count#729398L, count#729399L, min#729400, max#729401]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=444700]

(13) ShuffleQueryStage
Output [4]: [count#729398L, count#729399L, min#729400, max#729401]
Arguments: 0

(14) SortAggregate
Input [4]: [count#729398L, count#729399L, min#729400, max#729401]
Keys: []
Functions [4]: [count(1), count(COL_TRIGRAMME_216272#729345), min(COL_TRIGRAMME_216272#729345), max(COL_TRIGRAMME_216272#729345)]
Aggregate Attributes [4]: [count(1)#729352L, count(COL_TRIGRAMME_216272#729345)#729355L, min(COL_TRIGRAMME_216272#729345)#729358, max(COL_TRIGRAMME_216272#729345)#729360]
Results [4]: [count(1)#729352L AS COL_TRIGRAMME_2162721#729354L, count(COL_TRIGRAMME_216272#729345)#729355L AS COL_TRIGRAMME_2162722#729357L, min(COL_TRIGRAMME_216272#729345)#729358 AS COL_TRIGRAMME_2162724#729359, max(COL_TRIGRAMME_216272#729345)#729360 AS COL_TRIGRAMME_2162725#729361]

(15) Project
Output [1]: [Trigramme#729055 AS COL_TRIGRAMME_216272#729345]
Input [1]: [Trigramme#729055]

(16) Project
Output [1]: [Trigramme#729126 AS COL_TRIGRAMME_216272#729392]
Input [1]: [Trigramme#729126]

(17) Project
Output [1]: [Trigramme#729204 AS COL_TRIGRAMME_216272#729393]
Input [1]: [Trigramme#729204]

(18) Union

(19) SortAggregate
Input [1]: [COL_TRIGRAMME_216272#729345]
Keys: []
Functions [4]: [partial_count(1), partial_count(COL_TRIGRAMME_216272#729345), partial_min(COL_TRIGRAMME_216272#729345), partial_max(COL_TRIGRAMME_216272#729345)]
Aggregate Attributes [4]: [count#729394L, count#729395L, min#729396, max#729397]
Results [4]: [count#729398L, count#729399L, min#729400, max#729401]

(20) Exchange
Input [4]: [count#729398L, count#729399L, min#729400, max#729401]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=444662]

(21) SortAggregate
Input [4]: [count#729398L, count#729399L, min#729400, max#729401]
Keys: []
Functions [4]: [count(1), count(COL_TRIGRAMME_216272#729345), min(COL_TRIGRAMME_216272#729345), max(COL_TRIGRAMME_216272#729345)]
Aggregate Attributes [4]: [count(1)#729352L, count(COL_TRIGRAMME_216272#729345)#729355L, min(COL_TRIGRAMME_216272#729345)#729358, max(COL_TRIGRAMME_216272#729345)#729360]
Results [4]: [count(1)#729352L AS COL_TRIGRAMME_2162721#729354L, count(COL_TRIGRAMME_216272#729345)#729355L AS COL_TRIGRAMME_2162722#729357L, min(COL_TRIGRAMME_216272#729345)#729358 AS COL_TRIGRAMME_2162724#729359, max(COL_TRIGRAMME_216272#729345)#729360 AS COL_TRIGRAMME_2162725#729361]

(22) AdaptiveSparkPlan
Output [4]: [COL_TRIGRAMME_2162721#729354L, COL_TRIGRAMME_2162722#729357L, COL_TRIGRAMME_2162724#729359, COL_TRIGRAMME_2162725#729361]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

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