hdh-spark-job - Details for Query 1760

Submitted Time: 2026/09/03 11:31:34
Duration: 0.7 s
Succeeded Jobs: 2203 2204

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: 8 local merged chunks fetched: 0 shuffle write time total (min, med, max (stageId: taskId)) 2 ms (0 ms, 0 ms, 0 ms (stage 3214.0: task 25926)) 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: 8 local bytes read: 672.0 B fetch wait time: 0 ms remote bytes read: 0.0 B merged fetch fallback count: 0 local blocks read: 8 remote merged chunks fetched: 0 remote blocks read: 0 data size total (min, med, max (stageId: taskId)) 448.0 B (56.0 B, 56.0 B, 56.0 B (stage 3214.0: task 25926)) 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)) 672.0 B (84.0 B, 84.0 B, 84.0 B (stage 3214.0: task 25926))"]; 3 [labelType="html" label="SortAggregate number of output rows: 8"]; subgraph cluster4 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: total (min, med, max (stageId: taskId))\n1.1 s (73 ms, 150 ms, 166 ms (stage 3214.0: task 25931))"; 5 [labelType="html" label=" Project "]; } 6 [labelType="html" label="Scan csv number of output rows: 438,506 number of files read: 1 metadata time: 0 ms size of files read: 29.7 MiB"]; 1->0; 2->1; 3->2; 5->3; 6->5; }

AdaptiveSparkPlan isFinalPlan=true

SortAggregate(key=[], functions=[count(1), count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)])

Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=107174]

SortAggregate(key=[], functions=[partial_count(1), partial_count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), partial_min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), partial_max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)])

Project [SPECACC#448611 AS COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722]

WholeStageCodegen (1)

FileScan csv [SPECACC#448611] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/csv/execution/0B169EC1_E45B_447C_B262_7BC2954E3..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<SPECACC:string>

Details

== Physical Plan ==
AdaptiveSparkPlan (11)
+- == Final Plan ==
   SortAggregate (6)
   +- ShuffleQueryStage (5), Statistics(sizeInBytes=448.0 B, rowCount=8)
      +- Exchange (4)
         +- SortAggregate (3)
            +- * Project (2)
               +- Scan csv  (1)
+- == Initial Plan ==
   SortAggregate (10)
   +- Exchange (9)
      +- SortAggregate (8)
         +- Project (7)
            +- Scan csv  (1)


(1) Scan csv 
Output [1]: [SPECACC#448611]
Batched: false
Location: InMemoryFileIndex [file:/data/input/depot/csv/execution/0B169EC1_E45B_447C_B262_7BC2954E3BEE/current/RSF_Actes__patient.csv]
ReadSchema: struct<SPECACC:string>

(2) Project [codegen id : 1]
Output [1]: [SPECACC#448611 AS COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722]
Input [1]: [SPECACC#448611]

(3) SortAggregate
Input [1]: [COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722]
Keys: []
Functions [4]: [partial_count(1), partial_count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), partial_min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), partial_max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)]
Aggregate Attributes [4]: [count#448753L, count#448754L, min#448755, max#448756]
Results [4]: [count#448757L, count#448758L, min#448759, max#448760]

(4) Exchange
Input [4]: [count#448757L, count#448758L, min#448759, max#448760]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=107174]

(5) ShuffleQueryStage
Output [4]: [count#448757L, count#448758L, min#448759, max#448760]
Arguments: 0

(6) SortAggregate
Input [4]: [count#448757L, count#448758L, min#448759, max#448760]
Keys: []
Functions [4]: [count(1), count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)]
Aggregate Attributes [4]: [count(1)#448728L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448731L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448734, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448736]
Results [4]: [count(1)#448728L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07801#448730L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448731L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07802#448733L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448734 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07804#448735, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448736 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07805#448737]

(7) Project
Output [1]: [SPECACC#448611 AS COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722]
Input [1]: [SPECACC#448611]

(8) SortAggregate
Input [1]: [COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722]
Keys: []
Functions [4]: [partial_count(1), partial_count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), partial_min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), partial_max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)]
Aggregate Attributes [4]: [count#448753L, count#448754L, min#448755, max#448756]
Results [4]: [count#448757L, count#448758L, min#448759, max#448760]

(9) Exchange
Input [4]: [count#448757L, count#448758L, min#448759, max#448760]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=107162]

(10) SortAggregate
Input [4]: [count#448757L, count#448758L, min#448759, max#448760]
Keys: []
Functions [4]: [count(1), count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722), max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)]
Aggregate Attributes [4]: [count(1)#448728L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448731L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448734, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448736]
Results [4]: [count(1)#448728L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07801#448730L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448731L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07802#448733L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448734 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07804#448735, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448722)#448736 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07805#448737]

(11) AdaptiveSparkPlan
Output [4]: [COL_AFD799C8_68A7_4102_A165_EAFF501D07801#448730L, COL_AFD799C8_68A7_4102_A165_EAFF501D07802#448733L, COL_AFD799C8_68A7_4102_A165_EAFF501D07804#448735, COL_AFD799C8_68A7_4102_A165_EAFF501D07805#448737]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

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