hdh-spark-job - Details for Query 1754

Submitted Time: 2026/09/03 11:27:48
Duration: 0.7 s
Succeeded Jobs: 2197 2198

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 3206.0: task 25906)) 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 3206.0: task 25906)) 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 3206.0: task 25906))"]; 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))\n1.3 s (81 ms, 173 ms, 194 ms (stage 3206.0: task 25907))"; 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#448380), min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)])

Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=107035]

SortAggregate(key=[], functions=[partial_count(1), partial_count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), partial_min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), partial_max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)])

Project [SPECACC#448269 AS COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380]

WholeStageCodegen (1)

FileScan csv [SPECACC#448269] 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#448269]
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#448269 AS COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380]
Input [1]: [SPECACC#448269]

(3) SortAggregate
Input [1]: [COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380]
Keys: []
Functions [4]: [partial_count(1), partial_count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), partial_min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), partial_max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)]
Aggregate Attributes [4]: [count#448411L, count#448412L, min#448413, max#448414]
Results [4]: [count#448415L, count#448416L, min#448417, max#448418]

(4) Exchange
Input [4]: [count#448415L, count#448416L, min#448417, max#448418]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=107035]

(5) ShuffleQueryStage
Output [4]: [count#448415L, count#448416L, min#448417, max#448418]
Arguments: 0

(6) SortAggregate
Input [4]: [count#448415L, count#448416L, min#448417, max#448418]
Keys: []
Functions [4]: [count(1), count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)]
Aggregate Attributes [4]: [count(1)#448386L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448389L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448392, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448394]
Results [4]: [count(1)#448386L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07801#448388L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448389L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07802#448391L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448392 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07804#448393, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448394 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07805#448395]

(7) Project
Output [1]: [SPECACC#448269 AS COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380]
Input [1]: [SPECACC#448269]

(8) SortAggregate
Input [1]: [COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380]
Keys: []
Functions [4]: [partial_count(1), partial_count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), partial_min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), partial_max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)]
Aggregate Attributes [4]: [count#448411L, count#448412L, min#448413, max#448414]
Results [4]: [count#448415L, count#448416L, min#448417, max#448418]

(9) Exchange
Input [4]: [count#448415L, count#448416L, min#448417, max#448418]
Arguments: SinglePartition, ENSURE_REQUIREMENTS, [plan_id=107023]

(10) SortAggregate
Input [4]: [count#448415L, count#448416L, min#448417, max#448418]
Keys: []
Functions [4]: [count(1), count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380), max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)]
Aggregate Attributes [4]: [count(1)#448386L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448389L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448392, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448394]
Results [4]: [count(1)#448386L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07801#448388L, count(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448389L AS COL_AFD799C8_68A7_4102_A165_EAFF501D07802#448391L, min(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448392 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07804#448393, max(COL_AFD799C8_68A7_4102_A165_EAFF501D0780#448380)#448394 AS COL_AFD799C8_68A7_4102_A165_EAFF501D07805#448395]

(11) AdaptiveSparkPlan
Output [4]: [COL_AFD799C8_68A7_4102_A165_EAFF501D07801#448388L, COL_AFD799C8_68A7_4102_A165_EAFF501D07802#448391L, COL_AFD799C8_68A7_4102_A165_EAFF501D07804#448393, COL_AFD799C8_68A7_4102_A165_EAFF501D07805#448395]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

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