SP1 - Details for Query 460

Submitted Time: 2026/02/23 14:36:12
Duration: 0.2 s
Succeeded Jobs: 610 612

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

digraph G { 0 [labelType="html" label=" AdaptiveSparkPlan "]; 1 [labelType="html" label=" TakeOrderedAndProject "]; subgraph cluster2 { isCluster="true"; label="WholeStageCodegen (2)\n \nduration: 12 ms"; 3 [labelType="html" label="HashAggregate spill size: 0.0 B time in aggregation build: 0 ms peak memory: 256.0 KiB number of output rows: 20 number of sort fallback tasks: 0 avg hash probes per key: 0"]; } 4 [labelType="html" label="AQEShuffleRead number of partitions: 1 partition data size: 801.0 B number of coalesced partitions: 1"]; 5 [labelType="html" label="Exchange shuffle records written: 20 local merged chunks fetched: 0 shuffle write time: 1 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: 20 local bytes read: 775.0 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: 480.0 B 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: 775.0 B"]; subgraph cluster6 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: 8 ms"; 7 [labelType="html" label="HashAggregate spill size: 0.0 B time in aggregation build: 2 ms peak memory: 256.0 KiB number of output rows: 20 number of sort fallback tasks: 0 avg hash probes per key: 0"]; 8 [labelType="html" label=" Project "]; 9 [labelType="html" label="Filter number of output rows: 20"]; 10 [labelType="html" label="ColumnarToRow number of output rows: 20 number of input batches: 1"]; } 11 [labelType="html" label="Scan parquet number of files read: 1 scan time: 2 ms metadata time: 0 ms size of files read: 683.0 B number of output rows: 20"]; 1->0; 3->1; 4->3; 5->4; 7->5; 8->7; 9->8; 10->9; 11->10; }

AdaptiveSparkPlan isFinalPlan=true

TakeOrderedAndProject(limit=100, orderBy=[COL_74E6D4E3_B982_4314_9251_72C890126F36#138469 DESC NULLS LAST], output=[COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476])

HashAggregate(keys=[COL_74E6D4E3_B982_4314_9251_72C890126F36#138469], functions=[])

WholeStageCodegen (2)

AQEShuffleRead coalesced

Exchange hashpartitioning(COL_74E6D4E3_B982_4314_9251_72C890126F36#138469, 10), ENSURE_REQUIREMENTS, [plan_id=13450]

HashAggregate(keys=[COL_74E6D4E3_B982_4314_9251_72C890126F36#138469], functions=[])

Project [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454 AS COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]

Filter CASE WHEN isnull(Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454))), )) THEN false ELSE Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454))), ) END

ColumnarToRow

WholeStageCodegen (1)

FileScan parquet [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454] Batched: true, DataFilters: [CASE WHEN isnull(Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_..., Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/output/cache/parquet/datablock/FINESS_PERIODE__307891], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<COL_4003FF80_371D_49FA_937B_9968FF6C0635:string>

Details

== Physical Plan ==
AdaptiveSparkPlan (17)
+- == Final Plan ==
   TakeOrderedAndProject (10)
   +- * HashAggregate (9)
      +- AQEShuffleRead (8)
         +- ShuffleQueryStage (7), Statistics(sizeInBytes=480.0 B, rowCount=20)
            +- Exchange (6)
               +- * HashAggregate (5)
                  +- * Project (4)
                     +- * Filter (3)
                        +- * ColumnarToRow (2)
                           +- Scan parquet  (1)
+- == Initial Plan ==
   TakeOrderedAndProject (16)
   +- HashAggregate (15)
      +- Exchange (14)
         +- HashAggregate (13)
            +- Project (12)
               +- Filter (11)
                  +- Scan parquet  (1)


(1) Scan parquet 
Output [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454]
Batched: true
Location: InMemoryFileIndex [file:/data/output/cache/parquet/datablock/FINESS_PERIODE__307891]
ReadSchema: struct<COL_4003FF80_371D_49FA_937B_9968FF6C0635:string>

(2) ColumnarToRow [codegen id : 1]
Input [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454]

(3) Filter [codegen id : 1]
Input [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454]
Condition : CASE WHEN isnull(Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454))), )) THEN false ELSE Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454))), ) END

(4) Project [codegen id : 1]
Output [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454 AS COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Input [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454]

(5) HashAggregate [codegen id : 1]
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Keys [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Functions: []
Aggregate Attributes: []
Results [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]

(6) Exchange
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Arguments: hashpartitioning(COL_74E6D4E3_B982_4314_9251_72C890126F36#138469, 10), ENSURE_REQUIREMENTS, [plan_id=13450]

(7) ShuffleQueryStage
Output [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Arguments: 0

(8) AQEShuffleRead
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Arguments: coalesced

(9) HashAggregate [codegen id : 2]
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Keys [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Functions: []
Aggregate Attributes: []
Results [2]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469 AS COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476, COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]

(10) TakeOrderedAndProject
Input [2]: [COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476, COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Arguments: 100, [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469 DESC NULLS LAST], [COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476]

(11) Filter
Input [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454]
Condition : CASE WHEN isnull(Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454))), )) THEN false ELSE Contains(str_remove_accent(upper(str_remove_accent(COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454))), ) END

(12) Project
Output [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454 AS COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Input [1]: [COL_4003FF80_371D_49FA_937B_9968FF6C0635#138454]

(13) HashAggregate
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Keys [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Functions: []
Aggregate Attributes: []
Results [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]

(14) Exchange
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Arguments: hashpartitioning(COL_74E6D4E3_B982_4314_9251_72C890126F36#138469, 10), ENSURE_REQUIREMENTS, [plan_id=13427]

(15) HashAggregate
Input [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Keys [1]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Functions: []
Aggregate Attributes: []
Results [2]: [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469 AS COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476, COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]

(16) TakeOrderedAndProject
Input [2]: [COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476, COL_74E6D4E3_B982_4314_9251_72C890126F36#138469]
Arguments: 100, [COL_74E6D4E3_B982_4314_9251_72C890126F36#138469 DESC NULLS LAST], [COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476]

(17) AdaptiveSparkPlan
Output [1]: [COL_065C4D77_AA25_45E8_A0BF_EDB8B4D6417A#138476]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

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