EVAL1_SPC1 - Details for Query 677

Submitted Time: 2026/02/20 13:26:42
Duration: 0.3 s
Succeeded Jobs: 824 825

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: 2 ms"; 3 [labelType="html" label="HashAggregate spill size: 0.0 B time in aggregation build: 0 ms peak memory: 64.2 MiB number of output rows: 2 number of sort fallback tasks: 0 avg hash probes per key: 1"]; } 4 [labelType="html" label="AQEShuffleRead number of partitions: 1 partition data size: 144.0 B number of coalesced partitions: 1"]; 5 [labelType="html" label="Exchange shuffle records written: 2 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: 2 local bytes read: 142.0 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: 64.0 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: 142.0 B"]; subgraph cluster6 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: 82 ms"; 7 [labelType="html" label="HashAggregate spill size: 0.0 B time in aggregation build: 4 ms peak memory: 256.0 KiB number of output rows: 2 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: 189"]; 10 [labelType="html" label="ColumnarToRow number of output rows: 189 number of input batches: 1"]; } 11 [labelType="html" label="Scan parquet number of files read: 1 scan time: 3 ms metadata time: 0 ms size of files read: 11.3 KiB number of output rows: 189"]; 1->0; 3->1; 4->3; 5->4; 7->5; 8->7; 9->8; 10->9; 11->10; }

AdaptiveSparkPlan isFinalPlan=true

TakeOrderedAndProject(limit=10, orderBy=[COL_GENDER_33352#105311L DESC NULLS LAST], output=[COL_GENDER_33351#105300,COL_GENDER_33352#105311L])

HashAggregate(keys=[COL_GENDER_3335#105286], functions=[count(1)])

WholeStageCodegen (2)

AQEShuffleRead coalesced

Exchange hashpartitioning(COL_GENDER_3335#105286, 10), ENSURE_REQUIREMENTS, [plan_id=15943]

HashAggregate(keys=[COL_GENDER_3335#105286], functions=[partial_count(1)])

Project [GENDER_3335#105239 AS COL_GENDER_3335#105286]

Filter isnotnull(GENDER_3335#105239)

ColumnarToRow

WholeStageCodegen (1)

FileScan parquet [GENDER_3335#105239] Batched: true, DataFilters: [isnotnull(GENDER_3335#105239)], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/output/cache/parquet/uet/PATIENT_3332], PartitionFilters: [], PushedFilters: [IsNotNull(GENDER_3335)], ReadSchema: struct<GENDER_3335:string>

Details

== Physical Plan ==
AdaptiveSparkPlan (17)
+- == Final Plan ==
   TakeOrderedAndProject (10)
   +- * HashAggregate (9)
      +- AQEShuffleRead (8)
         +- ShuffleQueryStage (7), Statistics(sizeInBytes=64.0 B, rowCount=2)
            +- 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]: [GENDER_3335#105239]
Batched: true
Location: InMemoryFileIndex [file:/data/output/cache/parquet/uet/PATIENT_3332]
PushedFilters: [IsNotNull(GENDER_3335)]
ReadSchema: struct<GENDER_3335:string>

(2) ColumnarToRow [codegen id : 1]
Input [1]: [GENDER_3335#105239]

(3) Filter [codegen id : 1]
Input [1]: [GENDER_3335#105239]
Condition : isnotnull(GENDER_3335#105239)

(4) Project [codegen id : 1]
Output [1]: [GENDER_3335#105239 AS COL_GENDER_3335#105286]
Input [1]: [GENDER_3335#105239]

(5) HashAggregate [codegen id : 1]
Input [1]: [COL_GENDER_3335#105286]
Keys [1]: [COL_GENDER_3335#105286]
Functions [1]: [partial_count(1)]
Aggregate Attributes [1]: [count#105318L]
Results [2]: [COL_GENDER_3335#105286, count#105319L]

(6) Exchange
Input [2]: [COL_GENDER_3335#105286, count#105319L]
Arguments: hashpartitioning(COL_GENDER_3335#105286, 10), ENSURE_REQUIREMENTS, [plan_id=15943]

(7) ShuffleQueryStage
Output [2]: [COL_GENDER_3335#105286, count#105319L]
Arguments: 0

(8) AQEShuffleRead
Input [2]: [COL_GENDER_3335#105286, count#105319L]
Arguments: coalesced

(9) HashAggregate [codegen id : 2]
Input [2]: [COL_GENDER_3335#105286, count#105319L]
Keys [1]: [COL_GENDER_3335#105286]
Functions [1]: [count(1)]
Aggregate Attributes [1]: [count(1)#105309L]
Results [2]: [COL_GENDER_3335#105286 AS COL_GENDER_33351#105300, count(1)#105309L AS COL_GENDER_33352#105311L]

(10) TakeOrderedAndProject
Input [2]: [COL_GENDER_33351#105300, COL_GENDER_33352#105311L]
Arguments: 10, [COL_GENDER_33352#105311L DESC NULLS LAST], [COL_GENDER_33351#105300, COL_GENDER_33352#105311L]

(11) Filter
Input [1]: [GENDER_3335#105239]
Condition : isnotnull(GENDER_3335#105239)

(12) Project
Output [1]: [GENDER_3335#105239 AS COL_GENDER_3335#105286]
Input [1]: [GENDER_3335#105239]

(13) HashAggregate
Input [1]: [COL_GENDER_3335#105286]
Keys [1]: [COL_GENDER_3335#105286]
Functions [1]: [partial_count(1)]
Aggregate Attributes [1]: [count#105318L]
Results [2]: [COL_GENDER_3335#105286, count#105319L]

(14) Exchange
Input [2]: [COL_GENDER_3335#105286, count#105319L]
Arguments: hashpartitioning(COL_GENDER_3335#105286, 10), ENSURE_REQUIREMENTS, [plan_id=15920]

(15) HashAggregate
Input [2]: [COL_GENDER_3335#105286, count#105319L]
Keys [1]: [COL_GENDER_3335#105286]
Functions [1]: [count(1)]
Aggregate Attributes [1]: [count(1)#105309L]
Results [2]: [COL_GENDER_3335#105286 AS COL_GENDER_33351#105300, count(1)#105309L AS COL_GENDER_33352#105311L]

(16) TakeOrderedAndProject
Input [2]: [COL_GENDER_33351#105300, COL_GENDER_33352#105311L]
Arguments: 10, [COL_GENDER_33352#105311L DESC NULLS LAST], [COL_GENDER_33351#105300, COL_GENDER_33352#105311L]

(17) AdaptiveSparkPlan
Output [2]: [COL_GENDER_33351#105300, COL_GENDER_33352#105311L]
Arguments: isFinalPlan=true

SQL / DataFrame Properties

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