digraph G {
0 [labelType="html" label="<br><b>AdaptiveSparkPlan</b><br><br>"];
subgraph cluster1 {
isCluster="true";
label="WholeStageCodegen (3)\n \nduration: 0 ms";
2 [labelType="html" label="<b>HashAggregate</b><br><br>time in aggregation build: 0 ms<br>number of output rows: 1"];
}
3 [labelType="html" label="<b>Exchange</b><br><br>shuffle records written: 11<br>local merged chunks fetched: 0<br>shuffle write time total (min, med, max (stageId: taskId))<br>4 ms (0 ms, 0 ms, 0 ms (stage 2514.0: task 9981))<br>remote merged bytes read: 0.0 B<br>local merged blocks fetched: 0<br>corrupt merged block chunks: 0<br>remote merged reqs duration: 0 ms<br>remote merged blocks fetched: 0<br>records read: 11<br>local bytes read: 649.0 B<br>fetch wait time: 0 ms<br>remote bytes read: 0.0 B<br>merged fetch fallback count: 0<br>local blocks read: 11<br>remote merged chunks fetched: 0<br>remote blocks read: 0<br>data size total (min, med, max (stageId: taskId))<br>176.0 B (16.0 B, 16.0 B, 16.0 B (stage 2514.0: task 9971))<br>local merged bytes read: 0.0 B<br>number of partitions: 1<br>remote reqs duration: 0 ms<br>remote bytes read to disk: 0.0 B<br>shuffle bytes written total (min, med, max (stageId: taskId))<br>649.0 B (59.0 B, 59.0 B, 59.0 B (stage 2514.0: task 9971))"];
subgraph cluster4 {
isCluster="true";
label="WholeStageCodegen (2)\n \nduration: total (min, med, max (stageId: taskId))\n969 ms (61 ms, 80 ms, 154 ms (stage 2514.0: task 9981))";
5 [labelType="html" label="<b>HashAggregate</b><br><br>time in aggregation build total (min, med, max (stageId: taskId))<br>965 ms (61 ms, 79 ms, 153 ms (stage 2514.0: task 9981))<br>number of output rows: 11"];
}
6 [labelType="html" label="<br><b>Union</b><br><br>"];
7 [labelType="html" label="<b>Scan csv </b><br><br>number of output rows: 601,244<br>number of files read: 1<br>metadata time: 0 ms<br>size of files read: 104.1 MiB"];
subgraph cluster8 {
isCluster="true";
label="WholeStageCodegen (1)\n \nduration: 154 ms";
9 [labelType="html" label="<b>Scan JDBCRelation((SELECT \"IPP\", \"Code \u00E9tablissement\", \"Lib \u00E9tablissement\", \"Date pr\u00E9l\u00E9vement\", \"Code examen Biologie\", \"Libell\u00E9 examen Biologie\", \"R\u00E9sultat (num\u00E9rique)\", \"Unite\", \"Code m\u00E9decin\", \"Nom m\u00E9decin\", \"Pr\u00E9nom m\u00E9decin\", \"Nom document biologie\", \"Nom complet document biologie\", \"Venue\", \"Borne basse\", \"Borne haute\" FROM \"public\".\"biologie_etb_lin\") as x) [numPartitions=1] </b><br><br>number of output rows: 471,858"];
}
2->0;
3->2;
5->3;
6->5;
7->6;
9->6;
}
10
AdaptiveSparkPlan isFinalPlan=true
HashAggregate(keys=[], functions=[count(1)])
WholeStageCodegen (3)
Exchange SinglePartition, ENSURE_REQUIREMENTS, [plan_id=95064]
HashAggregate(keys=[], functions=[partial_count(1)])
WholeStageCodegen (2)
Union
FileScan csv [] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/csv/tmp/BIOLOGIE_SAINT__19889/BIOLOGIE_Etab_STA..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<>
Scan JDBCRelation((SELECT "IPP", "Code établissement", "Lib établissement", "Date prélévement", "Code examen Biologie", "Libellé examen Biologie", "Résultat (numérique)", "Unite", "Code médecin", "Nom médecin", "Prénom médecin", "Nom document biologie", "Nom complet document biologie", "Venue", "Borne basse", "Borne haute" FROM "public"."biologie_etb_lin") as x) [numPartitions=1] [] PushedFilters: [], ReadSchema: struct<>
WholeStageCodegen (1)