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Posted to issues@spark.apache.org by "Yuming Wang (Jira)" <ji...@apache.org> on 2019/11/06 08:58:00 UTC
[jira] [Issue Comment Deleted] (SPARK-29655) Prefer bucket join if
adaptive execution is enabled and maxNumPostShufflePartitions != bucket
number
[ https://issues.apache.org/jira/browse/SPARK-29655?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Yuming Wang updated SPARK-29655:
--------------------------------
Comment: was deleted
(was: I'm working on.)
> Prefer bucket join if adaptive execution is enabled and maxNumPostShufflePartitions != bucket number
> ----------------------------------------------------------------------------------------------------
>
> Key: SPARK-29655
> URL: https://issues.apache.org/jira/browse/SPARK-29655
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Yuming Wang
> Priority: Major
>
> Prefer bucketing join if adaptive execution is enabled and maxNumPostShufflePartitions != bucket number. How to reproduce:
> {code:scala}
> import org.apache.spark.sql.SaveMode
> spark.conf.set("spark.sql.autoBroadcastJoinThreshold", -1)
> spark.conf.set("spark.sql.shuffle.partitions", 4)
> val bucketedTableName = "bucketed_table"
> spark.range(10).write.bucketBy(4, "id").sortBy("id").mode(SaveMode.Overwrite).saveAsTable(bucketedTableName)
> val bucketedTable = spark.table(bucketedTableName)
> val df = spark.range(4)
> df.join(bucketedTable, "id").explain()
> spark.conf.set("spark.sql.adaptive.enabled", true)
> spark.conf.set("spark.sql.adaptive.shuffle.maxNumPostShufflePartitions", 5)
> df.join(bucketedTable, "id").explain()
> {code}
> Output:
> {noformat}
> == Physical Plan ==
> AdaptiveSparkPlan(isFinalPlan=false)
> +- Project [id#5L]
> +- SortMergeJoin [id#5L], [id#3L], Inner
> :- Sort [id#5L ASC NULLS FIRST], false, 0
> : +- Exchange hashpartitioning(id#5L, 5), true, [id=#92]
> : +- Range (0, 4, step=1, splits=16)
> +- Sort [id#3L ASC NULLS FIRST], false, 0
> +- Exchange hashpartitioning(id#3L, 5), true, [id=#93]
> +- Project [id#3L]
> +- Filter isnotnull(id#3L)
> +- FileScan parquet default.bucketed_table[id#3L] Batched: true, DataFilters: [isnotnull(id#3L)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-preview-bin-hadoop3.2/spark-warehouse/bucketed_table], PartitionFilters: [], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint>, SelectedBucketsCount: 4 out of 4
> {noformat}
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