[
https://issues.apache.org/jira/browse/SPARK-29147?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon updated SPARK-29147:
---------------------------------
Priority: Major (was: Critical)
> Spark doesn't use shuffleHashJoin as expected
> ---------------------------------------------
>
> Key: SPARK-29147
> URL: https://issues.apache.org/jira/browse/SPARK-29147
> Project: Spark
> Issue Type: Question
> Components: Spark Core, SQL
> Affects Versions: 2.4.3, 2.4.4
> Reporter: Artsiom Yudovin
> Priority: Major
>
> I run the following code:
> {code:java}
> val spark = SparkSession.builder()
> .appName("ShuffleHashJoin")
> .master("local[*]")
> .config("spark.sql.autoBroadcastJoinThreshold", 0)
> .config("spark.sql.join.preferSortMergeJoin", value = false)
> .getOrCreate()
> import spark.implicits._
> val dataset = Seq(
> ("1", "playing"),
> ("2", "with"),
> ("3", "ShuffledHashJoinExec")
> ).toDF("id", "token")
> val dataset1 = Seq(
> ("1", "playing"),
> ("2", "with"),
> ("3", "ShuffledHashJoinExec")
> ).toDF("id1", "token")
>
> dataset.join(dataset1, $"id" === $"id1", "inner").foreach(t => println(t))
> {code}
> My expectation that Spark will use 'shuffleHashJoin' but I see in SparkUI and
> explain() that Spark uses 'sortMergeJoin'
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
