[jira] [Assigned] (SPARK-40622) Result of a single task in collect() must fit in 2GB

["Apache Spark (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-40622?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-40622:
------------------------------------

    Assignee: Apache Spark

> Result of a single task in collect() must fit in 2GB
> ----------------------------------------------------
>
>                 Key: SPARK-40622
>                 URL: https://issues.apache.org/jira/browse/SPARK-40622
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core, SQL
>    Affects Versions: 3.3.0
>            Reporter: Ziqi Liu
>            Assignee: Apache Spark
>            Priority: Major
>
> when collecting results, data from single partition/task is serialized through byte array or ByteBuffer(which is backed by byte array as well), therefore it's subject to java array max size limit(in terms of byte array, it's 2GB).
>  
> Construct a single partition larger than 2GB and collect it can easily reproduce the issue
> {code:java}
> // create data of size ~3GB in single partition, which exceeds the byte array limit
> // random gen to make sure it's poorly compressed
> val df = spark.range(0, 3000, 1, 1).selectExpr("id", s"genData(id, 1000000) as data")
> withSQLConf("spark.databricks.driver.localMaxResultSize" -> "4g") {
>   withSQLConf("spark.sql.useChunkedBuffer" -> "true") {
>     df.queryExecution.executedPlan.executeCollect()
>   }
> } {code}
>  will get a OOM error from [https://github.com/AdoptOpenJDK/openjdk-jdk11/blob/master/src/java.base/share/classes/java/io/ByteArrayOutputStream.java#L125]
>  
> Consider using ChunkedByteBuffer to replace byte array in order to bypassing this limit



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