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Too Large Frame error

By Dinesh
Description: When the size of the shuffle data blocks exceeds the limit of 2 GB, which spark can handle, the following error occurs.

org.apache.spark.shuffle.FetchFailedException: Too large frame: XXXXXXXXXX at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:513) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:444)    Caused by: java.lang.IllegalArgumentException: Too large frame: XXXXXXXXXX at org.spark_project.guava.base.Preconditions.checkArgument(Preconditions.java:119) at org.apache.spark.network.util.TransportFrameDecoder.decodeNext(TransportFrameDecoder.java:133)

Solutions that  may work  -

  1. Set spark.sql.shuffle.partitions
  2. Identify the DataFrame that is causing the issue.
    1. After the DataFrame is identified, repartition the DataFrame by using df.repartition()
A possible reason to problem above can be data skewness.

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