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Apache Spark commented on SPARK-18207: -------------------------------------- User 'kiszk' has created a pull request for this issue: https://github.com/apache/spark/pull/15745 > class > "org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection" > grows beyond 64 KB > ------------------------------------------------------------------------------------------------------------ > > Key: SPARK-18207 > URL: https://issues.apache.org/jira/browse/SPARK-18207 > Project: Spark > Issue Type: Bug > Components: Optimizer, SQL > Affects Versions: 2.0.1, 2.1.0 > Reporter: Don Drake > Attachments: spark-18207.txt > > > I have 2 wide dataframes that contain nested data structures, when I explode > one of the dataframes, it doesn't include records with an empty nested > structure (outer explode not supported). So, I create a similar dataframe > with null values and union them together. See SPARK-13721 for more details > as to why I have to do this. > I was hoping that SPARK-16845 was going to address my issue, but it does not. > I was asked by [~lwlin] to open this JIRA. > I will attach a code snippet that can be pasted into spark-shell that > duplicates my code and the exception. This worked just fine in Spark 1.6.x. > {code} > org.apache.spark.SparkException: Job aborted due to stage failure: Task 35 in > stage 5.0 failed 4 times, most recent failure: Lost task 35.3 in stage 5.0 > (TID 812, somehost.mydomain.com, executor 8): > java.util.concurrent.ExecutionException: java.lang.Exception: failed to > compile: org.codehaus.janino.JaninoRuntimeException: Code of method > "apply(Lorg/apache/spark/sql/catalyst/InternalRow;)Lorg/apache/spark/sql/catalyst/expressions/UnsafeRow;" > of class > "org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection" > grows beyond 64 KB > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org