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https://issues.apache.org/jira/browse/SPARK-17936?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-17936.
-------------------------------
    Resolution: Duplicate

Duplicate of several JIRAs -- have a look through first.

> "CodeGenerator - failed to compile: 
> org.codehaus.janino.JaninoRuntimeException: Code of" method Error
> -----------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-17936
>                 URL: https://issues.apache.org/jira/browse/SPARK-17936
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.0.1
>            Reporter: Justin Miller
>
> Greetings. I'm currently in the process of migrating a project I'm working on 
> from Spark 1.6.2 to 2.0.1. The project uses Spark Streaming to convert Thrift 
> structs coming from Kafka into Parquet files stored in S3. This conversion 
> process works fine in 1.6.2 but I think there may be a bug in 2.0.1. I'll 
> paste the stack trace below.
> org.codehaus.janino.JaninoRuntimeException: Code of method 
> "(Lorg/apache/spark/sql/catalyst/expressions/GeneratedClass;[Ljava/lang/Object;)V"
>  of class 
> "org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection"
>  grows beyond 64 KB
>       at org.codehaus.janino.CodeContext.makeSpace(CodeContext.java:941)
>       at org.codehaus.janino.CodeContext.write(CodeContext.java:854)
>       at org.codehaus.janino.UnitCompiler.writeShort(UnitCompiler.java:10242)
>       at org.codehaus.janino.UnitCompiler.writeLdc(UnitCompiler.java:9058)
> Also, later on:
> 07:35:30.191 ERROR o.a.s.u.SparkUncaughtExceptionHandler - Uncaught exception 
> in thread Thread[Executor task launch worker-6,5,run-main-group-0]
> java.lang.OutOfMemoryError: Java heap space
> I've seen similar issues posted, but those were always on the query side. I 
> have a hunch that this is happening at write time as the error occurs after 
> batchDuration. Here's the write snippet.
> stream.
>       flatMap {
>         case Success(row) =>
>           thriftParseSuccess += 1
>           Some(row)
>         case Failure(ex) =>
>           thriftParseErrors += 1
>           logger.error("Error during deserialization: ", ex)
>           None
>       }.foreachRDD { rdd =>
>         val sqlContext = SQLContext.getOrCreate(rdd.context)
>         transformer(sqlContext.createDataFrame(rdd, converter.schema))
>           .coalesce(coalesceSize)
>           .write
>           .mode(Append)
>           .partitionBy(partitioning: _*)
>           .parquet(parquetPath)
>       }
> Please let me know if you can be of assistance and if there's anything I can 
> do to help.
> Best,
> Justin



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