[ https://issues.apache.org/jira/browse/SPARK-17936?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Justin Miller updated SPARK-17936: ---------------------------------- Comment: was deleted (was: I did look through them and I don't think they're related. Note that the error is different and this is trying to write data not read large amounts of data.) > "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 -- 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