Apache Spark job fails with InvalidClassException, class version mismatch, in Azure HDInsight

This article describes troubleshooting steps and possible resolutions for issues when using Apache Spark components in Azure HDInsight clusters.


You try to create an Apache Spark job in a Spark 2.x cluster. It fails with an error similar to the following:

18/09/18 09:32:26 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID 1, wn7-dev-co.2zyfbddadfih0xdq0cdja4g.ax.internal.cloudapp.net, executor 4): java.io.InvalidClassException:
org.apache.commons.lang3.time.FastDateFormat; local class incompatible: stream classdesc serialVersionUID = 2, local class serialVersionUID = 1
        at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:699)
        at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1885)
        at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1751)
        at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2042)
        at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1573)


This error can be caused by adding an additional jar to the spark.yarn.jars config, specifically a shaded jar that includes a different version of the commons-lang3 package and introduces a class mismatch. By default, Spark 2.1/2/3 uses version 3.5 of commons-lang3.


To shade a library is to put its contents into your own jar, changing its package. This differs from packaging the library, which is putting the library into your own jar without repackaging.


Either remove the jar, or recompile the customized jar (AzureLogAppender) and use maven-shade-plugin to relocate classes.

Next steps

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