How to Resolve Spark Java error NoClassDefFoundError on Amazon Elastic MapReduce

How to Resolve Spark Java error NoClassDefFoundError on Amazon Elastic MapReduce

As a data scientist or software engineer, you might encounter the NoClassDefFoundError while using Apache Spark on Amazon Elastic MapReduce (EMR). This error typically occurs when the Java Virtual Machine (JVM) cannot find a class it needs due to various reasons. In this tutorial, we will explore how to resolve this issue.

Understanding the Error

Before we delve into the solution, let’s understand the NoClassDefFoundError. This error is a subclass of java.lang.LinkageError and occurs when the JVM can’t find the class it needs at runtime, even though the code compiled without error. This issue is often due to a classpath issue, issues with JAR files, or dependency conflicts.

Identifying the Root Cause

The first step towards resolving this error is identifying the root cause. You can do this by inspecting your Spark logs. Use the following command in your EMR terminal:

yarn logs -applicationId <your application id>

Search the logs for NoClassDefFoundError to find the problematic class.

Solution 1: Verify Classpath Settings

The first solution to try is to verify your classpath settings. In Spark, you can use the --driver-class-path and --executor-class-path options to add directories, JAR, and ZIP files to the classpath. Here’s an example:

spark-submit --class com.mycompany.MyApp --driver-class-path /path/to/your/library.jar --executor-class-path /path/to/your/library.jar yourSparkJob.jar

Solution 2: Include Missing Dependencies

If the NoClassDefFoundError error is caused by a missing dependency, you can include the missing dependencies in your JAR file. The Maven Assembly Plugin or the SBT Assembly Plugin can help you create a so-called “fat” JAR that includes all dependencies:

For Maven:

<plugin>
  <artifactId>maven-assembly-plugin</artifactId>
  <configuration>
    <archive>
      <manifest>
        <mainClass>com.mycompany.MyApp</mainClass>
      </manifest>
    </archive>
    <descriptorRefs>
      <descriptorRef>jar-with-dependencies</descriptorRef>
    </descriptorRefs>
  </configuration>
</plugin>

For SBT:

assemblyOption in assembly := (assemblyOption in assembly).value.copy(includeScala = false)
assemblyJarName in assembly := s"\${name.value}-\${version.value}-fat.jar"

Then, submit your Spark job with the new JAR file:

spark-submit --class com.mycompany.MyApp yourSparkJob-fat.jar

Solution 3: Correctly Position Your JARs in spark.jars

If the error is due to JAR order in spark.jars, you should specify your JARs before the Spark JARs. Here’s an example:

spark-submit --jars /path/to/your/library.jar,/path/to/spark/jars/* --class com.mycompany.MyApp yourSparkJob.jar

Conclusion

In this tutorial, we’ve covered how to resolve the NoClassDefFoundError error when using Spark on Amazon EMR. We’ve discussed understanding the error, how to identify the root cause, and provided three solutions to solve the issue.

Remember, the NoClassDefFoundError typically indicates a classpath or dependency issue. By ensuring your classpath settings and dependencies are correct, you can keep your Spark applications running smoothly on EMR.

Happy Sparking!

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