Solving the Mysterious “Symbolic Reference Class is Not Accessible” Error in Spark

Are you struggling with the infamous “symbolic reference class is not accessible: class sun.util.calendar.ZoneInfo, from interface spark.sql.catalyst.util.SparkDateTimeUtils” error in your Spark application? You’re not alone! This pesky error has been plaguing Spark developers for years, leaving many scratching their heads in frustration. But fear not, dear reader, for we’re about to embark on a journey to demystify this error and provide a comprehensive guide to resolving it once and for all.

Understanding the Error

To tackle this error, we need to understand its root cause. The “symbolic reference class is not accessible” error occurs when Spark tries to access a class that’s not available in its classpath. In this specific case, the offending class is `sun.util.calendar.ZoneInfo`, which is part of the Java Runtime Environment (JRE). The error message is telling us that Spark can’t find this class, despite it being part of the JRE.

Why Does This Error Happen?

There are several reasons why this error might occur:

• Incorrect Java version: Spark requires a specific version of Java, which might not be the one installed on your system.
• Missing dependencies: You might have forgotten to include necessary dependencies in your Spark project, preventing Spark from finding the required classes.
• Classpath issues: Your Spark application’s classpath might be misconfigured, causing Spark to look for classes in the wrong places.
• Conflicting dependencies: Your project might have conflicting dependencies that are causing Spark to malfunction.

Resolving the Error

Now that we understand the error, let’s dive into the solutions!

Solution 1: Verify Your Java Version

Make sure you’re using the correct version of Java. Spark supports Java 8, 11, and 17. Check your Java version by running the following command:

$ java -version

If you’re not using one of the supported versions, upgrade or downgrade your Java installation accordingly.

Solution 2: Check Your Dependencies

Ensure you’ve included the necessary dependencies in your Spark project. Specifically, you need to include the `spark-sql` module, which includes the `SparkDateTimeUtils` class.

In your `pom.xml` file (if you’re using Maven), add the following dependency:

<dependency>
  <groupId>org.apache.spark</groupId>
  <artifactId>spark-sql_2.12</artifactId>
  <version>3.1.2</version>
</dependency>

In your `build.sbt` file (if you’re using SBT), add the following dependency:

libraryDependencies += "org.apache.spark" %% "spark-sql" % "3.1.2"

Solution 3: Configure Your Classpath

Verify that your Spark application’s classpath is correctly configured. You can do this by checking your `spark-submit` command or your Spark configuration file.

In your `spark-submit` command, ensure that you’re including the necessary JAR files:

$ spark-submit --class <main_class> --jars spark-sql_2.12-3.1.2.jar <your_jar_file>

In your Spark configuration file, ensure that you’ve added the necessary JAR files to the `spark.jars` property:

spark.jars = spark-sql_2.12-3.1.2.jar

Solution 4: Check for Conflicting Dependencies

Verify that you don’t have conflicting dependencies in your project. Check your `pom.xml` or `build.sbt` file for any dependencies that might be causing conflicts.

In particular, look out for dependencies that include `java.util.calendar` or `sun.util.calendar`, as these might conflict with the `ZoneInfo` class.

Additional Troubleshooting Steps

If the above solutions don’t work, try the following additional troubleshooting steps:

1. Check your Java installation’s ` rt.jar` file, which contains the `sun.util.calendar` package. Ensure that it’s not corrupted or missing.
2. Verify that your Spark application’s `spark.driver.extraClassPath` property is correctly set to include the necessary JAR files.
3. Try running your Spark application with the `–verbose` flag to get more detailed error messages.
4. Check your project’s build logs for any errors or warnings related to classpath or dependency issues.

Conclusion

The “symbolic reference class is not accessible” error can be frustrating, but by following the solutions outlined in this article, you should be able to resolve it and get your Spark application up and running smoothly. Remember to:

• Verify your Java version
• Check your dependencies
• Configure your classpath correctly
• Check for conflicting dependencies

By following these steps and troubleshooting tips, you’ll be well-equipped to tackle this error and ensure that your Spark application runs without a hitch.

Solution	Description
Verify Java Version	Ensure you’re using a supported Java version (8, 11, or 17)
Check Dependencies	Include necessary dependencies, such as spark-sql, in your project
Configure Classpath	Verify that your Spark application’s classpath is correctly configured
Check for Conflicting Dependencies	Ensure that you don’t have conflicting dependencies in your project

Happy Spark-ing!

Here are the 5 questions and answers about the error “symbolic reference class is not accessible: class sun.util.calendar.ZoneInfo, from interface spark.sql.catalyst.util.SparkDateTimeUtils”:

Frequently Asked Question

Are you stuck with the error “symbolic reference class is not accessible: class sun.util.calendar.ZoneInfo, from interface spark.sql.catalyst.util.SparkDateTimeUtils”? Worry no more! We’ve got you covered with these frequently asked questions.

I hope this helps!