How to Print the Scala Version in Apache Spark

Apache Spark is a powerful open-source processing engine for big data, built on top of the Scala programming language. While Spark applications can be written in various languages, including Java, Python, and R, Scala remains a core component of Spark’s architecture. Understanding the Scala version used by your Spark environment can be crucial for compatibility and debugging purposes. In this article, we’ll explore how to print the Scala version in a Spark environment.

Why Knowing the Scala Version Matters

Scala is a statically typed language that runs on the Java Virtual Machine (JVM). Different versions of Spark are built with specific versions of Scala, and using incompatible versions can lead to runtime errors or unexpected behavior. Knowing the Scala version can help you:

• Ensure compatibility with libraries and dependencies.
• Debug issues related to language features or syntax.
• Align your development environment with production settings.

Methods to Determine the Scala Version

1. Checking JAR File Names

One of the simplest ways to determine the Scala version used by Spark is to inspect the JAR files in the Spark installation directory. The Scala version is often embedded in the JAR file names. For example, a JAR file named spark-core_2.12-3.0.1.jar indicates that Spark is built with Scala 2.12.

Steps:

1. Navigate to the jars directory within your Spark installation.
2. Look for JAR files with names that include the Scala version, such as spark-core_2.12-3.0.1.jar.

2. Using the Spark Shell

If you have access to the Spark shell, you can execute Scala commands directly to print the Scala version.

Steps:

1. Start the Spark shell by running the spark-shell command in your terminal.
2. Execute the following Scala command to print the version:

println(scala.util.Properties.versionString)

This command will output the Scala version string, such as “version 2.12.10”.

3. Accessing Scala Version in PySpark

For those using PySpark, accessing the Scala version requires a bit of a workaround, as PySpark is primarily a Python API. However, you can leverage the underlying JVM to execute Scala commands.

Steps:

Start a PySpark session:

from pyspark.sql import SparkSession

spark = SparkSession.builder \
    .appName("ScalaVersionCheck") \
    .getOrCreate()

Access the Spark context and use the JVM to print the Scala version:

sc = spark.sparkContext
scala_version = sc._jvm.scala.util.Properties.versionString()
print("Scala version:", scala_version)

4. Referencing Spark Documentation

Each Spark release is associated with a specific Scala version. You can refer to the official Spark documentation or release notes to determine the Scala version for your Spark version.

Conclusion

Printing the Scala version in a Spark environment is a straightforward process that can be accomplished through various methods. Whether you’re inspecting JAR files, using the Spark shell, or leveraging PySpark’s access to the JVM, knowing the Scala version can help ensure compatibility and smooth operation of your Spark applications. By understanding the Scala version, you can better manage dependencies, troubleshoot issues, and align your development and production environments.