How to Include Multiple Jars in Spark Submit Classpath
Including multiple JARs in the Spark classpath during the submission of a Spark job can be done using the `–jars` option in the `spark-submit` command. This option allows you to specify multiple JAR files as a comma-separated list. Here’s a detailed explanation on how to do this:
### Using `–jars` Option
When submitting a Spark job, you can include multiple JAR files in the classpath using the `–jars` option. Each JAR file should be separated by a comma. Here is a basic syntax:
spark-submit --class <main-class> --master <master-url> --jars <path-to-jar-1>,<path-to-jar-2>,<path-to-jar-3> <application-jar> [application-arguments]
### Example
Let’s say you have the following JAR files that you want to include in your Spark job:
– `/path/to/jar1.jar`
– `/path/to/jar2.jar`
And your application JAR is located at `/path/to/app.jar` and your main class is `com.example.MainClass`. You can submit your Spark job as follows:
spark-submit --class com.example.MainClass --master yarn --jars /path/to/jar1.jar,/path/to/jar2.jar /path/to/app.jar [application-arguments]
### Ensuring Classpath Set on All Nodes
It is important to ensure that these JAR files are accessible to all nodes in the Spark cluster. The `–jars` option distributes the specified JARs to nodes in the cluster. If JARs are large or many, be mindful of network overhead. As an alternative, you can use a distributed storage system accessible to all nodes (e.g., HDFS, S3) and provide the URIs for the JAR locations. For example:
spark-submit --class com.example.MainClass --master yarn --jars hdfs:///path/to/jar1.jar,hdfs:///path/to/jar2.jar /path/to/app.jar [application-arguments]
### Example with PySpark
For a PySpark application, the `–jars` option works similarly. Here is an example with a PySpark script located at `/path/to/script.py`:
spark-submit --master yarn --jars /path/to/jar1.jar,/path/to/jar2.jar /path/to/script.py [application-arguments]
### Example with Scala
If you have a Scala application with the main class `com.example.MainClass`, the submission command is the same:
spark-submit --class com.example.MainClass --master yarn --jars /path/to/jar1.jar,/path/to/jar2.jar /path/to/app.jar [application-arguments]
### Example with Java
For a Java application, assume your main class is `com.example.MainApp`:
spark-submit --class com.example.MainApp --master yarn --jars /path/to/jar1.jar,/path/to/jar2.jar /path/to/app.jar [application-arguments]
Conclusion
Using the `–jars` option in the `spark-submit` command is a straightforward way to include multiple JARs in the classpath of your Spark job. Whether you are using PySpark, Scala, or Java, this practice ensures that all necessary dependencies are distributed to the cluster nodes, enabling smooth execution of your Spark applications.