How to add dependencies as jar files or Python scripts to PySpark

This article is a part of my "100 data engineering tutorials in 100 days" challenge. (89/100)

When we want to use external dependencies in the PySpark code, we have two options. We can either pass them as jar files or Python scripts.

In this article, I will show how to do that when running a PySpark job using AWS EMR. The jar and Python files will be stored on S3 in a location accessible from the EMR cluster (remember to set the permissions).

First, we have to add the --jars and --py-files parameters to the spark-submit command while starting a new PySpark job:

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spark-submit --deploy-mode cluster \
    --jars s3://some_bucket/java_code.jar \
    --py-files s3://some_bucket/python_code.py \
    s3://some_bucket/pyspark_job.py 

In the pyspark_job.py file, I can import the code from the jar file just like any other dependency.

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import python_code.something

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Bartosz Mikulski
Bartosz Mikulski * data/machine learning engineer * conference speaker * co-founder of Software Craft Poznan & Poznan Scala User Group

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