How to add custom jars to PySpark in a Jupyter notebook

There are two ways to add custom jars to PySpark in a Jupyter notebook:

1. Using the PYSPARK_SUBMIT_ARGS environment variable

The PYSPARK_SUBMIT_ARGS environment variable can be used to pass arguments to the spark-submit command when submitting a PySpark job. To add custom jars to PySpark using this environment variable, you can do the following:

1. First, download the JAR file you want to use and save it on your local machine. Next, create a new Python cell in Jupyter Notebook and import the “os” library.
2. In the same cell, set the environment variable “PYSPARK_SUBMIT_ARGS” to include the path to the JAR file you downloaded. The code to set the environment variable is as follows:

export PYSPARK_SUBMIT_ARGS="--jars <path-to-jar1>,<path-to-jar2>"

3. Start a Jupyter notebook and import PySpark.
4. Create a SparkContext and a SparkSession.
5. Use the SparkContext.addJar() method to add the custom jars to the SparkContext.

For example, the following code shows how to add two custom jars to PySpark:

import os

# Export the PYSPARK_SUBMIT_ARGS environment variable
os.environ['PYSPARK_SUBMIT_ARGS'] = '--jars /path/to/jar1.jar,/path/to/jar2.jar'

# Start a Jupyter notebook and import PySpark
import pyspark

# Create a SparkContext and a SparkSession
sc = pyspark.SparkContext()
spark = pyspark.sql.SparkSession(sc)

# Add the custom jars to the SparkContext
sc.addJar('/path/to/jar1.jar')
sc.addJar('/path/to/jar2.jar')

# Use the custom jars
df = spark.read.json('/path/to/data.json')
df.show()

2. Using the %configure magic command

The %configure magic command can be used to set Spark configuration properties in a Jupyter notebook. To add custom jars to PySpark using this magic command, you can do the following:

1. Open a Jupyter notebook and import PySpark.
2. Use the %configure magic command to set the spark.jars property to the path of the custom jars.

For example, the following code shows how to add two custom jars to PySpark using the %configure magic command:

import pyspark

# Use the %configure magic command to set the spark.jars property
%%configure -f {'spark.jars': '/path/to/jar1.jar,/path/to/jar2.jar'}

# Create a SparkContext and a SparkSession
sc = pyspark.SparkContext()
spark = pyspark.sql.SparkSession(sc)

# Use the custom jars
df = spark.read.json('/path/to/data.json')
df.show()