Pass Environment Variables to Executors in PySpark

access_time 12 months ago visibility596 comment 0

Sometime it is necessary to pass environment variables to Spark executors. To pass environment variable to executors, use setExecutorEnv function of SparkConf class.

Code snippet

In the following code snippet, an environment variable name ENV_NAME is set up with value as 'ENV_Value'.

from pyspark import SparkConf
from pyspark.sql import SparkSession

appName = "Python Example - Pass Environment Variable to Executors"
master = 'yarn'

# Create Spark session
conf = SparkConf().setMaster(master).setAppName(
    appName).setExecutorEnv('ENV_NAME', 'ENV_Value')

spark = SparkSession.builder.config(conf=conf) \
    .getOrCreate()
copyright This page is subject to Site terms.
Like this article?
Share on

Please log in or register to comment.

account_circle Log in person_add Register

Log in with external accounts

Want to publish your article on Kontext?

Learn more

Kontext Column

Created for everyone to publish data, programming and cloud related articles.
Follow three steps to create your columns.


Learn more arrow_forward

More from Kontext

Schema Merging (Evolution) with Parquet in Spark and Hive

local_offer parquet local_offer pyspark local_offer spark-2-x local_offer hive local_offer hdfs local_offer spark-advanced

visibility 5413
thumb_up 1
access_time 10 months ago

Schema evolution is supported by many frameworks or data serialization systems such as Avro, Orc, Protocol Buffer and Parquet. With schema evolution, one set of data can be stored in multiple files with different but compatible schema. In Spark, Parquet data source can detect and merge schema of ...

local_offer spark local_offer linux local_offer WSL local_offer big-data-on-wsl

visibility 7471
thumb_up 0
access_time 2 years ago

This pages summarizes the steps to install the latest version 2.4.3 of Apache Spark on Windows 10 via Windows Subsystem for Linux (WSL). Follow either of the following pages to install WSL in a system or non-system drive on your Windows 10. Install Windows Subsystem for Linux on a Non-System ...

PySpark Read Multiple Lines Records from CSV

local_offer pyspark local_offer spark-2-x local_offer python local_offer spark-file-operations

visibility 1679
thumb_up 0
access_time 8 months ago

CSV is a common format used when extracting and exchanging data between systems and platforms. Once CSV file is ingested into HDFS, you can easily read them as DataFrame in Spark. However there are a few options you need to pay attention to especially if you source file: Has records across ...

About column

Code snippets and tips for various programming languages/frameworks.

rss_feed Subscribe RSS