Apache Spark Installation on Anaconda video(PySpark)

Apache Spark Installation on Anaconda using "conda". Python + Spark
#PySpark #sparkteam #anaconda #conda #spark #python #dataengineering #dataengineeringessentials

[@bubnak6240]

Well explained

[@ManojKumar-datarider]

Thanks for Liking it, kindly subscribe and share for more interesting tech videos.

[@silambarasanrathinam318]

Awesome explanation

[@ManojKumar-datarider]

Glad you liked it

[@Delchursing]

Good video.

[@ManojKumar-datarider]

Glad you enjoyed it, please subscribe and share .

[@BhargavSarikonda]

(pyspark_env) C:\Users\Lenovo>jupyter kernelspec list 'jupyter' is not recognized as an internal or external command, operable program or batch file. i am getting this error

[@ManojKumar-datarider]

Kindly check back and repeat the steps, you will not have this error.

[@saisunilsigiri4309]

Hi Manoj, Thanks for the clear instructions. i have followed all the steps but while running "sc = SparkContext.getOrCreate()" iam getting """ RuntimeError: Java gateway process exited before sending its port number """. how to resolve this issue?

[@sudiptachakraborty745]

I too encountered the same error. Kindly help. Thank you !

[@ManojKumar-datarider]

The error "Java gateway process exited before sending its port number" typically occurs when the Java Virtual Machine (JVM) used by PySpark fails to start or crashes unexpectedly. This can happen due to various reasons, such as: 1. Environment Issues: This error can occur if there are conflicts or issues with your system's environment variables, such as JAVA_HOME, PYSPARK_PYTHON, or PYSPARK_DRIVER_PYTHON. Make sure these variables are set correctly and point to the correct paths. 2. Memory Issues: If the JVM doesn't have enough memory allocated, it can cause this error. Try increasing the memory allocated to the JVM by setting the spark.driver.memory and spark.executor.memory configuration properties when creating the SparkContext. 3. Conflicting Java Versions: Having multiple Java installations on your system can lead to conflicts and cause this error. Ensure that you have only one Java installation and that it is compatible with the version of Spark you're using. 4.Corrupt Installation: If your Spark or Java installation is corrupted, it can cause the JVM to crash during startup. Here are some steps you can try to resolve the issue: 1. Check Environment Variables: Ensure that JAVA_HOME is set correctly and points to the directory where Java is installed. Also, check if PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are set to the correct Python executable. 2. Increase Memory: Try increasing the memory allocated to the JVM by adding the following lines before creating the SparkContext: import os os.environ["SPARK_DRIVER_MEMORY"] = "4g" This sets the driver memory to 4GB. Adjust the value based on your system's available memory. 3. Use a Single Java Version: Remove any other Java installations from your system or update your system's PATH variable to prioritize the Java version you want to use with Spark. 4. Reinstall Spark and Java: If the issue persists, consider reinstalling both Spark and Java to ensure a clean installation. 5. Check Logs: Look for any additional error messages or clues in the Spark logs, which can help identify the root cause of the issue. 6. Update Spark and Java: Ensure you're using the latest compatible versions of Spark and Java, as this issue may have been resolved in newer releases.

[@ManojKumar-datarider]

www.oracle.com/in/java/technologies/javase/javase8-archive-downloads.html Set Environment Variable and path properly and restart the syatem and try again. It will be fixed.

[@ManojKumar-datarider]

www.oracle.com/in/java/technologies/javase/javase8-archive-downloads.html Set Environment Variable and path properly and restart the syatem and try again. It will be fixed.