List of Important Apache Spark Commands commonly used

Nixon Data List of Important Apache Spark Commands commonly used

Here are some important Apache Spark commands that you may find useful:

  1. spark-submit: This command is used to submit a Spark application for execution on a cluster. It takes various arguments to specify the location of the application code, the main class, and the dependencies.
  2. spark-shell: This command starts the Spark shell, which is an interactive shell for running Spark commands.
  3. spark-sql: This command starts the Spark SQL CLI (command-line interface), which allows you to run SQL queries against data stored in Spark.
  4. spark-submit --master yarn: This command submits a Spark application to run on a YARN cluster.
  5. spark-submit --class <main class> --executor-memory <memory> --total-executor-cores <cores> <application JAR>: This command submits a Spark application with specific settings for the executor memory and number of cores.
  6. spark.stop(): This command stops the SparkContext, which is used to stop a Spark application.
  7. sc.textFile(): This command reads a text file from HDFS (Hadoop Distributed File System) or a local file system and returns it as an RDD (Resilient Distributed Dataset).
  8. sc.parallelize(): This command creates an RDD from a collection of data in the driver program.
  9. rdd.map(): This command applies a function to each element of an RDD and returns a new RDD.

These are just a few examples of Spark commands. There are many other commands and functions available for manipulating and processing data using Spark.

Checkout more interesting articles on Nixon Data on https://nixondata.com/knowledge/