Here are some important Apache Spark commands that you may find useful:
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.spark-shell
: This command starts the Spark shell, which is an interactive shell for running Spark commands.spark-sql
: This command starts the Spark SQL CLI (command-line interface), which allows you to run SQL queries against data stored in Spark.spark-submit --master yarn
: This command submits a Spark application to run on a YARN cluster.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.spark.stop()
: This command stops the SparkContext, which is used to stop a Spark application.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).sc.parallelize()
: This command creates an RDD from a collection of data in the driver program.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.
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