$ ./bin/spark-shell scala>
Spark shell is an interactive shell to learn how to make the most out of Apache Spark. This is a Spark application writted in Scala to offer a command-line environment with auto-completion (under
TAB key) where you can run ad-hoc queries and get familiar with the features of Spark (that help you in developing your own standalone Spark applications). It is a very convenient tool to explore the many things available in Spark with immediate feedback. It is one of the many reasons why Spark is so helpful for tasks to process datasets of any size.
There are variants of Spark shell for different languages:
spark-shell for Scala and
pyspark for Python.
This document uses
You can start Spark shell using
scala> :type spark org.apache.spark.sql.SparkSession // Learn the current version of Spark in use scala> spark.version res0: String = 2.1.0-SNAPSHOT
scala> :imports 1) import spark.implicits._ (59 terms, 38 are implicit) 2) import spark.sql (1 terms)
When you execute
org.apache.spark.deploy.SparkSubmit --class org.apache.spark.repl.Main --name Spark shell spark-shell
You start Spark shell using
spark-shell script (available in
$ ./bin/spark-shell Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException Spark context Web UI available at http://10.47.71.138:4040 Spark context available as 'sc' (master = local[*], app id = local-1477858597347). Spark session available as 'spark'. Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 2.1.0-SNAPSHOT /_/ Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_112) Type in expressions to have them evaluated. Type :help for more information. scala>
Spark shell creates an instance of SparkSession under the name
spark for you (so you don’t have to know the details how to do it yourself on day 1).
scala> :type spark org.apache.spark.sql.SparkSession
Besides, there is also
sc value created which is an instance of SparkContext.
scala> :type sc org.apache.spark.SparkContext
To close Spark shell, you press
Ctrl+D or type in
:q (or any subset of
|Spark Property||Default Value||Description|