How to use two versions of spark shell?
I have Spark 1.6.2 and Spark 2.0 installed on my hortonworks cluster.
Both these versions are installed on a node in the Hadoop Cluster of 5 nodes.
Each time I start the
spark-shell I get:
$ spark-shell Multiple versions of Spark are installed but SPARK_MAJOR_VERSION is not set Spark1 will be picked by default
When I check the version I get:
scala> sc.version res0: String = 1.6.2
How can I start the other version(spark-shell of Spark2.0)?
You just need to give the major version 2 or 1.
$ export SPARK_MAJOR_VERSION=2 $ spark-submit --version SPARK_MAJOR_VERSION is set to 2, using Spark2 Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 126.96.36.199.5.0.0-1245
Solved: how to choose which version of spark be used in HD , Solved: There are two versions of Spark in HDP 2.5, Spark 1.6 and Spark 2.0. I don't Here is an example for a user who submits jobs using spark-submit under For supporting multiple versions of Spark you need to install it manually on a single node and copy the config files for YARN and Hive inside its conf directory. And when you refer the spark-submit of that version, it will distribute the Spark-core binary on each YARN nodes to execute your code. You don't need to install Spark on each YARN nodes.
Working this approach:
loads Spark 1.6
loads Spark 2.0
How to use multiple spark version?, I want to install Spark 1 and 2 without uninstalling either and use them depending on my need. How can I do this? 1. To check if the Spark is installed and to know its version, below command, is used (All commands hereafter shall be indicated starting with this symbol “$”) $ spark-shell. The following output is displayed if the spark is installed: $ spark-shell. SPARK_MAJOR_VERSION is set to 2, using Spark2. Setting the default log level to “WARN”.
$ SPARK_MAJOR_VERSION=2 spark-shell
Multiple versions of Spark but can't set to Spark 2 - scala - html, However, I would like to begin exploring the use of Spark with Scala through a When running: spark-submit --version I got a message saying Multiple versions ./bin/spark-shell --master local The --master option specifies the master URL for a distributed cluster, or local to run locally with one thread, or local[N] to run locally with N threads. You should start by using local for testing. For a full list of options, run Spark shell with the --help option. Spark also provides a Python API.
use spark2-submit, pyspark2 or spark2-shell
How to select SPARK2 as default spark version – SQL & Hadoop, How to select SPARK2 as default spark version. Hi Guys. Run below command before calling spark-shell export SPARK_MAJOR_VERSION=2. Now call Since we won’t be using HDFS, you can download a package for any version of Hadoop. Note that, before Spark 2.0, the main programming interface of Spark was the Resilient Distributed Dataset (RDD). After Spark 2.0, RDDs are replaced by Dataset, which is strongly-typed like an RDD, but with richer optimizations under the hood.
Overview - Spark 2.2.0 Documentation, Downloads are pre-packaged for a handful of popular Hadoop versions. Users can also download a You will need to use a compatible Scala version (2.11.x). Note that support for Java bin/spark-shell --master local. The --master option I have Spark 1.6.2 and Spark 2.0 installed on my hortonworks cluster. Both these versions are installed on a node in the Hadoop Cluster of 5 nodes. Each time I start the spark-shell I get: $ spark-shell Multiple versions of Spark are installed but SPARK_MAJOR_VERSION is not set Spark1 will be picked by default When I check the version I get:
Overview - Spark 2.3.3 Documentation, This documentation is for Spark version 2.3.3. Spark You will need to use a compatible Scala version (2.11.x). Note that bin/spark-shell --master local. 2. Scala – Spark Shell Commands. Start the Spark Shell. Apache Spark is shipped with an interactive shell/scala prompt, as the spark is developed in Scala.Using the interactive shell we will run different commands (RDD transformation/action) to process the data.
Quickstart, You can run the steps in this guide on your local machine in the following two ways: To use Delta Lake interactively within the Spark's Scala/Python shell, you need a Download the latest version of Apache Spark (3.0 or above) by following The simplest way to run a Spark application is by using the Scala or Python shells. Important: By default, CDH is configured to permit any user to access the Hive Metastore.