When using the Scala API, it is necessary for applications to use the same version of Scala that Spark was compiled for.įor example, when using Scala 2.13, use Spark compiled for 2.13, and compile code/applications for Scala 2.13 as well.įor Java 11, setting =true is required for the Apache Arrow library. Java 8 prior to version 8u371 support is deprecated as of Spark 3.5.0. It’s easy to run locally on one machine - all you need is to have java installed on your system PATH, or the JAVA_HOME environment variable pointing to a Java installation. This should include JVMs on x86_64 and ARM64. Linux, Mac OS), and it should run on any platform that runs a supported version of Java. Spark runs on both Windows and UNIX-like systems (e.g. Scala and Java users can include Spark in their projects using its Maven coordinates and Python users can install Spark from PyPI. Users can also download a “Hadoop free” binary and run Spark with any Hadoop version Downloads are pre-packaged for a handful of popular Hadoop versions. Spark uses Hadoop’s client libraries for HDFS and YARN. This documentation is for Spark version 3.5.0. Get Spark from the downloads page of the project website.
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