Support for Scala 2.10 was removed as of 2.3.0. Note that support for Java 7, Python 2.6 and old Hadoop versions before 2.6.5 were removed as of Spark 2.2.0. You will need to use a compatible Scala version Spark runs on Java 8, Python 2.7+/3.4+ and R 3.1+. Or the JAVA_HOME environment variable pointing to a Java installation. Locally on one machine - all you need is to have java installed on your system PATH, Spark runs on both Windows and UNIX-like systems (e.g.
#INSTALL APACHE SPARK CENTOS 6 INSTALL#
Scala and Java users can include Spark in their projects using its Maven coordinates and in the future Python users can also 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 2.4.6. Get Spark from the downloads page of the project website.
Please see Spark Security before downloading and running Spark.
This could mean you are vulnerable to attack by default. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python and R,Īnd an optimized engine that supports general execution graphs. Apache Spark is a fast and general-purpose cluster computing system.
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