Welcome to the documentation for the DC/OS Apache Spark. For more information about new and changed features, see the release notes.

Apache Spark is a fast and general-purpose cluster computing system for big data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including the following:

• Spark SQL for SQL and DataFrames
• MLlib for machine learning
• GraphX for graph processing
• Spark Streaming for stream processing.

For more information, see the Apache Spark documentation.

DC/OS Apache Spark consists of Apache Spark with a few custom commits along with DC/OS-specific packaging.

DC/OS Apache Spark includes:

• Mesos Cluster Dispatcher
• Spark History Server
• DC/OS Apache Spark CLI
• Interactive Spark shell

Benefits

• Utilization: DC/OS Apache Spark leverages Mesos to run Spark on the same cluster as other DC/OS services
• Improved efficiency
• Simple management
• Multi-team support
• Interactive analytics through notebooks
• UI integration
• Security, including file- and environment-based secrets

Features

• Multiversion support
• Run multiple Spark dispatchers
• Run against multiple HDFS clusters
• Backports of scheduling improvements
• Simple installation of all Spark components, including the dispatcher and the history server
• Integration of the dispatcher and history server
• Zeppelin integration
• Kerberos and SSL support

Related services

• HDFS
• Kafka
• Zeppelin