Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.

If you’d like to build Spark from source, visit Building Spark. Spark runs on both Windows and UNIX-like systems (e.g. Linux, Mac OS), and it should run on any platform that runs a supported version of Java.

To follow along with this guide, first, download a packaged release of Spark from the Spark website. Since we won’t be using HDFS, you can download a package for any version of Hadoop.

Dec 11, 2025 · PySpark combines Python’s learnability and ease of use with the power of Apache Spark to enable processing and analysis of data at any size for everyone familiar with Python. PySpark …

Spark allows you to perform DataFrame operations with programmatic APIs, write SQL, perform streaming analyses, and do machine learning. Spark saves you from learning multiple frameworks …

Apache Spark™ Documentation Setup instructions, programming guides, and other documentation are available for each stable version of Spark below: Spark Spark 4.1.0

With Spark 3.4 and Spark Connect, the development of Spark Client Applications is simplified, and clear extension points and guidelines are provided on how to build Spark Server Libraries, making it easy …

Spark SQL supports three types of set operators: EXCEPT or MINUS INTERSECT UNION Note that input relations must have the same number of columns and compatible data types for the respective …

Types of time windows Spark supports three types of time windows: tumbling (fixed), sliding and session. Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time …

Spark now comes packaged with a self-contained Maven installation to ease building and deployment of Spark from source located under the build/ directory. This script will automatically download and …