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.

The documentation linked to above covers getting started with Spark, as well the built-in components MLlib, Spark Streaming, and GraphX. In addition, this page lists other resources for learning Spark.

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.

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 …

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 SQL includes a cost-based optimizer, columnar storage and code generation to make queries fast. At the same time, it scales to thousands of nodes and multi hour queries using the Spark …

There are more guides shared with other languages such as Quick Start in Programming Guides at the Spark documentation. There are live notebooks where you can try PySpark out without any other step:

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 …

Check out the guide on migrating from Spark JVM to Spark Connect to learn more about how to write code that works with Spark Connect. Also, check out how to build Spark Connect custom extensions …

Spark Streaming is an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. Data can be ingested from many sources like Kafka, …