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.

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 …

Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both …

Spark Declarative Pipelines (SDP) is a declarative framework for building reliable, maintainable, and testable data pipelines on Spark. SDP simplifies ETL development by allowing you to focus on the …

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, …

Structured Streaming Programming Guide As of Spark 4.0.0, the Structured Streaming Programming Guide has been broken apart into smaller, more readable pages. You can find these pages here.

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 …

Jan 11, 2026 · We’re proud to announce the release of Spark 0.7.0, a new major version of Spark that adds several key features, including a Python API for Spark and an alpha of Spark Streaming.

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 …