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

Spark Connect is a new client-server architecture introduced in Spark 3.4 that decouples Spark client applications and allows remote connectivity to Spark clusters.

Hands-On Exercises Hands-on exercises from Spark Summit 2014. These let you install Spark on your laptop and learn basic concepts, Spark SQL, Spark Streaming, GraphX and MLlib. Hands-on …

Quick Start Interactive Analysis with the Spark Shell Basics More on Dataset Operations Caching Self-Contained Applications Where to Go from Here This tutorial provides a quick introduction to using …

Apache Spark ™ examples This page shows you how to use different Apache Spark APIs with simple examples. Spark is a great engine for small and large datasets. It can be used with single …

Spark Release 3.5.0 Apache Spark 3.5.0 is the sixth release in the 3.x series. With significant contributions from the open-source community, this release addressed over 1,300 Jira tickets. This …

Apache Spark leverages GitHub Actions that enables continuous integration and a wide range of automation. Apache Spark repository provides several GitHub Actions workflows for developers to …

Jan 2, 2026 · PySpark Overview # Date: Jan 02, 2026 Version: 4.1.1 Useful links: Live Notebook | GitHub | Issues | Examples | Community | Stack Overflow | Dev Mailing List | User Mailing List …

Spark SQL is Spark's module for working with structured data, either within Spark programs or through standard JDBC and ODBC connectors.

Spark SQL, DataFrames and Datasets Guide Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark …