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

Apache Spark started as a research project at UC Berkeley in the AMPLab, which focuses on big data analytics. Our goal was to design a programming model that supports a much wider class …

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 …

Spark Structured Streaming uses the same underlying architecture as Spark so that you can take advantage of all the performance and cost optimizations built into the Spark engine.

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

Nov 19, 2025 · 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 …

Apache Spark started as a research project at the UC Berkeley AMPLab in 2009, and was open sourced in early 2010. Many of the ideas behind the system were presented in various …

We use Spark to regularly read raw data, convert them into Parquet, and process them to create advanced analytics dashboards: aggregation, sampling, statistics computations, anomaly …

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 …

Spark supports two types of shared variables: broadcast variables, which can be used to cache a value in memory on all nodes, and accumulators, which are variables that are only “added” to, …