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

Running Spark Client Applications Anywhere with Spark Connect. Spark Connect is a new client-server architecture introduced in Spark 3.4 that decouples Spark client applications and allows …

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 …

Unlike the earlier examples with the Spark shell, which initializes its own SparkSession, we initialize a SparkSession as part of the program. To build the program, we also write a Maven …

Spark is a great engine for small and large datasets. It can be used with single-node/localhost environments, or distributed clusters. Spark’s expansive API, excellent performance, and …

Download Spark: Verify this release using the and project release KEYS by following these procedures. Note that Spark 4 is pre-built with Scala 2.13, and support for Scala 2.12 has …

May 19, 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. …

Seamlessly mix SQL queries with Spark programs. Spark SQL lets you query structured data inside Spark programs, using either SQL or a familiar DataFrame API. Usable in Java, Scala, …

We are happy to announce the availability of Spark 4.0.0! Visit the release notes to read about the new features, or download the release today. Spark News Archive

Spark revolves around the concept of a resilient distributed dataset (RDD), which is a fault-tolerant collection of elements that can be operated on in parallel.