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

Spark docker images are available from Dockerhub under the accounts of both The Apache Software Foundation and Official Images. Note that, these images contain non-ASF software …

Spark Connect is a client-server architecture within Apache Spark that enables remote connectivity to Spark clusters from any application. PySpark provides the client for the Spark …

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 …

You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Apache Cassandra, Apache HBase, Apache Hive, and …

Structured Streaming is a scalable and fault-tolerant stream processing engine built on the Spark SQL engine. You can express your streaming computation the same way you would express a …

Apache Spark 4.0.0 marks a significant milestone as the inaugural release in the 4.x series, embodying the collective effort of the vibrant open-source community.

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 …

Dependency changes While being a maintenance release we did still upgrade some dependencies in this release they are: [SPARK-50886]: Upgrade Avro to 1.11.4 You can …

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 …