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

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 supported version of Java.

As new Spark releases come out for each development stream, previous ones will be archived, but they are still available at Spark release archives. NOTE: Previous releases of Spark may be affected by …

To follow along with this guide, first, download a packaged release of Spark from the Spark website. Since we won’t be using HDFS, you can download a package for any version of Hadoop.

Dec 11, 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. PySpark …

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 …

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.

Starting Up: SparkSession The entry point into SparkR is the SparkSession which connects your R program to a Spark cluster. You can create a SparkSession using sparkR.session and pass in …

ALTER TABLE Description ALTER TABLE statement changes the schema or properties of a table. RENAME ALTER TABLE RENAME TO statement changes the table name of an existing table in the …

The Spark SQL engine will take care of running it incrementally and continuously and updating the final result as streaming data continues to arrive. You can use the Dataset/DataFrame API in Scala, Java, …