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 and may be …

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 Connect server, …

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.

DataFrame and Spark SQL share the same execution engine so they can be interchangeably used seamlessly. For example, you can register the DataFrame as a table and run a SQL easily as below:

Spark 3.5.5 released We are happy to announce the availability of Spark 3.5.5! Visit the release notes to read about the new features, or download the release today. Spark News Archive

Spark provides three locations to configure the system: Spark properties control most application parameters and can be set by using a SparkConf object, or through Java system properties. …

Apache Spark’s ability to choose the best execution plan among many possible options is determined in part by its estimates of how many rows will be output by every node in the execution plan (read, filter, …

Types of time windows Spark supports three types of time windows: tumbling (fixed), sliding and session. Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time …

You will express your streaming computation as standard batch-like query as on a static table, and Spark runs it as an incremental query on the unbounded input table.