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

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 …

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

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 …

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 …

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 …

In this model, Spark is responsible for updating the Result Table when there is new data, thus relieving the users from reasoning about it. As an example, let’s see how this model handles …

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 …

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 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. …