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 …

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. …

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 …

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 …

Spark Declarative Pipelines (SDP) is a declarative framework for building reliable, maintainable, and testable data pipelines on Spark. SDP simplifies ETL development by allowing you to …

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 …

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 …

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

PySpark is included in the official releases of Spark available in the Apache Spark website. For Python users, PySpark also provides pip installation from PyPI.