|
- Apache Spark™ - Unified Engine for large-scale data analytics
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters
- Overview - Spark 4. 0. 1 Documentation
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
- Downloads - Apache Spark
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 subject to different license terms
- Quick Start - Spark 4. 0. 1 Documentation
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
- PySpark Overview — PySpark 4. 0. 1 documentation - Apache Spark
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, allowing Spark to be used as a service
- SparkR (R on Spark) - Spark 4. 0. 1 Documentation
To use Arrow when executing these, users need to set the Spark configuration ‘spark sql execution arrow sparkr enabled’ to ‘true’ first This is disabled by default
- Structured Streaming Programming Guide - Spark 4. 0. 1 Documentation
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 batch computation on static data
- Spark Release 4. 0. 0 - Apache Spark
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
|
|
|