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

It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, pandas API on Spark for pandas workloads, MLlib for machine learning, GraphX …

The documentation linked to above covers getting started with Spark, as well the built-in components MLlib, Spark Streaming, and GraphX. In addition, this page lists other resources …

Where to Go from Here This tutorial provides a quick introduction to using Spark. We will first introduce the API through Spark’s interactive shell (in Python or Scala), then show how to …

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 …

Spark allows you to perform DataFrame operations with programmatic APIs, write SQL, perform streaming analyses, and do machine learning. Spark saves you from learning multiple …

2025年2月23日 · 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 …

Integrated Seamlessly mix SQL queries with Spark programs. Spark SQL lets you query structured data inside Spark programs, using either SQL or a familiar DataFrame API. Usable …

This guide shows each of these features in each of Spark’s supported languages. It is easiest to follow along with if you launch Spark’s interactive shell – either bin/spark-shell for the Scala …

Getting Started ¶ This page summarizes the basic steps required to setup and get started with PySpark. There are more guides shared with other languages such as Quick Start in …