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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.
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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.
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Overview - Spark 4.1.1 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.
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Documentation | Apache Spark
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 for learning Spark.
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Quick Start - Spark 4.1.1 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.
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Examples - Apache Spark
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 frameworks and patching together various ...
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Spark SQL & DataFrames | Apache Spark
Spark SQL includes a cost-based optimizer, columnar storage and code generation to make queries fast. At the same time, it scales to thousands of nodes and multi hour queries using the Spark engine, which provides ful...
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PySpark Overview — PySpark 4.1.1 documentation - Apache Spark
Jan 2, 2026 · 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 Python. PySpark supports all of Spar...
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Spark Declarative Pipelines Programming Guide
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 focus on the transformations yo...
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Spark SQL and DataFrames - Spark 4.1.1 Documentation
Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computa...