Project Summary
Apache Spark is an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write.
To run programs faster, Spark provides primitives for in-memory cluster computing: your job can load data into memory and query it repeatedly more rapidly than with disk-based systems like Hadoop.
To make programming faster, Spark offers high-level APIs in Scala, Java and Python, letting you manipulate distributed datasets like local collections. You can also use Spark interactively to query big data from the Scala or Python shells.
Spark integrates closely with Hadoop to run inside Hadoop clusters and can access any existing Hadoop data source.
In a Nutshell, Apache Spark...
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has a well established, mature codebase
maintained by a very large development team
with stable Y-O-Y commits -
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took an estimated 441 years of effort (COCOMO model)
starting with its first commit in March, 2010
ending with its most recent commit 1 day ago
Quick Reference
Apache License 2.0
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Use Patent Claims
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Required
Include Copyright
State Changes
Include License
Include Notice
These details are provided for information only. No information here is legal advice and should not be used as such.
Project Security
Vulnerabilities per Version ( last 10 releases )
There are no reported vulnerabilities
Project Vulnerability Report
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Vulnerability Exposure Index
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30 Day SummaryAug 31 2025 — Sep 30 2025
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12 Month SummarySep 30 2024 — Sep 30 2025
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