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 increasing Y-O-Y commits -
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took an estimated 561 years of effort (COCOMO model)
starting with its first commit in March, 2010
ending with its most recent commit 2 days ago
Quick Reference
Apache License 2.0
Permitted
Commercial Use
Modify
Distribute
Place Warranty
Sub-License
Private Use
Use Patent Claims
Forbidden
Hold Liable
Use Trademarks
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
Security Confidence Index
Vulnerability Exposure Index
Did You Know...
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use of OSS increased in 65% of companies in 2016
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by exploring contributors within projects, you can view details on every commit they have made to that project
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nearly 1 in 3 companies have no process for identifying, tracking, or remediating known open source vulnerabilities
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