Apache Spark 1.2.1

A cluster computing system for fast data analysis

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What's new in Apache Spark 1.2.0:

  • PySpark’s sort operator now supports external spilling for large datasets.
  • PySpark now supports broadcast variables larger than 2GB and performs external spilling during sorts.
  • Spark adds a job-level progress page in the Spark UI, a stable API for progress reporting, and dynamic updating of output metrics as jobs complete.
  • Spark now has support for reading binary files for images and other binary formats.
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LICENSE TYPE:

BSD License

USER RATING:
UNRATED
  0.0/5
DEVELOPED BY:
UC Berkeley AMP Lab
HOMEPAGE:
spark-project.org
LANGUAGE:
Java
CATEGORY:
C: \ Server Management
Spark was designed to improve processing speeds for data analysis and manipulation programs.

It was written in Java and Scala and provides features not found in other systems, mostly because they're not mainstream nor that useful for non-data processing applications.

Last updated on February 10th, 2015

Runs on: Windows / Linux / Mac OS / BSD / Solaris

feature list

#data processing #cluster computing #Scala framework #cluster #computing #analysis #in-memory

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