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From Mahesh Balija <>
Subject Mahout Vs Spark
Date Tue, 21 Oct 2014 22:04:16 GMT
Hi Team,

As Spark framework is gaining more attention in the Big Data - Open source
frameworks, with the support for variety of applications like,

1) Shark
2) GraphX
3) MLLib
4) Streaming

With the rapid development algorithms supporting Clustering,
Classification, Regression etc in the MLlib package and inbuilt support for
I am trying to differentiate between Mahout and Spark, here is the small

  Features Mahout Spark  Clustering Y Y  Classification Y Y
Regression Y Y  Dimensionality
Reduction Y Y  Java Y Y  Scala N Y  Python N Y  Numpy N Y  Hadoop Y Y  Text
Mining Y N  Scala/Spark Bindings Y N/A  scalability Y  Y
Apart from above, Mahout has vast coverage of Machine Learning algorithms
with many utilities and API's as opposed to Spark.
And Mahout 1.0 providing support for Scala, Spark bindings.

I was trying to demarcate between Mahout and Spark?
Can you throw some light on key differences and uniqueness of Mahout
framework. Am I missing any important distinction which makes Mahout the
only choice for Scalable machine learning.


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