Apache Spark Review

It makes web-based queries for plotting data easier. It needs to be simpler to use the machine learning algorithms supported by Octave.

Valuable Features

  • RDDs
  • DataFrames
  • Machine learning libraries

Improvements to My Organization

Faster time to parse and compute data. It makes web-based queries for plotting data easier.

Room for Improvement

It needs to be simpler to use the machine learning algorithms supported by Octave (example polynomial regressions, polynomial interpolation).

Use of Solution

I've been using it for one year.

Deployment Issues

There have been no issues with the deployment.

Stability Issues

There have been no issues with the stability.

Scalability Issues

There have been no issues with the scalability.

Customer Service and Technical Support

We still rely on user forums for my answers. We do not use a commercial product yet.

Initial Setup

The initial set-up was easy. I have not explored using this on AWS clusters.

Implementation Team

We did an in-house implementation and development for our regression tool.

ROI

The ROI will be an in-house product to do machine learning analytics on data obtained from customer.

Other Solutions Considered

We did not evaluate any other products.

Other Advice

It's easy to use and has a learning curve.

Which version of this solution are you currently using?

SPARC 1.0
**Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Highlights
I found the solution stable. We haven't had any problems with it.
The scalability has been the most valuable aspect of the solution.
The most valuable feature of this solution is its capacity for processing large amounts of data.
The solution is very stable.
I feel the streaming is its best feature.
The features we find most valuable are the machine learning, data learning, and Spark Analytics.
The main feature that we find valuable is that it is very fast.
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