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Difference between Spark MLlib/ML and H20

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Super Collaborator

Hi experts,

Just curious to know about the differences between Spark MLlib/ML and H2O in terms of implementation of algorithms, performance and usability and which one is better in what kinds of use-cases?

Thanks a lot in advance.

1 ACCEPTED SOLUTION

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Master Guru

You will have to run your algorithms on your cluster with your data to get a reasonable performance analysis.

What language are you looking at?

The Python Spark interface is pretty clean.

http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science.html

H2O has a few more algorithms than Spark MLib.

https://spark.apache.org/docs/latest/ml-classification-regression.html

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2 REPLIES 2

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Master Guru

You will have to run your algorithms on your cluster with your data to get a reasonable performance analysis.

What language are you looking at?

The Python Spark interface is pretty clean.

http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science.html

H2O has a few more algorithms than Spark MLib.

https://spark.apache.org/docs/latest/ml-classification-regression.html

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Super Collaborator

Thanks @Timothy Spann for your answer. These links are really helpful. I used python for Spark MLlib so will use the same for H2O as well.