RHadoop updated: improved performance and more control

[This article was first published on Revolutions, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Revolution Analytics' open-source RHadoop project, which provides integration between R and Hadoop, has been updated with the release of version 1.2 of the “rmr” package. New in this version: support for binary I/O formats, which improves on the text-only interfact by allowing use of faster and more space-efficient data formats like R's native serialization format. This version also improves the performance of the reduce step (to get around the fact that list appends in R are not constant-time operations), and provides control to the Hadoop user to do things like set number of reducers on a per-job basis.

Find more details about these and other updates in rmr 1.2 (available now) at the link below.

RHadoop: Overview of rmr v1.2

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)