Kevin Feasel


Hadoop, R, Spark

John Mount shows off replyr, which is dplyr for remote, distributed data setsĀ (think SparkR or sparklyr):

Suppose we had a large data set hosted on a Spark cluster that we wished to work with using dplyr and sparklyr (for this article we will simulate such using data loaded into Spark from the nycflights13 package).

We will work a trivial example: taking a quick peek at your data. The analyst should always be able to and willing to look at the data.

It is easy to look at the top of the data, or any specific set of rows of the data.

Read on for more details.

Related Posts

R In Linux For Windows

David Smith shows how to install and use R in the Windows Subsystem for Linux: R has been available for Windows since the very beginning, but if you have a Windows machine and want to use R within a Linux ecosystem, that’s easy to do with the new Fall Creator’s Update (version 1709). If you […]

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A Hack For Dynamic ML Services Result Sets

Dave Mason has put together a solution to his dynamic data frame naming problem: We can take those names and R types, string them together, and “convert” them to SQL data types. (Mapping data types from one language to another is waaaay outside the scope of this post. Lines 11-13 are quick and dirty, just […]

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March 2017
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