Tag Archives: R

Analyzing US flight data on Amazon S3 with sparklyr and Apache Spark 2.0

Categories: CDH Data Science Hadoop Spark Use Case

We posted several blog posts about sparklyr (introduction, automation), which enables you to analyze big data leveraging Apache Spark seamlessly with R. sparklyr, developed by RStudio, is an R interface to Spark that allows users to use Spark as the backend for dplyr, which is the popular data manipulation package for R.

If you are interested in sparklyr, you can learn how to use it with the official document,

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Introducing sparklyr, an R Interface for Apache Spark

Categories: Data Science Guest Spark

Earlier this week, RStudio announced sparklyr, a new package that provides an interface between R and Apache Spark. We republish RStudio’s blog post below (see original) for your convenience.

sparklyr-illustration

Over the past couple of years we’ve heard time and time again that people want a native dplyr interface to Spark, so we built one! sparklyr also provides interfaces to Spark’s distributed machine learning algorithms and much more. 

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Feather: A Fast On-Disk Format for Data Frames for R and Python, powered by Apache Arrow

Categories: Data Science

This past January, we (Hadley and Wes) met and discussed some of the systems challenges facing the Python and R open source communities. In particular, we wanted to explore opportunities to collaborate on tools for improving interoperability between Python, R, and external compute and storage systems.

One thing that struck us was that, while R’s data frames and Python’s pandas data frames utilize different internal memory representations, the semantics of their user data types are mostly the same.

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How-to: Train Models in R and Python using Apache Spark MLlib and H2O

Categories: Data Science How-to Spark

Creating and training machine-learning models is more complex on distributed systems, but there are lots of frameworks for abstracting that complexity.

There are more options now than ever from proven open source projects for doing distributed analytics, with Python and R become increasingly popular. In this post, you’ll learn the options for setting up a simple read-eval-print (REPL) environment with Python and R within the Cloudera QuickStart VM using APIs for two of the most popular cluster computing frameworks: Apache Spark (with MLlib) and H2O (from the company with the same name).

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Common Probability Distributions: The Data Scientist’s Crib Sheet

Categories: Data Science

Data scientists have hundreds of probability distributions from which to choose. Where to start?

Data science, whatever it may be, remains a big deal.  “A data scientist is better at statistics than any software engineer,” you may overhear a pundit say, at your local tech get-togethers and hackathons. The applied mathematicians have their revenge, because statistics hasn’t been this talked-about since the roaring 20s. They have their own legitimizing Venn diagram of which people don’t make fun.

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