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Alec Stashevsky has completed

Introduction to Spark with sparklyr in R

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4 hours
4,600 XP
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Course Description

Explore the Advantages of R, Spark, and sparklyr

R is mostly optimized to help you write data analysis code quickly and readably. Apache Spark is designed to analyze huge datasets quickly. The sparklyr package lets you write dplyr R code that runs on a Spark cluster, giving you the best of both worlds. This 4-hour course teaches you how to manipulate Spark DataFrames using both the dplyr interface and the native interface to Spark, as well as trying machine learning techniques.

Load Data into Spark and Manipulate Spark DataFrames

You’ll start this Spark course by investigating how Spark and R work well together and practicing loading data, ready for cleaning, transformation, and analysis. You’ll use Spark frames and dplyr syntax to manipulate your data by filtering and arranging rows, and mutating and summarizing columns.

Delve into Big Data Analysis with Spark MLib

This course focuses on building your skills and confidence in analyzing huge datasets. The final chapters take you through Spark’s machine learning data transformation features and offer you the chance to practice sparklyr’s machine learning routines by using it to make predictions using gradient boosted trees and random forests. "
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  1. 1

    Light My Fire: Starting To Use Spark With dplyr Syntax


    In which you learn how Spark and R complement each other, how to get data to and from Spark, and how to manipulate Spark data frames using dplyr syntax.

    Play Chapter Now
    Getting started
    50 xp
    Made for each other
    50 xp
    Here be dragons
    50 xp
    The connect-work-disconnect pattern
    100 xp
    Copying data into Spark
    100 xp
    Big data, tiny tibble
    100 xp
    Exploring the structure of tibbles
    100 xp
    Selecting columns
    100 xp
    Filtering rows
    100 xp
    Arranging rows
    100 xp
    Mutating columns
    100 xp
    Summarizing columns
    100 xp
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Collaborator's avatar
Tom Jeon


Intermediate R
Richie Cotton HeadshotRichie Cotton

Data Evangelist at DataCamp

Richie is a Data Evangelist at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.
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