Introduction to Spark with sparklyr in R
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Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
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. ”
What You’ll Learn
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.
Going Native: Use The Native Interface to Manipulate Spark DataFrames
In which you learn about Spark’s machine learning data transformation features, and functionality for manipulating native DataFrames.
Tools of the Trade: Advanced dplyr Usage
In which you learn more about using the dplyr interface to Spark, including advanced field selection, calculating groupwise statistics, and joining data frames.
Case Study: Learning to be a Machine: Running Machine Learning Models on Spark
A case study in which you learn to use sparklyr’s machine learning routines, by predicting the year in which a song was released.
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