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Introduction to Spark with sparklyr in R

中级技能水平
更新时间 2024年10月
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
免费开始课程
SparkData Engineering
4 小时
4 视频
50 练习
4,600 经验值
20,193
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课程描述

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. "

先决条件

Supervised Learning in R: Regression
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.
开始章节
2

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.
开始章节
Introduction to Spark with sparklyr in R
课程完成

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