Applying MapReduce to Common Data Problems

Knowing how to program MapReduce is only half the battle. In this course, you'll learn how to set up the correct MapReduce based on what you want to accomplish.
Course info
Rating
(63)
Level
Beginner
Updated
Oct 26, 2016
Duration
2h 1m
Table of contents
Description
Course info
Rating
(63)
Level
Beginner
Updated
Oct 26, 2016
Duration
2h 1m
Description

This course, Applying MapReduce to Common Data Problems, helps you with three unique MapReduce patterns: summarizing numeric data, filtering large datasets, and building an index for fast data lookup. First, you'll learn about how you start "Thinking MapReduce" including what's involved and what needs to be broken down to start thinking in these terms. Next, you'll explore how to compute numeric summary metrics, and how to filter large data sets. Finally, you'll wrap up the course by learning about building indices, and why an inverted index is so important in the context of search engines. After watching this course, you'll have the confidence to spot patterns in MapReduce problems and will be on you're way to mastering this programming model.

About the author
About the author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.

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