Applying MapReduce to Common Data Problems

Pluralsight
Course Summary
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 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.
-
+
Course Syllabus
Course Overview- 1m 31s
—Course Overview 1m 31sThinking MapReduce- 20m 2s
—Overview of MapReduce 5m 32s
—MapReduce Hello World 5m 1s
—More Parallelism with a Combiner 3m 39s
—Download Hadoop Jars and Set up an Intellij Project 5m 49sComputing Numeric Summary Metrics- 42m 38sFiltering Large Data Sets- 38m 15sBuilding Indexes- 19m 47s