Hadoop Basics Courses - Skillup Online

 

Is it true or not that you are interested in moving past the obvious issue at hand and understanding

Hadoop as a foundational toolset in your future? Then select this learning way to acquire openness to

the tools utilized in Big Data, Hadoop's center parts, and supporting open source projects.

About the Program

Hadoop is a name that addresses two things, one a kid's toy and the other an open-source structure for

appropriated capacity and handling of big data. In the two contexts, collaboration with Hadoop is foundational

in self-improvement and advancement. Hadoop Basics learning way covers content that is basic to your

progress in this domain. It takes you on an excursion that makes sense of the Hadoop calculated plan, then,

at that point, it looks at how to utilize the application and afterward control data without the utilization of

intricate coding.

This Learning Path empowers you with a small but comprehensive understanding of Hadoop.

First, you will take a step back and learn about the conceptual design behind the Hadoop framework.

You will then navigate through the application and finally manipulate data without the use of complex

coding.

Hadoop Basics - Course Outline

Course 1: Hadoop 101

Apache Hadoop is probably the best technology that clears the ground for analyzing big data. Get

familiar with what Hadoop is and its components, like MapReduce and HDFS. Come on this journey

to play with huge data sets and see Hadoop's strategy for distributed processing.

After completing this course you will be able to:

1. Use Hadoop architecture including MapReduce and HDFS.

2. Understand the Hadoop file system shell and the Ambari Console to work with HDFS.

3. Start and Stop Hadoop components.

4. Add/remove a node to/from a Hadoop cluster.

5. Modify Hadoop configuration parameters.

Course 2: MapReduce and YARN

String together your understanding of Yet Another Resource Negotiator (YARN) by acquiring openness

to MapReduce1, the tool-sets that start the handling of Big Data.

After completing this course, you will be able to:

1. Understand the MapReduce model

2. Create a YARN model

3. Understand MR2/YARN processing

4. Understand the high-level architecture of YARN

5. Configure, monitor, and run applications in the YARN environment.