Hadoop and HDFS Fundamentals on Cloudera

This course is primarily divided into two modules. The first module focuses on understanding Big Data and how Hadoop can be used as a storage as well as processing framework for Big Data. The second module explains Cloudera’s Hadoop distribution and practicals on the same. This entire course is helpful for any software developer who wants to learn Hadoop and totally new to the Big Data world.

The tutorials will help you learn about the meaning of big data, processing big data, distributed storage and processing, and understanding the basics of map reduction. In the next module wherein we practically apply we would learn the Cloudera environment, Understand the Hadoop environment installed on Cloudera, Understand metadata configuration on Hadoop, understand HDFS web UI and HUE, HDFS shell commands, and Access HDFS through Java program.

Hadoop software is a framework that allows you for the distributed processing of big data sets across clusters of computers using simple programming models. Hadoop was developed by the Apache software foundation under an open source platform in 2005. To handle such big data it uses the MapReduce concept. This MapReduce takes the input data and breaks it for further processing across various nodes within the Hadoop instance. These nodes are called worker nodes and they break the data for the next processing. The processed data is then collected back in reduce step and forwarded back to the original query. Hadoop looks through massive-scale data analysis. Hadoop is implemented on scale-out architecture which is a very low-cost physical server. It is used to distribute the processed data during map operations.

Course Objective:

• To study completely new technology which is a need of the hour
• To enhance your technical skills by learning new concepts of data storage as well as data processing

Target Customers (Who should go for this training):

• Students
• Professionals
• Anyone who wants to learn Big Data