Apache Hadoop is 100% open source, and pioneered a fundamentally new way of storing and processing data. Instead of relying on expensive, proprietary hardware and different systems to store and process data, Hadoop enables distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that both store and process the data, and can scale without limits.
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. If first begins with describing what is Big Data and the need for Hadoop to be able to process that data in a timely manner. In-depth knowledge of core concepts will be covered in the course along with implementation on varied industry use-cases.
This course helps developers become more comfortable with, and proficient at solving problems in, the Hadoop space. Learners will become more familiar with a wide variety of Hadoop-related tools and best practices for implementation.
This course will teach how to build solutions using tools such as Apache Hive, Pig, MapReduce, HDFS, and Apache HBase.
We provide in-depth explanations and code examples. Each module contains a set of recipes that pose, and then solve, technical challenges and that can be completed in any order. A recipe breaks a single problem down into discrete steps that are easy to follow. This covers unloading/loading to and from HDFS, batch data analysis using Hive, Pig, and MapReduce, real-time processing from HBase, debugging and troubleshooting MapReduce jobs, and columnar storage and retrieval of structured data using Apache HBase. We give examples learners need to apply the Hadoop technology to their own problems.