Hadoop – Big Data Development & Analytics – V2
!! Apache Community Delivers Big Data Solution to Advance Enterprise Analytics !!
The data revolution is upon us and Hadoop is THE leading Big Data platform. Fortune 500 companies are using it for storing and analyzing extremely large datasets, while other companies are realizing its potential and preparing their budgets for future Big Data positions. It’s the elephant in Big Data’s room!
Hey !! Can you Believe you can built your OWN Super Computer
First Class Room and Real Training Program of Big Data Hadoop version 2 in India
First Time in India – Built MapReduce Jobs in Python Language
This series will get you up to speed on Big Data and Hadoop. Topics include how to install, configure and manage a single and multi-node Hadoop cluster, configure and manage HDFS, write MapReduce jobs and work with many of the projects around Hadoop such as Pig, Hive, HBase, Sqoop, and Zookeeper. Topics also include configuring Hadoop in the cloud and troubleshooting a multi-node Hadoop cluster.
The Apache Hadoop software is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Hadoop is a software framework for storing and processing Big Data. It is an open-source tool build on java platform and focuses on improved performance in terms of data processing on clusters of commodity hardware.
- Hadoop comprises of multiple concepts and modules like HDFS, Map-Reduce, HBASE, PIG, HIVE, SQOOP and ZOOKEEPER to perform the easy and fast processing of huge data
- Hadoop conceptually different from Relational databases and can process the high volume, high velocity and high variety of data to generate value
After the completion of the Big Data and Hadoop Course, you should be able to:
- Master the concepts of Hadoop Distributed File System and MapReduce framework
- Setup a Hadoop Cluster
- Understand Data Loading Techniques using Sqoop and Flume
- Program in MapReduce (Both MRv1 and MRv2)
- Learn to write Complex MapReduce programs
- Program in YARN (MRv2)
- Perform Data Analytics using Pig and Hive
- Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing
- Have a good understanding of ZooKeeper service
- New features in Hadoop 2.0 — YARN, HDFS Federation, NameNode High Availability
- Implement best Practices for Hadoop Development and Debugging
- Implement a Hadoop Project
- Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience
Hiring IT professionals who are certified as Hadoop BigData allows many organizations to increase their ratio of servers to administrators, enabling them to be more cost effective in building out their infrastructures without needing to bring on additional resources.
– Why Hadoop, Scaling, Distributed Framework, Hadoop v/s RDBMS, Brief history of Hadoop, Problems with traditional large-scale systems, Requirements for a new approach, Anatomy of a Hadoop cluster, Other Hadoop Ecosystem components
Hadoop Cluster Configuration and Data Loading
Hadoop MapReduce framework
Pig and Pig Latin
Hive and HiveQL
Advance Hive, NoSQL Databases and HBase
Advance HBase and ZooKeeper
Hadoop 2.0, MRv2 and YARN