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Big Data Hadoop Development Training

Hadoop Big Data Training course helps you learn the core techniques and concepts of Big Data and Hadoop ecosystem. It equips you with in-depth knowledge of writing codes using MapReduce framework and managing large data sets with HBase. The topics covered in this course mainly includes- Hive, Pig and setup of Hadoop Cluster.

After the completion of the Big Data and Hadoop Course at UGS, 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

Pre-requisites:

You should have knowledge of programming in C++ or Java or any other Object Oriented Programming language

Hadoop Development Course

Understanding Big Data

• Introductions and course logistics
• Course objectives

Introduction to VMware Virtualization

• Big Data Characteristics
• Velocity, Volume & Variety
• Structured and Unstructured Data
• How do Big Data add value to traditional applications?
• How Big Data complements BI systems and DW processes
• Present day scenario about BI/Analytics
• How Analytics add value to Big Data?
• Application and use cases of Big Data
• Industry examples and Common use cases

MapReduce Framework

• Programming paradigms
• Functional programming Vs. Others
• MapReduce overview
• Pros & Cons of MapReduce
• Running MapReduce Jobs
• Basic MapReduce Programs
• MapReduce Data Flow
• Anatomy of a MapReduce Job
• Legacy MR & MR v2 (YARN)
• Combiners, Partitioners, Counters
• Input & Output file formats

Apache Pig

• Installation & Configuration
• Running PigScripts
• Understanding Execution Flow

Apache Hive

• Installation & Configuration
• Running Hive
• Understanding Execution Flow in Hive
• Differences between Hive and Pig

Course Deliverables

• Hadoop Installed VM
• Course Material includes
• Graphically Rich Presentations
• Cheat sheets
• Reference Cards
• Supplementary Material
• Lecture Notes
• Code and Data Sets