Big Data and Hadoop Certification Training
Apache Hadoop is a new technology that allows large data volumes to be organized and processed while keeping the data on the original data storage cluster. It is an open source project for processing large datasets in parallel with the use of low level commodity machines. Hadoop is built on two main parts; a special file system called Hadoop Distributed File System (HDFS) and the MapReduce Framework.
- Research firm IDC is predicting a Hadoop market that will grow revenue at 31.7 percent a year until it hits the $23.8 billion mark in 2016.
- According to a research by MarketsandMarkets, the worldwide Hadoop & Big Data Analytics market is expected to grow to about $13.9 billion by 2017.
- An IDC forecast shows that the Big Data technology and services market will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017
The HDFS File System is an optimized file system for distributed processing of very large datasets on commodity hardware. The map reduces framework works in two main phases to process the data which are the Map phase and the Reduce phase. This course is ideal for managers, analysts, architects and developers seeking an understanding of Hadoop concepts, MapReduce, HDFS and Hive for processing large data workloads.
Objectives of the Course
In this program, Instructor will explain and illustrate the capabilities of Hadoop (including MapReduce, Yarn and HDS), Hive, HBase and Spark for processing large volume of data workloads with various industry use cases.
Course topics include – Understanding of Hadoop concepts and evolution, characteristics and significance of Hadoop, Hadoop Distributed File Systems (HDFS), Hadoop Map/Reduce and Hadoop projects reference. Homework will be assigned to help students to review and apply the concepts to problem-solving in the real world.
Who Should Attend this Course
This course is designed for individuals seeking to gain expertise in the concepts, tools and the platform of Hadoop needed for processing large data sets. Further, this course is designed to meet the need to fulfil professional development training requirements on Hadoop to process large data sets
Objectives of the Course
- Learn Hadoop concepts and evolution
- Recognize Basic Hadoop MapReduce Features
- Understand and Utilize Hadoop MapReduce types and formats
- Understand how MapReduce and Yarn work?
- Know the basics of Hadoop Distributed File Systems (HDFS)
- Identify HDFS I/O operations
- Acquire the basics of Hive
- Acquire the basics of HBase
- Acquire the basics of Pig
- Acquire the basics of Sqoop
- Acquire the basics of Scala
- Acquire the basics of Spark
|Hadoop Concepts and Evolution|
|Basic Hadoop MapReduce Features|
|Hadoop MapReduce Types and Formats|
|How MapReduce Works?|
|Basic understandings of Hadoop Distributed File Systems (HDFS)|
|Hadoop I/O operations|
|Setting up a Hadoop Cluster|
|Administering Hadoop Environment|
|Introduction to Hive|
|Basics of Hbase|
|Basics of Pig|
|Basics of Sqoop|
|Basics of Scala|
|Basics of Spark|
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