It is a prediction by the IT sectors that in the coming three to five years, around half of the data of the world will have to be processed on Hadoop. The demand for Hadoop experts is hence going to multiply into thousands and more.
adoop online training, thus, will introduce you to a big market of opportunities where your success and growth will be unlimited. The projection indeed point out irrespective of whether a particular enterprise is in need of a Big Data strategy or not, the requirement for Hadoop experts is to escalate in coming few years.
Through Hadoop online training, you can get Hadoop certification, which has been in huge demand in all types of industries including vertical services such as utilities, retail, financial services, pharmaceuticals and energy. There is a competition among the corporate to hire the best Hadoop professionals, which clearly demonstrate the hike in the demand for this field.
Hadoop online Training Course Content
Introduction to Big Data and Analytics
Introduction to Hadoop
Hadoop ecosystem – Concepts
Hadoop Map-reduce concepts and features
Developing the map-reduce Applications
Oozie workflow concepts
Real Life Use Cases
1. Virtualbox/VM Ware
Hadoop v/s RDBMS
Brief history of hadoop
4. Setup hadoop
Installation of java, hadoop
Configurations of hadoop
Hadoop Processes ( NN, SNN, JT, DN, TT)
Common errors when running hadoop cluster, solutions
5. HDFS- Hadoop distributed File System
HDFS Design and Architecture
Interacting HDFS using command line
Interacting HDFS using Java APIs
6. Hadoop Processes
Secondary name node
7. Map Reduce
Developing Map Reduce Application
Phases in Map Reduce Framework
Map Reduce Input and Output Formats
8. Joining datasets in Mapreduce jobs
9. Map reduce customization
Custom Input format class
Custom Output format class
10. Hadoop Programming Languages :-
Installation and Configuration
Interacting HDFS using HIVE
Map Reduce Programs through HIVE
Loading, Filtering, Grouping
Data types, Operators
Sample programs in HIVE
Installation and Configurations
OVERVIEW HADOOP DEVELOPER
12. The Motivation for Hadoop
Problems with traditional large-scale systems
Requirements for a new approach
13. Hadoop: Basic Concepts
An Overview of Hadoop
The Hadoop Distributed File System
How MapReduce Works
Anatomy of a Hadoop Cluster
Other Hadoop Ecosystem Components
14. Writing a MapReduce Program
The MapReduce Flow
Examining a Sample MapReduce Program
Basic MapReduce API Concepts
The Driver Code
Hadoop’s Streaming API
Using Eclipse for Rapid Development
The New MapReduce API
15. Common MapReduce Algorithms
Sorting and Searching
Machine Learning With Mahout
Term Frequency Inverse Document Frequency
Data loading in PIG.
Data Extraction in PIG.
Data Transformation in PIG.
Hands on exercise on PIG.
17. Hive Concepts.
Hive Query Language.
Alter and Delete in Hive.
Partition in Hive.
Joins in Hive.Unions in hive.
Industry specific configuration of hive parameters.
Authentication & Authorization.
Statistics with Hive.
Archiving in Hive.
18. Working with Sqoop
19. Working with Flume
Configuration and Setup.
Flume Sink with example.
Flume Source with example.
Complex flume architecture.
20. OOZIE Concepts
21. IMPALA Concepts
22. HUE Concepts
23. HBASE Concepts
24. ZooKeeper concepts
What is visual analysis?
Strengths/weakness of the visual system.
Laying the Groundwork for Visual Analysis
Preparing for analysis
Getting, Cleaning and Classifying Your Data
Cleaning, formatting and reshaping.
Using additional data to support your analysis.
Visual Mapping Techniques
Visual Variables : Basic Units of Data Visualization
Working with Color
Marks in action: Common chart types
Solving Real-World Problems with Visual Analysis
Getting a Feel for the Data- Exploratory Analysis.
Looking at (co-)Relationships.
Try, try again.
Communicating Your Findings
Fine-tuning for more effective visualization
Storytelling and guided analytics