BIG DATA HADOOP Online Training:-
We at Rizetrainings expertise providing online hadoop training. Our faculties and study material teaches the simplified way to learn hadoop onlineWe are one step training provider but not limited to Bigdata hadoop online training. Our services are globalized specially for a developed countries like USA. We expertise in providing hadoop online training in USA.
*Course Details:
Course Objective Summary
During this course, you will learn:
Introduction to Big Data and Analytics
Introduction to Hadoop
Hadoop ecosystem - Concepts
Hadoop Map-reduce concepts and features
Developing the map-reduce Applications
Pig concepts
Hive concepts
Sqoop concepts
Flume Concepts
Oozie workflow concepts
Impala Concepts
Hue Concepts
HBASE Concepts
ZooKeeper Concepts
Real Life Use Cases
Reporting Tool
*Tableau
*1. Virtualbox/VM Ware
Basics
Installations
Backups
Snapshots
*2. Linux
Basics
Installations
Commands
*3. Hadoop
Why Hadoop?
Scaling
Distributed Framework
Hadoop v/s RDBMS
Brief history of hadoop
*4. Setup hadoop
Pseudo mode
Cluster mode
Ipv6
Ssh
Installation of java, hadoop
Configurations of hadoop
Hadoop Processes ( NN, SNN, JT, DN, TT)
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Temporary directory
Common errors when running hadoop cluster, solutions
*5. HDFS- Hadoop distributed File System
HDFS Design and Architecture
HDFS Concepts
Interacting HDFS using command line
Interacting HDFS using Java APIs
Dataflow
Blocks
Replica
*6. Hadoop Processes
Name node
Secondary name node
Job tracker
Task tracker
Data node
*7. Map Reduce
Developing Map Reduce Application
Phases in Map Reduce Framework
Map Reduce Input and Output Formats
Advanced Concepts
Sample Applications
Combiner
*8. Joining datasets in Mapreduce jobs
Map-side join
Reduce-Side join
*9. Map reduce – customization
Custom Input format class
Hash Partitioner
Custom Partitioner
Sorting techniques
Custom Output format class
*10. Hadoop Programming Languages :-
*I.HIVE
Introduction
Installation and Configuration
Interacting HDFS using HIVE
Map Reduce Programs through HIVE
HIVE Commands
Loading, Filtering, Grouping….
Data types, Operators…..
Joins, Groups….
Sample programs in HIVE
*II. PIG
Basics
Installation and Configurations
Commands….
OVERVIEW HADOOP DEVELOPER
*11. Introduction
*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
Hands-On Exercise
How MapReduce Works
Hands-On Exercise
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
The Mapper
The Reducer
Hadoop’s Streaming API
Using Eclipse for Rapid Development
Hands-on exercise
The New MapReduce API
*15. Common MapReduce Algorithms
Sorting and Searching
Indexing
Machine Learning With Mahout
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Term Frequency – Inverse Document Frequency
Word Co-Occurrence
Hands-On Exercise.
*16.PIG Concepts..
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.
Indexing.
Joins in Hive.Unions in hive.
Industry specific configuration of hive parameters.
Authentication & Authorization.
Statistics with Hive.
Archiving in Hive.
Hands-on exercise
*18. Working with Sqoop
Introduction.
Import Data.
Export Data.
Sqoop Syntaxs.
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Databases connection.
Hands-on exercise
*19. Working with Flume
Introduction.
Configuration and Setup.
Flume Sink with example.
Channel.
Flume Source with example.
Complex flume architecture.
*20. OOZIE Concepts
*21. IMPALA Concepts
*22. HUE Concepts
*23. HBASE Concepts
*24. ZooKeeper concepts
Reporting Tool..
Tableau
This course is designed for the beginner to intermediate-level Tableau user. It is for anyone who works with data – regardless of technical or analytical background. This course is designed to help you understand the important concepts and techniques used in Tableau to move from simple to complex visualizations and learn how to combine them in interactive dashboards.
*Course Topics
*Overview
*What is visual analysis?
strengths/weakness of the visual system.
Laying the Groundwork for Visual Analysis
*Analytical Process
Preparing for analysis
Getting, Cleaning and Classifying Your Data
*Cleaning, formatting and reshaping.
Using additional data to support your analysis.
Data classification
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.
Making comparisons
Looking at (co-)Relationships.
Checking progress.
Spatial Relationships.
Try, try again.
Communicating Your Findings
*Fine-tuning for more effective visualization
Storytelling and guided analytics
Dashboards
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