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What is Hadoop?

Hadoop is an open source framework that processes large data sets (Big Data), in a distributed storage environment. This platform can process/handle large volume of data (Big Data) in a small amount of time. APIs for MapReduce applications enables us to read, write and compute data in parallel.

Hadoop Distributed File System (HDFS) was made to store the huge amount (hundreds of gigabytes) of data every second. This stored data is used to generate various analytics. Traditional databases cannot handle data of this size. The MapReduce helps to run different kinds of computation on this huge volume of data with ease.

Hadoop Developers Training Details

Before you start your training, See what you will learn in our BIG DATA and HADOOP Developers training course

1. Introduction to BIG DATA and HADOOP

What are BIG DATA features and challenges
Problems with Traditional Large-Scale Systems
Horizontal and vertical scaling
Why Hadoop Comparison with RDBMS
A brief history and Limitation of Hadoop
Available version

2. HADOOP ECOSYSTEM & CLUSTER

Available Distributions of Hadoop (Apache, Cloudera, Hortonworks, etc)
Hadoop Architecture & Planning for cluster
Cluster Daemons & Its Functions :
a. Name Node
b. Secondary Node
c. Data Nodes
d. Job Tracker
e. Task Trackers
Hadoop Ecosystem components and uses

3. HDFS CONCEPTS

HDFS Design & Goals
Understand Blocks and Configuration of block size
Block replication, replication factor and failure handling
Understand Rack Awareness and Configuring racks in Hadoop
File read and write anatomy in HDFS

4. YARN - YET ANOTHER RESOURCE NEGOTIATOR

YARN Architecture
Components of YARN
* Resource Manager * Node Manager * Job History Server * MR Application Master YARN Application execution flow
Running and Monitoring YARN Applications
Understand and Configure Capacity / Fair Schedulers in YARN

5. HADOOP INSTALLATION & DEPLOYMENT

Setting up Apache / Cloudera environment
Specifying the Configuration
Performing Initial HDFS Configuration
Performing Initial YARN and Map-Reduce Configuration
Logging & Cluster Monitoring

6. CLOUDERA SANDBOX OR QUICK START

Installation of Cloudera quick start
Difference in sandbox and distributed environment
Overview of apache HUE

7. MAP-REDUCE, MAP-REDUCE STREAMING (IN JAVA)

All Map-Reduce API Concepts
Architecture of Map-Reduce
Writing Map-Reduce Drivers, Mappers, and Reducers in Java
Speeding Up Hadoop Development by Using Eclipse
Differences between the Old and New Map-Reduce APIs
Writing Mappers and Reducers with the Streaming API
Different question raised for Map-Reduce

8. HBASE THE HADOOP DATABASE

Problems with RDBMS
Introduction to HBase
Non-RDBMS, Not-Only SQL or No-SQL
Installation HBase & Deployment
Types CRUD & Batch Operations
Filters, Counters, Pool
Rest Interface & Web-UI

9. SHELL AND COMMANDS

Hadoop Developer commands using shell
Map-Reduce job deployment
Oozie workflow design
Different Components Jobs design.

10. HIVE

Problems with No-SQL Database
Introduction & Installation Hive
Hive Schema and Data Storage
Data Types & Introduction to SQL
Hive-SQL: DML & DDL
Hive-SQL: Views & Indexes
Explain and use the various Hive file formats
Use Hive to run SQL-like queries to perform data analysis
Use Hive to join data sets using a variety of techniques, including Mapside joins and Sort-Merge-Bucket joins
Integration to HBase & Cassandra
Sentiment Analysis and N-Grams
Hive Thrift Service

11. FLUME

Installation of Flume
Ingesting Data from External Sources with Flume
Configuration for flume
REST Interfaces
Best Practices for Importing Data

12. SQOOP

Installation of Sqoop
Ingesting Data from External (RDBMS) Sources with Sqoop
Ingesting Data from/to Relational Databases with Sqoop
Integration of Sqoop and Hbase
Integration of Sqoop and Hive
Best Practices for Importing Data

13. CONCLUSION & FAQS

  • sessions * Hue * Cloudera Manager * Zookeeper *Impala * Ooozie * Etc

    Who can take the Big Data Hadoop Training?

    Developers, Adminstrators, Operation team members or even fresher who want to begin their careers can take this course.

    Prerequisites

    None.

    Duration

    35 Hours Live Training sessions + Unlimited Real Environment/Server Access for you to practice

    Machine Configuration

    8GB RAM and i3+ processor

    Features of our Hadoop Online Training:

  • Live Interactive led sessions
  • 100% Money back guarantee
  • Fast-track / Regular / Weekend as per your convenience
  • Learn Hadoop for Certification
  • Unlimited Real time Environment/Server Access for you to practice
  • Revisit recorded sessions from live trainings

    Our Big Data Hadoop trainers are:

  • Trainers with min 4 project experience.
  • Certified Technical experts from the Industry
  • Excellent Teachers.

  • Fees for Big Data Hadoop Developers Training Online

  • 16,000/- INR or 250 USD (Inclusive all Taxes)
  • Demo of Big Data Hadoop Online Training

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    • Training Feedback

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