Best Hadoop Online Training

Published on May 2016 | Categories: Types, Presentations | Downloads: 56 | Comments: 0 | Views: 419
of 6
Download PDF   Embed   Report

Hadoop Online Training : kelly technologies is the bestHadoop online Training Institutes in Bangalore. ProvidingHadoop online Training by real time faculty in Bangalore.



Hadoop Online Training
Best Hadoop Online Training by Real time Experts:
Hadoop is an open source framework which is used for storing and processing the large scale of data
sets on large clusters of hardware. The specialty of Hadoop involves in HDFS which is used for storing
data on large commodity machines and provides very huge bandwidth for the cluster. Mainly, Hadoop
uses Map Reduce Method for processing large scale data sets. Lead Online Training provides the best
online training for Hadoop by technical experts in subject and will provide you the best training and
makes you perfect in technology. We are always available to support you.
Hadoop Online Training Course Overview:
Basics of Hadoop:

Motivation for Hadoop

Large scale system training

Survey of data storage literature

Literature survey of data processing

Networking constraints

New approach requirements

Basic concepts of Hadoop

What is Hadoop?

Distributed file system of Hadoop

Map reduction of Hadoop works

Hadoop cluster and its anatomy

Hadoop demons

Master demons

Name node

Tracking of job

Secondary node detection

Slave daemons

Tracking of task

HDFS(Hadoop Distributed File System)

Page 1

Hadoop Online Training

Spilts and blocks

Input Spilts

HDFS spilts

Replication of data

Awareness of Hadoop racking

High availably of data

Block placement and cluster architecture


Practices & Tuning of performances

Development of mass reduce programs

Local mode

Running without HDFS

Pseudo-distributed mode

All daemons running in a single mode

Fully distributed mode

Dedicated nodes and daemon running
Hadoop administration

Setup of Hadoop cluster of Cloud era, Apache, Green plum, Horton works

On a single desktop, make a full cluster of a Hadoop setup.

Configure and Install Apache Hadoop on a multi node cluster.

In a distributed mode, configure and install Cloud era distribution.

In a fully distributed mode, configure and install Hortom works distribution

In a fully distributed mode, configure the Green Plum distribution.

Monitor the cluster

Get used to the management console of Horton works and Cloud era.

Name the node in a safe mode

Data backup.

Case studies

Monitoring of clusters
Hadoop Development :

Writing a MapReduce Program

Sample the mapreduce program.

API concepts and their basics

Driver code



Page 2

Hadoop Online Training

Hadoop AVI streaming

Performing several Hadoop jobs

Configuring close methods

Sequencing of files

Record reading

Record writer

Reporter and its role


Output collection

Assessing HDFS

Tool runner

Use of distributed CACHE

Several MapReduce jobs (In Detailed)




Identification of mapper

Identification of reducer

Exploring the problems using this application

Debugging the MapReduce Programs

MR unit testing


Debugging strategies

Advanced MapReduce Programming

Secondary sort

Output and input format customization

Mapreduce joins

Monitoring & debugging on a Production Cluster


Skipping Bad Records

Running the local mode

MapReduce performance tuning

Reduction network traffic by combiner


Reducing of input data

Using Compression

Page 3

Hadoop Online Training

Reusing the JVM

Running speculative execution

Performance Aspects

CDH4 Enhancements :
1. Name Node – Availability
2. Name Node federation
3. Fencing
4. MapReduce – 2
1.Concepts of Hive
2. Hive and its architecture
3. Install and configure hive on cluster
4. Type of tables in hive
5. Functions of Hive library
6. Buckets
7. Partitions
8. Joins
1. Inner joins
2. Outer Joins
9. Hive UDF
1.Pig basics
2. Install and configure PIG
3. Functions of PIG Library
4. Pig Vs Hive
5. Writing of sample Pig Latin scripts
6. Modes of running
1. Grunt shell
2. Java program
8. Macros of Pig
9. Debugging the PIG
1. Difference between Pig and Impala Hive
2. Does Impala give good performance?

Page 4

Hadoop Online Training
3. Exclusive features
4. Impala and its Challenges
5. Use cases
1. HBase
2. HBase concepts
3. HBase architecture
4. Basics of HBase
5. Server architecture
6. File storage architecture
7. Column access
8. Scans
9. HBase cases
10. Installation and configuration of HBase on a multi node
11. Create database, Develop and run sample applications
12. Access data stored in HBase using clients like Python, Java and Pearl
13. Map Reduce client
14. HBase and Hive Integration
15. HBase administration tasks
16. Defining Schema and its basic operations.
17. Cassandra Basics
18. MongoDB Basics
Ecosystem Components
1. Sqoop
2. Configure and Install Sqoop
3. Connecting RDBMS
4. Installation of Mysql
5. Importing the data from Oracle/Mysql to hive
6. Exporting the data to Oracle/Mysql
7. Internal mechanism
1. Oozie and its architecture
2. XML file
3. Install and configuring Apache
4. Specifying the Work flow
5. Action nodes

Page 5

Hadoop Online Training
6. Control nodes
7. Job coordinator
Avro, Scribe, Flume, Chukwa, Thrift
1. Concepts of Flume and Chukwa
2. Use cases of Scribe, Thrift and Avro
3. Installation and configuration of flume
4. Creation of a sample application

Page 6

Sponsor Documents

Or use your account on


Forgot your password?

Or register your new account on


Lost your password? Please enter your email address. You will receive a link to create a new password.

Back to log-in