Hadoop Online Training

Hadoop Online Training By IT Experts :

Pravega online training facility offers Hadoop online training by trainers who have expert knowledge in the Hadoop and proven record of training hundreds of students. Our Hadoop training is regarded as the best online training by our students and corporate clients. We are training partners for corporate clients like IBM. We train students from across all countries like USA, UK, Singapore, UAE, Australia, India. Our Hadoop training is your one stop solution to Learn, Practice and build career in this field at the comfort of your Home with flexible class schedules..

Hadoop Introduction :

Hadoop is an open source software. Hadoop allows distributed processing of the scattered large sets of data across batch of computer servers using simple programming methods. It is outlined to scale up from a single server to thousands of machines, with a very high availability. offers local computation and storage. Rather than depending on hardware, the flexibility of these batches comes from the software’s capability to detect and handle failures at the application layer. This course helps you through address the challenges and take advantage of the core values provided by Hadoop in a vendor neutral way.

Pravega Training offers the Hadoop Online Course in a true global setting.

Hadoop Online Training Concepts : :

Basics of Hadoop:

1.Motivation for Hadoop
2.Large scale system training
3.Survey of data storage literature
4.Literature survey of data processing
5.Networking constraints
6.New approach requirements

Basic concepts of Hadoop
1.What is Hadoop?
2.Distributed file system of Hadoop
3.Map reduction of Hadoop works
4.Hadoop cluster and its anatomy
5.Hadoop demons
6.Master demons
7.Name node
8.Tracking of job
9.Secondary node detection
10.Slave daemons
11.Tracking of task
12.HDFS(Hadoop Distributed File System)
13.Spilts and blocks
14.Input Spilts
15.HDFS spilts
16.Replication of data
17.Awareness of Hadoop racking
18.High availably of data
19.Block placement and cluster architecture
20.CASE STUDIES
21.Practices & Tuning of performances
22.Development of mass reduce programs
23.Local mode
24.Running without HDFS
25.Pseudo-distributed mode

Hadoop administration

1.Setup of Hadoop cluster of Cloud era, Apache, Green plum, Horton works
2.On a single desktop, make a full cluster of a Hadoop setup.
3.Configure and Install Apache Hadoop on a multi node cluster.
4.In a distributed mode, configure and install Cloud era distribution.
5.In a fully distributed mode, configure and install Hortom works distribution
6.In a fully distributed mode, configure the Green Plum distribution.
7.Monitor the cluster
8.Get used to the management console of Horton works and Cloud era.

Hadoop Development :

1.Writing a MapReduce Program
2.Sample the mapreduce program.
3.API concepts and their basics
4.Driver code
5.Mapper
6.Reducer
7.Hadoop AVI streaming
8.Performing several Hadoop jobs
9.Configuring close methods
10.Sequencing of files
11.Record reading
12.Record writer
13.Reporter and its role
14.Counters

CDH4 Enhancements :

1.Name Node – Availability
2.Name Node federation
3.Fencing
4.MapReduce – 2

HADOOP ANALYST

1.Concepts of Hive
2. Hive and its architecture
3. Install and configure hive on cluster
4. Type of tables in hive

PIG :

1.Pig basics
2. Install and configure PIG
3. Functions of PIG Library
4. Pig Vs Hive
5. Writing of sample Pig Latin scripts

IMPALA

1. Difference between Pig and Impala Hive
2. Does Impala give good performance?
3. Exclusive features
4. Impala and its Challenges
5. Use cases

Our Hadoop Online Training batches start every week and we accommodate your flexible timings.