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The Big Data and Hadoop Training course from Maxonlinetraing is specially designed in such a way that everyone can enhance their knowledge and skills to become a successful Hadoop developer.

About The Hadoop Admin Online Training:

Maxonlinetraining.com Big Data Hadoop Administrator online training course is

mainly intended to understand the core concepts of  Apache Hadoop and Hadoop Cluster mainly. It

covers the important concepts associated to secure a Hadoop Cluster and Hbase administration. 

1. Hadoop Cluster Administration

Course content:

2. Hadoop Architecture and Cluster setup

3. Hadoop Cluster: Planning and Managing

4. Backup, Recovery and Maintenance

5. Hadoop 2.0 and High Availability

Apache Hadoop is an open-source software framework written in Java for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware.

What is Apache Hadoop?

The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part called Map Reduce.

Hadoop splits files into large blocks and distributes them across nodes in a cluster.

The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System (HDFS), and a processing part called Map Reduce. 

 Hadoop splits files into large blocks and distributes them across nodes in a cluster. 

Hadoop – Advantages and Disadvantages

Advantages of Hadoop

1) Distribute data and computation. The computation local to data prevents the network overload.2) Tasks are independent The task are independent so,• We can easy to handle partial failure. Here the entire nodes can fail

and restart.• it avoids crawling horrors of failure and tolerant synchronous

distributed systems.• Speculative execution to work around stragglers.

3) Linear scaling in the ideal case.It used to design for cheap, commodity hardware.4) Simple programming model.The end-user programmer only writes map-reduce tasks.5) HDFS store large amount of information6) HDFS is simple and robust coherency model7) That is it should store data reliably.

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1) Rough manner:- Hadoop Map-reduce and HDFS are rough in manner. Because the software under active development.2) Programming model is very restrictive:- Lack of central data can be preventive.3) Joins of multiple datasets are tricky and slow:- No indices! Often entire dataset gets copied in the process.4) Cluster management is hard:- In the cluster, operations like debugging, distributing software, collection logs etc are too hard.5) Still single master which requires care and may limit scaling6) Managing job flow isn’t trivial when intermediate data should be kept7) Optimal configuration of nodes not obvious.

Disadvantages of Hadoop

What is Big Data Integration & Analytics Platform 

The Big Data platform offers robust data integration in an open and scalable architecture leveraging

technologies such as Talend, Hadoop, MongoDB to integrate and

process the data.

• Structured Course Curriculum Content. • One Time Pay-Life time access to all videos and sessions. • Daily Assignments and weekly tests. • Unlimited mock interview sessions. • Resume Preparation. • 100% Job Placement Assistance.

Attend our Big Data Hadoop Online Training Demo for free. 

Our Big Data Course Special Features:

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Maxonlinetraining.com technical panel assists you to become certified Big Data Hadoop Admin professional depending on your performance in the project.http://maxonlinetraining.com/hadoop-admin-online-training/

For more details call:  +1 940 440 8084 / +91 953 383 7156Registration https://goo.gl/dcYVqh