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Best Institutes for Hadoop Admin training in Agra with Course Fees

List of 2+ Hadoop Admin training institutes located near to you in Agra as on December 15, 2019. Get access to training curriculum, placement training, course fees, contact phone numbers and students reviews.

 

 

training institutes Softechno Institute
Agra - Sikandra
Best training institute
Softechno Institute at Sikandra - training room	 photo_16590 
Address: HALL NO.3 2ND FLOOR BHAWANA MULTIPLEX, KARGIL X-ING SIKANDRA -BODALA ROAD, SIKANDRA AGRA.

It provides training on dot net, java, oracle, sql server, C, C++, PHP, HTML.
 
training institutes DD Sir Infomatics
Agra - Khandari
training institute
DD Sir Infomatics at Khandari - computer lab	 photo_18333 DD Sir Infomatics at Khandari - training pamphlets photo_18332 
Address: Kendriya Hindi Sansthan Road, Bansal Complex Khandari Agra-282005

 
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Hadoop Admin Training Institutes in Agra - by Location

Yet5.com Provides complete list of best Hadoop Admin training institutes in Agra and training centers with contact address, phone number, training reviews, course fees, job placement, course content, special offers and trainer profile information by area.

 

 

 

Learning Hadoop Admin course in Agra - Benefits, Advantages & Placements.

We have identified the benefits of learning hadoop-admin course in Agra.
Hadoop Admin training in Agra is part of Hadoop training course class, Hadoop is an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation. Hadoop makes it possible to run applications on systems with thousands of commodity hardware nodes, and to handle thousands of terabytes of data. Its distributed file system facilitates rapid data transfer rates among nodes and allows the system to continue operating in case of a node failure. This approach lowers the risk of catastrophic system failure and unexpected data loss, even if a significant number of nodes become inoperative. Consequently, Hadoop quickly emerged as a foundation for big data processing tasks, such as scientific analytics, business and sales planning, and processing enormous volumes of sensor data, including from internet of things sensors.
Hadoop was created by computer scientists Doug Cutting and Mike Cafarella in 2006 to support distribution for the Nutch search engine. It was inspired by Googles MapReduce, a software framework in which an application is broken down into numerous small parts. Any of these parts, which are also called fragments or blocks, can be run on any node in the cluster. After years of development within the open source community, Hadoop 1.0 became publically available in November 2012 as part of the Apache project sponsored by the Apache Software Foundation. Organizations can deploy Hadoop components and supporting software packages in their local data center. However, most big data projects depend on short-term use of substantial computing resources. This type of usage is best-suited to highly scalable public cloud services, such as Amazon Web Services (AWS), Google Cloud Platform and Microsoft Azure. Public cloud providers often support Hadoop components through basic services, such as AWS Elastic Compute Cloud and Simple Storage Service instances. However, there are also services tailored specifically for Hadoop-type tasks, such as AWS Elastic MapReduce, Google Cloud Dataproc and Microsoft Azure HDInsight. The Hadoop frameworks comprised of two main core components i.e. HDFS and MapReduce framework. Hadoop framework divides the data into smaller chunks and stores each part of the data in the separate node within the cluster. By doing this, the time frame to storing the data onto the disk significantly reduces. In order to provide high availability, Hadoop replicates each part of data on to other machines that are present within the cluster. The number of copies it replicates depends on the replication factor. The advantage of distributing this data across the cluster is that while processing the data it reduces the lot of time as this data can be processed simultaneously. The Figure shows the Hadoop working model for 4TB of data in 4 nodes of the Hadoop cluster.

Agra is located on the northern state of Uttar Pradesh on the banks of Yamuna River. It is a major tourist spot due to its Mughal buildings. Not only it attracts tourists, it also attracts students from all over India because it is a home for the prestigious Agra University. A total of 10 institutes comprising of various departments and 700 colleges are affiliated to Agra University which is now called as Dr.Bhim Rao Ambedkar University. It also is home for three prestigious Government Schools such as Kendriya Vidyalaya No 1, No 2 and No 3. Agra holds the literacy rate of 75.11%. Maurya Software Pvt Ltd, Adysoft, Perfect Software, Digita Software Solution, Suneet Infotech etc are located in Agra which offers job opportunities for people all over India. It also holds the privilege of holding India’s best training centers which provide exclusive and affordable training.
You have travel connectivity to hadoop-admin course educational training institutes in Agra. Agra Airport serves Air India flight which flies to Delhi, Varanasi and Khajuraho. Agra holds the North Central Railways serving to the important cities all over India. There are a total of 12 railway stations. Idgah Bus stand, Fort Depot, Taj Depot, and Inter State Bus Terminal are the major bus stops located in Agra which connects Agra to many bigger cities in North India. Also, Agra Municipal Corporation runs the bus services in Agra. Rickshaws and auto rickshaws are also frequently used by commuters due to its feasibility. The city also serves Agra Metro Rail Transport for comfortable commutation.

 

 

 

Hadoop Admin course Content / syllabus in agra

Below is the Hadoop Admin course content in agra used by the training institutes as part of the Hadoop Admin course training. The Hadoop Admin course syllabus covers basic to advanced level course contents which is used by most of Hadoop Admin training classes in agra .

 

1.INTRODUCTION
a.Big Data
b.3Vs
c.Role of Hadoop in Big data
d.Hadoop and its ecosystem
e.Overview of other Big Data Systems
f.Requirements in Hadoop
g.Use Cases of Hadoop

2.Installing the Hadoop Distributed File System (HDFS)
a.Defining key design assumptions and architecture
b.Configuring and setting up the file system
c.Issuing commands from the console
d.Reading and writing files

3. Setting the stage for MapReduce
a.Introducing the computing daemons
b.Dissecting a MapReduce job

4. Defining Hadoop Cluster Requirements
a.Selecting appropriate hardware
b.Designing a scalable cluster

5. Building the cluster
a.Installing Hadoop daemons
b.Optimizing the network architecture

6. Configuring a Cluster – Pseudo node and multi - node
a.Setting basic configuration parameters
b.Configuring block allocation, redundancy and replication

7. Deploying MapReduce
a.Installing and setting up the MapReduce environment
b.Delivering redundant load balancing via Rack Awareness

8. Configuring a Cluster
a.Setting basic configuration parameters
b.Configuring block allocation, redundancy and replication

9. Deploying MapReduce
a.Installing and setting up the MapReduce environment

10. Maintaining HDFS
a.Starting and stopping Hadoop daemons
b.Monitoring HDFS status
c.Adding and removing data nodes

11. Administering MapReduce
a.Managing MapReduce jobs
b.Tracking progress with monitoring tools
c.Commissioning and decommissioning compute nodes

12. Performing Hadoop status checks
a.Importing and exporting relational information with Sqoop

13. Planning for Backup, Recovery and Security
a.Coping with inevitable hardware failures
b.Securing your Hadoop cluster

14. Extending Hadoop
a.Enabling SQL-like querying with Hive
b.Installing Pig to create MapReduce jobs
c.Working with Zookeeper and Ooziew workflow

 

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