Hadoop Administration Certification Training

Hadoop mainly consists of three layers:  

• HDFS (Hadoop Distributed File System): the place where all the data is stored,  
• Application layer (on which the MapReduce engine sits): to process the stored data, and 
• YARN: which allocates the resources to various slaves. All of these are operating on Master and Slave nodes. 

Hadoop is an open-source framework written in Java that enables the distributed processing of large datasets. Hadoop is not a programming language. 

Hadoop developers are needed to develop or program applications whereas administrators are required to run those applications. Let’s see how Hadoop developer and administrator differ from each other in terms of roles and responsibilities:  

A few responsibilities of Hadoop Administrator: 

• Installing Hadoop in a Linux environment
• Runningand maintaininga Hadoop cluster 
• Ensuringthat a Hadoop cluster is running all the time 
• Creation and removal of a new node in a cluster environment
• Implementingand administeringHadoop infrastructure continuously 

A few responsibilities of Hadoop developer: 

• To load data using ETL tools from various platforms into the Hadoop platform
• Deciding a file format that would be most effective for a task
• Cleaning data using user-defined functions or streaming API based on the requirements
• Definingthe job flow in Hadoop 
• Maintaining, scheduling, and managinglog files.

Following is a list of different components of the Hadoop ecosystem: 

• HDFS 
• MapReduce 
• YARN 
• Hive 
• Apache Pig 
• Apache HBase 

Hadoop can store and process many unstructured datasets that are distributed across various clusters using simple program models. It breaks up unstructured data and distributes it into several parts for side by side data analysis. Rather than relying on one computer, the library is designed for detecting and handling failures of the application layer, thereby delivering a high-quality service on top of a cluster of computers. On top of these, Hadoop is an open-source framework available to everyone. 

Hadoop is a framework that is mainly written in the Java programming language, with some native code in C and command-line utilities written as shell scripts. Since MapReduce Java code is common any programming can be used with Hadoop. 

The best language to use for Hadoop is a matter of personal choice. Python helps when doing quick and simple programs. While the number of functions can be reduced using other languages like Python and Scala, there are some advanced features of Hadoop that are only available via Java API. Often, the programmer would be required to dig deep into the coding and figure out what is wrong, and Java especially helps in doing that. Scala language can be used because Hadoop is built on the same ecosystem. 

If Big Data is the problem, Hadoop can be said to be the solution. The Hadoop framework can be used for storing and processing big data that is present in large clusters in an organized manner. Hadoop segregates the big data into small parts and stores them separately on different servers present in a particular network. It is highly efficient and can handle large volumes of data. So, with knowledge of Hadoop, you can work on Big Data quickly and efficiently. 

Hadoop plays a tremendous role in the Big Data industry. It is easy to use, scalable and cost-effective. Hadoop provides massive storage solutions for any kind of data and can handle virtually limitless concurrent tasks or jobs. 

Hadoop is not a database; it is a software ecosystem that allows parallel computing on a vast scale. Hadoop enables specific types of NoSQL distributed databases (e.g. HBase) to spread the data across thousands of servers without affecting the quality.  

Yes, Hadoop is an Open-Source software framework that allows storing and processing the massive amount of data.  

Hadoop is the most favoured and in-demand Big Data tool worldwide. It is popular due to the following attributes: 

• Power of Computing-  

The distributed computing model in Hadoop processes big data very fast. The power of computing will be more if the number of nodes you use is more. 

• Massive data storing and processing- 

This tool lets organizations store and process massive amounts of any type of data quickly. 

• Zero Fault tolerance rate- 

HDFS is highly fault tolerant and handles faults by the process of replica creation. In case a node goes down, the tasks are redirected to other nodes to ensure that the distributed computing doesn’t fail, and fault tolerance rate will be zero. 

• Cheapest Price- 

It is an open-source framework that uses commodity hardware to store and process large amounts of data.  

• More Flexibility- 

Hadoop allows data processing before storing it, unlike in a traditional relational database.   

• Scalability-  

You can extend your system easily if you are required to handle more data by adding nodes with the help of the administration.    

Following are the benefits of Hadoop technology: 

• Hadoop is a storage platform which can store and distribute very large sets of data across hundreds of servers 
• Hadoop is a cost-effective tool as it can store huge data sets for businesses 
• Hadoop allows businesses to access new data sources easily  
• Hadoop can process terabytes of data in just minutes and petabytes of data in hours 
• The major benefit of using Hadoop is that it is resilient to failure due to its zero-fault tolerance rate    

The following are the top five organizations that are using Hadoop: 

• Marks and Spencer 
• Royal Bank of Scotland 
• Expedia 
• British Airways 
• Royal Mail 

Hadoop is a crucial tool in Data Science, and Data Scientists who have knowledge of Hadoop are highly sought after. Given below are the reasons why Data Scientists use Hadoop: 

• Transparent Parallelism 

With Hadoop, Data Scientists can write Java-based MapReduce code and use other big data tools in parallel. 

• Data transport is easy 

Hadoop helps Data Scientists in transporting the data to different nodes on a system at a faster rate. 

• Load data into Hadoop first 

The very first thing data scientists can do is to load data into Hadoop. For this, they need not do any transformations to get the data into the cluster. 

• Easy data exploration 

With Hadoop, Data Scientists can easily explore and figure out the complexities in the data. 

• Data Filtering 

Hadoop helps data scientists to filter a subset of data based on requirementsand address a specific business problem. 

• Sampling for data modelling 

Sampling in Hadoop gives a hint to Data Scientists on what approach might work best for data modelling. 

As Hadoop is in great demand, those professionals who are seeking a career in Big Data would do well to add it to their resume. Learning Hadoop needs hard work and full dedication to the study. There are various sources available that you can refer to learn Hadoop. The sources include videos, blogs, tutorials, and books. If you want to learn Hadoop through hands-on learning, you can go for the Hadoop training that will help you to clear your every doubt while learning and working on the projects.        

There are several free or paid resources available in the market to learn the Hadoop Administration course. The following is a list of resources that you can refer to: 

• Books 
• Hadoop Operations- A Guide for Developers and Administrators- Eric Sammer 
• Expert Hadoop 2 Administration: Managing Spark, YARN, and MapReduce- Sam R. Alapati 
• Hadoop Operations and Cluster Management Cookbook- Shumin Guo 
• Videos 
  • Hadoop Administrator tutorial for beginners 
  • Linux basics for Hadoop Administrators 
  • Hadoop Administration Tutorials 
• You can refer to various blogs 
• Take a Training- Learning by doing is the best way to get a grasp on any tool.

No, knowledge of a programming language is not required to learn the Hadoop administration course. However, a strong knowledge of Linux is mandatory to undertake a Hadoop administration role in an organization.  

The simple answer to this is if you have a zeal to work in the Big Data industry as a Hadoop administrator, it is easy to learn. However, undergoing Hadoop administration training will help you gain practical knowledge on Hadoop including Hadoop modules such as HDFS, Map Reduce, Hive, HBase, Sqoop, Flume, Oozie, Yarn. Learning from experts with years of experience will help you to understand concepts with ease, and working on a project will aid you in building a solid foundation in Hadoop.      

You are required to be aware of the following skills or techniques to become a Hadoop Administrator: 

• You should be able to deploy a Hadoop cluster, keep track of tasks, add or remove nodes, monitor clusters, etc. 
• General operational skills that include good troubleshooting skills, understanding of system’s capacity, bottlenecks, basics of memory, CPU, OS, storage, and networks 
• A strong understanding of Linux 
• Basic knowledge of open-source configuration management and deployment tools such as Puppet or Chef and Linux scripting 
• Should know core Java 
• Highly proficient in Unix commands and Unix based File system 
• Networking knowledge 
  

The best training institutes to learn Hadoop Administration course are as follows. 

• Edureka 
• Udemy 
• KnowledgeHut 
• Cloudera 
• Mindmajix 

KnowledgeHut is among the preferred coaching platforms for Hadoop Administration. The institute offers a clear and structured training on Hadoop Administration. Some of the benefits of choosing KnowledgeHut as your training provider are -  

• It is an Instructor-led training course  
• Industry renowned trainers 
• Practical approach to learning  
• Comprehensive training from basics to advanced concepts  
• Case Study based learning  
• Post-training mentoring 

Hadoop Admin professional course is not just limited to the IT industry. Any individual with a sound knowledge of Linux can be a part of the Hadoop Admin training. Here are the few steps to follow to become a Hadoop admin professional: 

• Enrol for the Hadoop admin course from KnowledgeHut 
• Take 30-hrs of live training from the Hadoop experts 
• Take 60-hrs of MCQs assignments 
• Work on 2 real-time projects to gain hands-on experience 
• Earn course completion certificate from KnowledgeHut 

Upon successful completion of the Hadoop Administration certification training along with live sessions, practical case studies you will be awarded an industry-recognized course completion certificate from KnowledgeHut. 

The course completion Hadoop Administration Certificate from KnowledgeHut has lifetime validity. 

Most of the companies are looking for candidates who can handle their requirements. Hadoop Administration training is the best way to demonstrate to your employer that you belong to the category of niche professionals who can make a difference. 

The demand for Hadoop in leading organizations has increased a lot, and today it is considered one of the most powerful versatile framework sources to opt for. There are multiple career opportunities in which you can make your mark across industries. You will be benefited with the following: 

• Get an edge over other professionals 
• Knowledge of Hadoop will enhance your salary prospects 
• Get hired by leading corporates 
• Plentiful job opportunities in a wide range of roles 

Today organizations need Hadoop administrators to take care of large Hadoop clusters. Top companies like Facebook, eBay, Twitter, etc are using Hadoop. The professionals with Hadoop skills are in huge demand. According to Payscale, the average salary for Hadoop Administrators is $121k.  

The Hadoop Administrator course is the right choice if you want to upgrade your data analytics skills. It is one of the best courses that provides you the practical as well as real-time industry experience. This course comes with lifetime validity. You can advance your big data skills which results in better job opportunities. By the end of the course, you will be able to get a clear understanding of the plan and deployment of a Hadoop Cluster, obtain an in-depth understanding of Apache Hadoop, HDFS, and Hadoop administration. 

The average Hadoop Admin salary in the USA is $110,000 per year or $56.41 per hour. Entry-level positions start at $78,000 per year, and the most experienced professionals can earn up to $175,939 per year. 

Big Data is everywhere! It has found uses across industries ranging from retail to politics to environmental issues. Most significantly it has been used to understand and target customers. Retailers are also using it with success to optimize their business processes. Big Data has also revolutionized the way healthcare operates and has helped huge advances to be made in the field of science and technology.With the increased adoption of Hadoop in the Big Data space, there is an ever-increasing demand for Hadoop Administrators in the market.  

The following are different types of companies that hire Hadoop Administrator Professionals: 

• IBM 
• Amazon 
• Infosys 
• Vodafone 
• Data Labs 
• Capgemini 
• UnitedHealth Group 
• Cognizant Softvision