Components of Hadoop You Should Definitely Learn

If you are interested in entering the data analytics space then you must have done some research about the big data job market. I assume you have come across a plenty of job roles that require Hadoop skills. It is pretty well known that big data training starts right at Hadoop. It is the best way to understand the system in which big data analytics functions. But Hadoop is a software suit not a singular tool or platform that you can learn.

 Hadoop is an umbrella

Hadoop is an umbrella term that refers to a lot of different technologies. These are all components of Hadoop and each has its own purpose and functionality. It is important to have some knowledge of the different components and to decide which ones you would like to master. Let us, then, take a look at some different components of Hadoop.

HDFS comes first

Hadoop Distributed File System is probably the most important component of the software suit. HDFS changed the game for a lot of companies during the early days of big data analytics. It solves and simplifies the most critical problem, that of data storage. While the data influx is ever widening and increasingly variegated HDFS makes it possible to store more and more data at a reasonable cost.

HDFS consists of two nodes – Name node and Data node. The former manages and maintains the data nodes and helps keep track of the added and deleted blocks of data.

Data nodes are where the data actually is. It adds and deletes blocks of data in accordance to the command of the name node.

Hbase deserves this place

Hbase is an open source non relational data base which was designed to run on top of HDFS. It allows you to store data in a fault tolerant way. It works brilliantly when you need to search for a very small a very specific data from a really huge heap of information.

MapReduce leads the processing unit

It is the main component for processing data in a Hadoop ecosystem. As the name suggests it has two functionalities- map and reduce. Map function helps in grouping sorting and filtering. Reduce summarizes the results produced by the filters applied by the map function.

Pig lets you breathe if you are not the best programmer

Pig has two parts. A language called pig Latin and pig run time. Pig Latin can be used to write applications for Analytics functions. It is surprising that 10 lines are f pig Latin code can be equivalent to 100 lines of MapReduce code. But anyway at the back end of Pig Latin it is MapReduce that gets the job done. Pig Latin code is internally converted into MapReduce code.

Hive

Hive is a very popular tool as it can process large data sets as well as real time data. This multipurpose tool is highly scalable. It supports data from various sources. Working with Hive can give you some extra mileage in the job market.

So, these are basically the most important components of Hadoop and their functions. It is ridiculously difficult to master the whole lot but it is advisable that you learn at least a couple of these tools to get a strong footing in the domain of data analytics.

Don’t forget the Spark though

The experts are quite at war with each other over the question that which one is more important Spark or Hadoop. You have just learnt that Hadoop is not a single tool but a suit containing a range of different tools. So, you need not waste your time over the fight between Hadoop and Spark. Just remember that Spark is a great complimentary tool for the Hadoop ecosystem. It can work on top of HDFS while processing real time data in lightning speed. You may as well learn Spark. It will definitely give you a vantage point.

The job market

This is always a relevant point in any article about any technology. Learning something should lead you somewhere else it is pretty useless in today’s world. Don’t worry, Hadoop training does take you somewhere. Currently there are thousands of jobs in India requiring Hadoop skills. The problem with Hadoop is that it is hard to find Hadoop professionals, that is why a lot of new companies are trying to bypass Hadoop. Hadoop professionals usually do not come cheap. So, with Hadoop skills you can expect an elevated salary.

Training in India

India has always come up with world class training facilities for any technology. Hadoop training in Bangalore is quite top notch. You can also find good institutes in the NCR. The combination of videos and live instructions make the best courses. Choose your course well; work hard; get ready for the opportunities which are sure to come.

2 thoughts on “Components of Hadoop You Should Definitely Learn

  1. Great article about the topic Hadoop.Thanks for sharing this valuable information and I’m waiting for like this topic keep on updating .nowadays the demand of Hadoop is more in the current trend.

  2. Thanks for sharing such an informational article. There is a lot of good institutes available in India which can give you a good knowledge of Hadoop and other courses.

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