Frequently Asked Interview Questions in Hadoop

Category: Hadoop Posted:Mar 01, 2017 By: admin

1. What is open-source framework?

An open-source framework is a resource with all the source code and license that is available for free to develop and implement in anyone’s organization. This kind of resource also allows the framework to be upgraded by anyone on their own interest (after approved by the monitoring organization).

2. Mention top 5 companies in the world which uses Hadoop.

Hundreds of top companies across the globe had implemented Hadoop in their organization for big data management. Following are the top 5 companies:

  • Yahoo
  • Amazon
  • Facebook
  • Adobe
  • Twitter

3. How significant the contribution of Yahoo to Hadoop?

Yahoo is one of the global companies which uses Hadoop extensively in their organizaiton. In addition to that it contributes more than 80% of the code to the Hadoop Framework.

4. What classes in Hadoop framework library can be used for panel styling?In accordance to the context, the panel can be made more meaningful using the following panel styling classes in Hadoop library. They are,

  • panel-success
  • panel-info
  • panel-warning
  • panel-primary
  • panel-danger

5. What is the use of bootstrap media objects?

Bootstrap media objects are abstract object styles which reduces the coding size of components such as tweets, comments and etc. which contains textual content alongside images.

6. What are the steps to create Bootstrap Dismissal Alerts?

Bootstrap Dismissal Alerts provides a contextual way to provide alert messages for dismissal actions. Following are the two simple steps to create Bootstrap Dismissal Alerts:

  • Create a <div> wrapper with .alert classes such as .alert-success, .alert-info, .alert-warning, .alert-danger, .alert-dismissible and etc.
  • Create a close button and specify the data-dismiss=attribute for the <button> tag.

7. Why input groups are used in form controls?

Input groups are used as an extension to the form controls to make the prepending and appending of text and buttons in forms easier. For instance, symbol can be prepended to every name entered in the twitter username input box.

8. What is Checkpointing in Hadoop?

Checkpointing is a process used in Hadoop to increase the operational efficiency and to avoid delay in the startup of NameNode. This process creates a new fsimage using edit log and existing fsiimage to avoid replaying of unbounded edit log.

9. What is indexing in Hadoop HDFS?

Hadoop follows its unique indexing method while storing the data in Hadoop Distributed File System. It appends the details where the next data block stored in the last part of every data block.

10. How to restart a Namenode in Hadoop?

At times, the restart of Namenode might be required during data processing. There are two ways to restart the Namenode. They are:

Method 1 – Simply click the stop-all.sh option followed by clicking start-all.sh option.

Method 2 – Use the following commands one by one with pressing enter key after each command.

  • sudo hdfs
  • su-hdfs
  • /etc/init.d/ha
  • /etc/init.d/Hadoop-0.20-namenode start

11. What is Hadoop?

Hadoop is a distributed computing platform written in Java. It incorporates features similar to those of the Google File System and of MapReduce.

12. What platforms and Java versions do Hadoop run on?

ASP or Active Server Pages is defined as a server-side script engine for execution in Microsoft Internet Information Server (IIS) for running dynamic content and powerful web pages.

13. What kind of hardware scales best for Hadoop?

Dual processor/dual core machines with 4-8GB of RAM using ECC memory, depending upon workflow needs.

14. Which types of companies hire Hadoop developers and administrators?

Product companies, E-Commerce, Research and Development Centers, Telecommunication, Retail, Technology Consulting Firms.

15. On what concept the Hadoop framework works?

It work on MapReduce and is devised by the Google.

16. What are the basic components of Hadoop application?

Input location of data, output location of processed data, map task, job task, reduced task and job configuration.

 

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