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Big Data Interview Questions

Big data Interview Questions: Every Big data job interview is crucial for the candidates. Cracking the Big data interview questions means, the aspirants have found the gateway to growth and success. The immense stress of job interview can be minimized, if Big data job seekers follow the questionnaire, Big data interview questions provided below. The article has been prepared by Aptron's Big data specialists, Big data experts, and Big data trainers who have put their quality experience and knowledge while developing the Big data interview questions and answers for freshers, and experience aspirants. This piece of write-up contains thorough answers covering basic and advanced Big data interview questions. Giving the relevant answers to Big data interview question can assist in deciding the fate of the candidates. Thus, it is immensely important to answer effectively and confidently during the interview sessions by the applicants so that interviewers can consider applicants’ knowledge and talent for the employment.

big data interview questions

About Big data

“Big data” means data analysis of large data sets, systematic extraction of data from structured or unstructured data, breaking down data sets using traditional and latest data processing application, etc. Big data has three key concepts, which are volume, variety, and velocity. Furthermore, The concept of Big Data is immensely required in the sectors such as finance, retail, advertising, telecommunications, utilities, healthcare, pharmaceuticals, and Defense and intelligence. Henceforth, this field is equipped with various challenges that incorporate capturing data, search, sharing, data storage, data analysis, transfer, visualization, querying, data source, updating, and information privacy.

Big Data Interview Questions And Answers

1. What do you understand by the term 'big data'?

Big data deals with complex and large sets of data that cannot be handled using conventional software.

2. What are the steps to deploy a Big Data solution?

The three steps to deploying a Big Data solution are:

  1. Data Ingestion
  2. Data Storage and
  3. Data Processing

3. Name the core methods of a reducer

The three core methods of a reducer are,

  1. setup()
  2. reduce()
  3. cleanup()

4. What are the real-time applications of Hadoop?

Some of the real-time applications of Hadoop are in the fields of:

  • Content management.
  • Financial agencies.
  • Defense and cybersecurity.
  • Managing posts on social media.

5. What is the function of HDFS?

The HDFS (Hadoop Distributed File System) is Hadoop’s default storage unit. It is used for storing different types of data in a distributed environment.

6. Name a few companies that use Hadoop.

Yahoo, Facebook, Netflix, Amazon, and Twitter.

7. What is the default mode for Hadoop?

Standalone mode is Hadoop's default mode. It is primarily used for debugging purpose.

8. What is an EdgeNode?

An EdgeNode is an interface that allows Hadoop to communicate with an outside network. Through it, client applications and Hadoop’s administration tools transfer data to the Hadoop cluster. EdgeNodes require enterprise-class storage facilities as they are highly efficient in managing multiple Hadoop clusters. Data management tools like Oozie, Pig and Flume work with EdgeNodes in Hadoop.

9. How is Hadoop related to Big Data? Describe its components.

Another fairly simple question. Apache Hadoop is an open-source framework used for storing, processing, and analyzing complex unstructured data sets for deriving insights and actionable intelligence for businesses.

The three main components of Hadoop are-

  • MapReduce – A programming model which processes large datasets in parallel
  • HDFS – A Java-based distributed file system used for data storage without prior organization
  • YARN – A framework that manages resources and handles requests from distributed applications

10. Define Big Data and explain the Vs of Big Data.

This is one of the most introductory yet important Big Data interview questions. The answer to this is quite straightforward:

Big Data can be defined as a collection of complex unstructured or semi-structured data sets which have the potential to deliver actionable insights.

The four Vs of Big Data are –

Volume – Talks about the amount of data

Variety – Talks about the various formats of data

Velocity – Talks about the ever increasing speed at which the data is growing

Veracity – Talks about the degree of accuracy of data available

11. How is Hadoop related to Big Data?

When we talk about Big Data, we talk about Hadoop. So, this is another Big Data interview question that you will definitely face in an interview.

Hadoop is an open-source framework for storing, processing, and analyzing complex unstructured data sets for deriving insights and intelligence.

12. Define HDFS and YARN, and talk about their respective components.

Now that we’re in the zone of Hadoop, the next Big Data interview question you might face will revolve around the same.

The HDFS is Hadoop’s default storage unit and is responsible for storing different types of data in a distributed environment.

HDFS has the following two components:

NameNode – This is the master node that has the metadata information for all the data blocks in the HDFS.

DataNode – These are the nodes that act as slave nodes and are responsible for storing the data.

YARN, short for Yet Another Resource Negotiator, is responsible for managing resources and providing an execution environment for the said processes.

The two main components of YARN are –

ResourceManager – Responsible for allocating resources to respective NodeManagers based on the needs.

NodeManager – Executes tasks on every DataNode.

13. What do you mean by commodity hardware?

This is yet another Big Data interview question you’re most likely to come across in any interview you sit for.

Commodity Hardware refers to the minimal hardware resources needed to run the Apache Hadoop framework. Any hardware that supports Hadoop’s minimum requirements is known as ‘Commodity Hardware.’

14. Define and describe the term FSCK.

FSCK stands for Filesystem Check. It is a command used to run a Hadoop summary report that describes the state of HDFS. It only checks for errors and does not correct them. This command can be executed on either the whole system or a subset of files.

15. What is the purpose of the JPS command in Hadoop?

The JPS command is used for testing the working of all the Hadoop daemons. It specifically tests daemons like NameNode, DataNode, ResourceManager, NodeManager and more.

(In any Big Data interview, you’re likely to find one question on JPS and its importance.)

16. Name the different commands for starting up and shutting down Hadoop Daemons.

This is one of the most important Big Data interview questions to help the interviewer gauge your knowledge of commands.

To start all the daemons:

./sbin/start-all.sh

To shut down all the daemons:

./sbin/stop-all.sh

17. Why do we need Hadoop for Big Data Analytics?

This Hadoop interview questions test your awareness regarding the practical aspects of Big Data and Analytics.

In most cases, Hadoop helps in exploring and analyzing large and unstructured data sets. Hadoop offers storage, processing and data collection capabilities that help in analytics.

18. Explain the different features of Hadoop.

Listed in many Big Data Interview Questions and Answers, the best answer to this is –

Open-Source – Hadoop is an open-sourced platform. It allows the code to be rewritten or modified according to user and analytics requirements.

Scalability – Hadoop supports the addition of hardware resources to the new nodes.

Data Recovery – Hadoop follows replication which allows the recovery of data in the case of any failure.

Data Locality – This means that Hadoop moves the computation to the data and not the other way round. This way, the whole process speeds up.

19. Define the Port Numbers for NameNode, Task Tracker and Job Tracker.

NameNode – Port 50070

Task Tracker – Port 50060

Job Tracker – Port 50030

20. How does HDFS Index Data blocks? Explain.

HDFS indexes data blocks based on their respective sizes. The end of a data block points to the address of where the next chunk of data blocks get stored. The DataNodes store the blocks of data while the NameNode manages these data blocks by using an in-memory image of all the files of said data blocks. Clients receive information related to data blocked from the NameNode.

Career scopes and salary scale

Every business domain in current scenario is witnessing the job crisis. However, when it is about Big data, the job seekers in the respective technology are making a better move in their career. Artificial Intelligence (AI), Machine learning (ML), Internet of Things (IoT), Big Data, and other programming sectors are completely dependent on Big data analysis. Data Analyst and Data Scientist are the talent behind current technological expansion. Besides, Big data has occupied the topmost place in the arena of AI, ML, IoT, etc. A newly joined Big data candidate in an organization can expect a minimum salary of 38,000 dollars per annum. However, the salary of an experienced Big data expert always get the double of it. The salaries are very reliant upon the location, business, and the company’s requirements.

Conclusion

This piece of write-up ‘Big data interview questions’ has efficiently answered every advanced Big data interview questions. Also, the approach in Big data interview questions for experienced is being projected by our trainers and team of experts. They have put their top of the familiarity to assist professionals in getting answers to all doubts and not clear perceptions. Even then, if learners still require more detailing about Big data, they may drop in a message to our experts related to Big data interview questions for experienced professionals. Our trainers would be happy to help and resolve all your Big data-programming issues of the students. Join Big Data Training in Noida, Big Data Training in Delhi, Big Data Training in Gurgaon

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