Big Data Interview Questions and Answers
Question - 71 : - Will you optimize algorithms or code to make them run faster?
Answer - 71 : -
How to Approach: The answer to this question should always be “Yes.” Real world performance matters and it doesn’t depend on the data or model you are using in your project.
The interviewer might also be interested to know if you have had any previous experience in code or algorithm optimization. For a beginner, it obviously depends on which projects he worked on in the past. Experienced candidates can share their experience accordingly as well. However, be honest about your work, and it is fine if you haven’t optimized code in the past. Just let the interviewer know your real experience and you will be able to crack the big data interview.
Question - 72 : - Define Big Data and explain the Vs of Big Data.
Answer - 72 : -
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
Question - 73 : - How is Hadoop related to Big Data?
Answer - 73 : -
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.
Question - 74 : - Define HDFS and YARN, and talk about their respective components.
Answer - 74 : -
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.
Question - 75 : - What do you mean by commodity hardware?
Answer - 75 : -
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.’
Question - 76 : - Define and describe the term FSCK.
Answer - 76 : -
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.
Question - 77 : - What is the purpose of the JPS command in Hadoop?
Answer - 77 : -
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.
Question - 78 : - Name the different commands for starting up and shutting down Hadoop Daemons.
Answer - 78 : -
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
Answer - 79 : -
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.
Question - 80 : - What are Edge Nodes in Hadoop?
Answer - 80 : -
Edge nodes refer to the gateway nodes which act as an interface between Hadoop cluster and the external network. These nodes run client applications and cluster management tools and are used as staging areas as well. Enterprise-class storage capabilities are required for Edge Nodes, and a single edge node usually suffices for multiple Hadoop clusters.