Big Data Interview? 8 Must-know Questions and Answers

We are now in an era where companies are handling copious amounts of data daily, trying to make sense of it all. This has quickly paved the way for emerging job roles in the industry, such as Data Scientist, Data Analyst, Database administrator, Big Data Engineer among others. If you have been aiming to crack any of these through relevant big data science training, here are some must-know questions and answers in the field of big data science that can maximise your chances!

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1.Define the Five Vs of Big Data

This is an important fundamental question and a go-to starting point for many interviewers. Big Data is essentially a collection of complex unstructured or semi-structured data sets that deliver actionable insights. 

The Four Vs are:

Volume: Amount of available data

Variety: Various formats of data

Velocity: Speed at which data is growing

Veracity: Degree of the accuracy of available data

Value: Ability to turn data into value

2.What Is the Difference Between HDFS and YARN?

HDFS refers to the Hadoop Distributed File System that is used to store data in distributed computing. It consists of two node types:

NameNode: Only stores the metadata of HDFS and tracks files across the cluster

DataNode: The background process that is responsible for storing and managing the actual data on the slave node

YARN manages resources and executes big data processes. It consists of:

ResourceManager: assigns processes to nodes and handles requests

NodeManager: on the correct DataNode the processes are executed

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3.What steps are involved in the deployment of a big data solution?

Any Big Data solution involves the following steps:

Data Ingestion: extraction of data from various sources like Salesforce, SAP, or MySQL.

Data Storage: Involves storing the extracted data in an HDFS (for sequential access) or NoSQL (for random read/write access) database.

Data Processing: Using a processing framework such as Spark, MapReduce, or Pig to process the data.

4.What are The Main Differences Between NAS (Network-Attached Storage) and HDFS?

5.What Are the Common Input Formats in Hadoop?

Common input formats in Hadoop are:

Text Input Format: The default input format of Hadoop that is automatically considered by the RecordReader if no file format has been defined.

Sequence File Input Format: Used to read files in a sequence. It consists of serialized/binary key-value pairs. Data is internally stored when MapReduce tasks are processed.

Key Value Input Format: Used for plain text files which are broken into lines. Each line is further divided into key and value parts by a separator byte.

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6.What Is the JPS Command Used for In Hadoop?

JPS (Java Virtual Machine Process Status Tool) command in Hadoop is used for testing the working of all the daemons. These include daemons like NameNode, DataNode, ResourceManager, and NodeManager.

7.What Is the Correlation Between Hadoop and Big Data?

Big Data is the field that deals with the analysis, systematic extraction, and handling of data sets that are otherwise deemed to be too large or complex to deal with by traditional data-processing software.

Hadoop is the core platform that enables users to structure Big Data while solving any related analytical issue. It is an open-source software framework that is used for storing and processing large-scale data sets on clusters of commodity hardware by using a map-reduce programming model.

8.What Are Edge Nodes in Hadoop?

Edge nodes are the gateway nodes that act as an interface between the Hadoop cluster and the external network. They are used in staging areas and to run client apps and cluster administrative tools. A single node usually makes up for the requirements of multiple Hadoop clusters. Though they require enterprise-class storage capabilities.

 

Conclusion

Knowing these popular questions is bound to increase your chances of landing a coveted data science job.

If you have been struggling to answer these questions on your own, upskilling through a dedicated Big Data science course can be a good option for you. Here are some leading data science and big data analytics courses that we offer at Manipal ProLearn:

Post Graduate Certificate Program in Machine Learning and Data Science 

PG Diploma in Big Data Science Course

Data Analysis and Visualization

Big Data Hadoop Training

Data Visualisation for Data Science using R

Exploratory Data Analysis for Data Science using R

Visit our website to learn more about the leading data science and big data analytics certifications and give your career the boost that you have been yearning for!