Big Data Interview? 8 Must-know Questions and Answers
By Saheli Roy Chowdhuri
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!
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
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.
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.
Knowing these popular questions is bound to increase your chances of landing a coveted data science job.
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