Hadoop is an open-source big-data framework with YARN, HDFS, and MapReduce as the three components. Many companies and organizations use Hadoop globally, including Twitter, Netflix, Uber, and the NSA of the United States.
It helps to know what kind of Hadoop interview questions to expect in order to better understand what interviewers are looking for. This article focuses on Hadoop interview questions so you can gauge your preparation levels.
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In this article, we’ll cover:
We’ll begin with some sample Hadoop interview questions and answers to get a basic idea of what to expect:
HDFS stands for Hadoop Distributed File System. It serves as the storage unit of Hadoop and follows master and slave topology. It helps us take different types of data as blocks and store them in a distributed environment.
The three modes are:
Resource manager, Node manager, container, and application master are some important YARN components.
YARN stands for Yet Another Resource Negotiator and serves as the processing framework in Hadoop. It helps by managing resources and providing an execution environment for the processes.
A trick question. MapReduce prohibits reducers from communicating with each other. So reducers can’t communicate with each other and run in isolation.
Now, here are some sample Hadoop interview questions. See if you can solve them:
Let’s move a step further with some Hadoop interview questions for experienced professionals:
Lastly, here are some Hadoop data engineer interview questions. Ensure you can solve them before your interview:
Q1. What are the three main components of Hadoop?
The three components of Hadoop are Hadoop HDFS (storage unit), Hadoop MapReduce (processing unit), and Hadoop YARN (resource management unit).
Q2. Name the three modes in which Hadoop can run.
The three modes Hadoop can run in are Standalone mode, Pseudo-distributed mode, and Fully-distributed mode.
Q3. What is Hadoop used for?
Apache Hadoop is used for the efficient storage and processing of large datasets. The datasets are massive; their size ranges from gigabytes to petabytes. Hadoop enables the clustering of multiple computers to analyze massive datasets faster in parallel instead of using one large computer for storage and processing.
Q4. Name the different Hadoop configuration files.
Hadoop configuration files include hadoop-env.sh, mapred-site.xml, core-site.xml, Master, Slaves, yarn-site.xml, and hdfs-site.xml.
Q5. What are some key characteristics of Hadoop?
Hadoop is open-source, cost-effective, and faster in data processing. Based on the data locality concept, it provides fault tolerance, high availability, and feasibility. Hadoop cluster is also highly scalable.
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