Hadoop is one of the open-source frameworks which allows to store and process big data in a distributed environment across clusters of computers using simple programming models. Hadoop is designed to scale up from single servers to thousands of machines, each offering local computation and storage in the industry.
Hadoop Interview Questions And Answers
There are lots of questions that you could be asked based on your experience and also as freshers.
If You are a fresher
If you are a fresher, the interviewer would mostly ask you fundamental questions. Interviewers will also concentrate more on conceptual questions and they will check how strong you are in fundamentals. You should have a good academic project and any training certificate from a reputed institute will also help. Hadoop certification in chennai will make you gain knowledge in hadoop.
From freshers, companies don’t expect much. You should have a sound fundamental knowledge, good attitude, adaptability, and be ready to learn the technology.
If you have experience between: 0–7 years
For Experienced candidates, apart from fundamentals, interviewers will concentrate on your projects, you must have good projects at least one in your resume. Make sure to work on all the phases of the project and have sound knowledge of technologies that you used in the projects.
You must be ready with the reasoning like why the specific component is used for the project and what are the alternatives that can be used. Interview will concentrate on both code as well as data flow and architecture of the project.
If you have experience between: 8+ years
You must be an expert in all the Big Data technologies like Hadoop as well as ecosystem, Spark as well as ecosystem. You must have thorough knowledge of complete data flow, an expert solution architect for the project. You should know about implementation details and follow the best practices to implement the project. knowledge of integration of multiple Big Data components together is also required.
Following are frequently asked questions in interviews for freshers as well experienced developers in the industry.
1. What is Hadoop Map Reduce?
Hadoop MapReduce framework is used for processing large data sets in parallel across a Hadoop cluster. Data analysis uses a two-step map and reduces processes.
2. How Hadoop MapReduce works?
In Hadoop MapReduce during the map phase, it counts the words in each document and in the reduce phase it aggregates the data as per the document spanning the entire collection. During the map phase, the input data is divided into splits for analysis by map tasks running in parallel across the Hadoop framework.
3. Explain what is shuffling in MapReduce?
The process by which the system performs the sort and transfers the map outputs to the reducer as inputs is known as the shuffle in Map Reduce.
4. What is distributed Cache in the MapReduce Framework?
Distributed Cache in MapReduce Framework is an important feature provided by the MapReduce framework. When you want to share some files across all nodes in Hadoop Clusters then Distributed Cache is used. The files could be an executable jar file or simple properties file.
5. Explain what is NameNode in Hadoop?
NameNode is the node where Hadoop stores all the file location information in the Hadoop Distributed File System. In other words, NameNode is the centerpiece of an Hadoop Distributed File System file system. It helps to keep the record of all the files in the file system and tracks the file data across the cluster or multiple machines.
6. Explain what is heartbeat in HDFS?
Heartbeat in HDFS is referred to a signal used between a data node and Name node, and between task tracker and job tracker. If the Name node or job tracker does not respond to the signal, then it is considered there are some issues with the data node or task tracker of the heartbeat.
7. Explain what combiners are and when you should use a combiner in a MapReduce Job?
To increase the efficiency of the MapReduce Program, Combiners are used. The amount of data can be reduced with the help of a combiner which needs to be transferred across to the reducers.
8. What happens when a data node fails?
When a data node fails Jobtracker and namenode detect the failure,On the failed node all tasks are re-scheduled and Namenode replicates the user’s data to another node.
9. Explain what is Speculative Execution?
In Hadoop during Speculative Execution, a certain number of duplicate tasks are launched in. On a different slave node, multiple copies of the same map or reduce task can be executed using Speculative Execution in hadoop.
10. Explain the basic parameters of a Mapper in hadoop?
The basic parameters of a Mapper in hadoop are LongWritable and Text,Text and IntWritable
11. Explain the function of the MapReduce partitioner?
The function of MapReduce partitioner in hadoop is to make sure that all the value of a single key goes to the same reducer. This eventually helps even distribution of the map output over the reducers.
12. Explain the difference between an Input Split and HDFS Block?
The logical division of data is known as Split while a physical division of data is known as Hadoop Distributed File System Block
13. What happens in text format?
In text input format each line in the text file is a record in the system. Value is defined as the content of the line while Key is the byte offset of the line. For instance, Key: longWritable, Value: text
14. Mention what are the main configuration parameters that users need to specify to run MapReduce Job?
The user of the MapReduce framework needs to specify the following things.
- Job’s input locations in the distributed file system
- Job’s output location in the distributed file system
- Input format
- Output format
- Class containing the map function
- Class containing the reduce function
- JAR file contains the mapper, reducer and driver classes
15. Explain what WebDAV is in Hadoop?
WebDAV is a set of extensions to HTTP which helps to support editing and updating files. On most operating systems WebDAV shares can be mounted as filesystems, so it is possible to access HDFS as a standard filesystem by exposing HDFS over WebDAV.
16. Mention Hadoop core components?
Hadoop core components include,
17. Mention the data components used by Hadoop?
Data components used by Hadoop are
18. Mention the data storage component used by Hadoop?
The data storage component used by Hadoop is HBase.
19. What are the different Hadoop configuration files?
The different Hadoop configuration files includes:
- Master and Slaves
20. How to copy data from the local system onto HDFS?
Syntax: hadoop fs –copyFromLocal [source] [destination]
Example: hadoop fs –copyFromLocal /tmp/data.csv /user/test/data.csv
These are the questions which are mostly asked by the interviewers. If you want to shine bright in the Hadoop field then join hadoop training in chennai. Hadoop courses in chennai makes you develop a strong career in hadoop field and gives you career guidance to make your career life wealthy.