Hadoop Interview Questions

In this blog you can find Hadoop interview questions and answers that have been asked in reccent years in many companies.

1) What is meant by Hadoop?

Hadoop is distributed computing platform and is written in Java. It consists of the following features like Google File System and MapReduce.

2) mention which platform and Java version required to run Hadoop?

Java 1.6.x or advanced versions are good for Hadoop work , preferably Linux and Windows are the supported operating system for Hadoop environment , but BSD, Mac OS/X, and Solaris are more famous for working.

3) What are Hardware specifications for Hadoop?

Hadoop can run on dual processor/ dual core machines along with 4-8 GB RAM using ECC memory. It depends on the workflow designs 4.Describe most common input formats defined in Hadoop?The most common input formats in Hadoop are:

TextInputFormat
KeyValueInputFormat
SequenceFileInputFormat

TextInputFormat is default input format.

5) How do you categorize a big data?

The big data is categorized by using the features like:

Volume
Velocity
Variety

6) what is the use of .mecia class?

For the floating media objects from one side to another side , we use this class.

7) List the use of the bootstrap panel.

Panels in bootstrap from the boxing of DOM components.

8) Describe purpose of button groups?

Button groups used for placement of more than one buttons in the same line. 9) List the various types of lists supported by Bootstrap.

Ordered list
Unordered list
Definition list

10) Name the command which is used for the retrieval of the status of daemons running the Hadoop cluster?

The ‘jps’ command used for the retrieval of status of daemons running the Hadoop cluster.

11) What is InputSplit ? Explain.

When a Hadoop job runs, splits input files into chunks and assigns each split to mapper for processing. which is called the InputSplit.

12) Explain textInputFormat?

TextInputFormat is the text file which is a record. Value is content of the line while Key is the byte offset of the line. For example Key: longWritable, Value: text

13) What is meant by SequenceFileInputFormat in Hadoop?

SequenceFileInputFormat in Hadoop is used to read files in sequence. It is the specific compressed binary file format which passes data between output of one MapReduce job to the input of some another MapReduce job.

14) How many InputSplits can be made by a Hadoop Framework?

Hadoop makes total 5 splits :

One split for 64K files
Two splits for 65MB files, and
Two splits for 127MB files

15) Describe the use of RecordReader in Hadoop?

InputSplit assigned with work but doesn’t know how to access . The record holder class is totally responsible for performing loading the data from its source and convert it to keys pair suitable for reading by Mapper. The RecordReader’s instance can also be defined by the Input Format.

16)Describe JobTracker in Hadoop?

JobTracker is service within the Hadoop which runs MapReduce jobs on the cluster.

17) Explain WebDAV in Hadoop?

WebDAV is set of extension to HTTP which used to support editing and uploading the files. On most operating system WebDAV shares can mounted as filesystems, so it is also possible to access HDFS as a standard filesystem by exposing HDFS over the WebDAV.

18) what is Sqoop in Hadoop?

Sqoop is a tool which is used to transfer data between the Relational Database Management System and Hadoop HDFS. Using Sqoop, one can transfer data from RDBMS like MySQL or Oracle into HDFS as well as exporting data from HDFS file to RDBMS.

19)List functionalities of JobTracker?

This are the main tasks of JobTracker:

accepting jobs from the client.
communicating with the NameNode to determine the location of the data.
To locate TaskTracker Nodes with free slots.
To submit work to the chosen TaskTracker node and monitor progress of each task.

20) Use of TaskTracker.

TaskTracker is node in cluster that accepts jobs like MapReduce and Shuffle operations from JobTracker.

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HADOOP DEVELOPER JOBS AND COURSE DETAILS

What is HADOOP?

Hadoop is open-source frame work for storage and distributed processing of large datasets ,clusters of commodity hardware. It was developed by Apache Software Foundation and is designed to handle jobs like holding vast amounts of data, including structured and unstructured data, across a distributed computing environment.

Hadoop is particularly well-suited for big data tasks like processing and analytics checking.

The key responsibilities of a HADOOP DEVELOPER will be as follows:

1.Determine & Design Big Data solutions based on the requirements aligning with overall guiding principles of the project ecosystem
2.Develop solutions as the part of Scrum teams
3.Build optimized data model, pipelines in the MPP environment
4. Enhance or build data engineering assets using Hadoop

HADOOP DEVELOPER COURSE INCLUDES:

1.Knowledge of designing principles and fundamentals of architecture
2.Understanding performanceof engineering
3.Knowledge on quality processes and estimation techniques
4.Basic understanding of the project domain
5.How to translate functional and nonfunctional requirements of systems requirements
6.How to design and perform code complex programs
7.How write test cases and scenarios based on specifications
8.Good understanding of the SDLC and agile methodologies
9.Awareness on latest technologies and trends
10.projects to improve Logical thinking and problem solving skills along with ability to collaborate
11.Brief Knowledge on Hadoop Cluster architecture and how to monitor cluster.
Is Hadoop good for Career?

If you are a fresher and wondering what career to choose to grow your career in databases, then Hadoop is the best option to choose.

CAREER IN HADOOP

If you are a fresher or experienced job seeker and wondering which career option to choose to grow your career in databases, then Hadoop is the best option to choose.

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Artificial Intelligence Interview Questions

LIST OF Artificial Intelligence Interview Questions

1.LIST Common Uses and Applications of Artificial Intelligence?

Possibilities include object detection,contract analysis and classification for navigation and avoidance , image recognition, content- distribution, predictive maintenance, data processing, automation of manual tasks, and data driven reporting.

2. What are the Intelligent Agents, and How They Used in AI?

Intelligent agents are the autonomous entities that uses sensor to know what is going on, and use actuators to perform their tasks/ goals. They can be simple , complex and can be programmed to learn and accomplish their jobs better.

3. What is meant by Tensorflow, and What is Tensorflow Used For?

Tensorflow is open-source software library was initially developed by Google Brain Team to use in neural networks research and machine learning . It is used for the data-flow programming. TensorFlow makes much easier to build the certain AI features into applications, including speech recognition and Natural language processing.

4. What is meant by Machine Learning, and How can It Relate to AI?

Machine learning is subset of AI. The idea is machines will “learn” and get better at the tasks over the time rather than having humans having to input parameters. Machine learning is practical application of AI.

5. What are the Neural Networks, and How Does they Relate to AI?

Neural networks are the class of machine learning algorithms. The neuron part of the neural is computational component, and network part is how the neurons are being connected. Neural networks pass the data among themselves, gathering more and more meaning as the data moves in along. Because networks are interconnected, more complex data can processed more efficiently.

6. What is Deep Learning, and How Does It Relate to AI?

Deep learning is subset of the machine learning. Refers to using multi-layered neural networks to process the data in increasingly sophisticated ways, enabling software to train itself to perform task like speech and image recognitions through the exposure to these vast amounts of data for continual improvement ability to recognize and process information. Layers of the neural networks stacked on the top of each for use in the deep learning are called deep neural networks.

7. Why Image Recognition is a Key Function of AI?

Humans are visual, and AI designed to emulate human brains. Teaching machines to recognize and categorize images is crucial part of AI. Image recognition also helps the machines to learn because the more images that are processed, are the better the software gets recognizing and processing those images.

8. What is meant by Automatic Programming?

Automatic programming describing what a program should do, and having the AI system “write” the program.

9. What is a Bayesian Network, and How Does Bayesian Relate to AI?

A Bayesian network is graphical model for the probabilistic relationships among a set of variables. It alsomimics the human brain in processing variables.

10. What are the Constraint Satisfaction Problems?

Constraint Satisfaction Problems (CSPs) are the mathematical problems defined as set of objects, the state which must meet several constraints. CSPs are mostuseful for AI because the regularity of their formulation offers commonality for analyzing and solving the problems.

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