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Top 10 Hadoop interview Questions and Answers

Last updated on Tue 17 Mar 2020



1.What is Big Data?

Big data is a term for data sets that are so large or composite that conventional data processing applications are deficient. Challenges include analysis, capture, data curation, explore, sharing, storage, convey, visualization, enquire, modernize and information privacy.

2.What do the four V’s of Big Data denote? 

                  Volume –Scale of data

                  Velocity –Analysis of streaming data

                  Variety – Different forms of data

                  Veracity – trustworthiness of the data

  1. On what concept the Hadoop framework works?

             HDFS – HDFS hold very large amounts of data and provides uncomplicated access. To store such   vast data, the files are stored across multiple machines. These files are stored in redundant trend to save the system from possible data losses in case of failure. HDFS also makes applications accessible to parallel processing.

             Hadoop MapReduce-MapReduce is a computational paradigm designed to process very large sets of data in a  dispense trend. The MapReduce model was developed by Google to implement their search technology, specify the indexing of web pages. The model is found on the concept of breaking the data, organize task into two smaller tasks of mapping and reduction.

  1. What is Hadoop streaming?

Hadoop streaming is a utility that approach with the Hadoop distribution. This utility allows you to generate and run MapReduce jobs with any executable or script as the mapper and the reducer.

  1. What are real-time industrial applications of Hadoop?

Analyze life-threatening risks

Identify warning signs of security breaches

Prevent hardware failure

Understand what people think about your company

Understand when to sell certain products

Find your ideal prospects

Gain insight from your log files

  1. How is Hadoop dissimilar from other parallel computing systems?

Hadoop is a dispense file system, which lets you store and handle huge amount of data on a cloud of machines, handling data redundancy. Go through this HDFS content to know how the distributed file system works. The primary benefit is that since data is stored in some nodes, it is better to process it in dispensing manner. Each node can process the data stored on it instead of expend time in moving it over the network.

  1. What all modes Hadoop can be run in?

         Standalone Mode- Default mode of Hadoop

        Pseudo Distributed Mode (One Node Cluster) - Configuration is desired in given three files in this mode

        Fully distributed mode (or multiple node cluster)- This is a Production Stage.

  1. What are the most commonly defined input formats in Hadoop?

Text Input Format- This is the default input format describe in Hadoop.

Key Value Input Format- This input format is used for plain text files wherein the files are broken

Towards a lower position into lines.

Sequence File Input Format- This input format is used for reading files in order.

9.What is SequenceFile in Hadoop?

SequenceFile is a flat file consisting of binary key/value pairs. It is substantial used in MapReduce as input/output set out. It is also worth noting that, internally, the interim outputs of the maps are stored using SequenceFile.

  1. What is Job Tracker role in Hadoop?

The JobTracker is the favor within Hadoop that farms out MapReduce tasks to specific nodes in the cluster, preferably the nodes that have the data, or at least are in the identical rack. Client applications, submit jobs to the Job tracker.

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