Answer / Dinesh Kumar Pandey

Hadoop's key features and characteristics that make it a popular and powerful big data processing tool include: (1) Scalability: Hadoop can handle petabytes of data and scale out to thousands of nodes. (2) Fault Tolerance: Hadoop is designed to withstand hardware failures, ensuring high availability and reliability of data. (3) Data Processing Flexibility: Hadoop supports a wide range of data processing tasks through its MapReduce and Hive APIs. (4) Open Source: Hadoop's open-source nature encourages innovation and collaboration among developers and users, fostering rapid development and adoption.

Have you ever used counters in hadoop?

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Which are the three modes in which hadoop can be run?

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Is Namenode machine same as DataNode machine as in terms of hardware in Hadoop?

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What do you know about the speculative execution?

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Clarify what webdav is in hadoop?

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Are there any special requirements for namenode?

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What happens if the number of reducers is 0 in Hadoop?

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How to restart NameNode or all the daemons in Hadoop?

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What is Chain Mapper?

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What are some of the characteristics of Hadoop framework?

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When should be hadoop archive create?

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How namenode handles data node failures?

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