Answer / Sumit Kumar Sharma

Apache Hadoop and Apache Spark are both open-source big data processing frameworks, but they have some key differences. Hadoop is a MapReduce-based framework used primarily for batch processing, while Spark offers faster in-memory data processing capabilities for both batch and real-time data processing tasks. Spark also has built-in support for stream processing (Spark Streaming) and machine learning (MLlib), whereas Hadoop requires additional libraries to perform these functions.

What are configuration files in Hadoop?

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Can you define a checkpoint?

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What mode(s) can hadoop code be run in?

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Can we deploye job tracker other than name node?

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Explain the common input formats in hadoop?

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What do you know about yarn?

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

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Why do the nodes are removed and added frequently in a hadoop cluster?

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How analysis of Big Data is useful for organizations?

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How can one check whether NameNode is working or not?

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Whats the default port that jobtrackers listens ?

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What is the command to change the replication factor ?

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