Answer / Ravi Kumar Gupta

RDD supports various transformations (like map, filter, and join) and actions (like count, saveAsTextFile, and reduce). These operations can be chained together to create complex data processing pipelines.

Explain the action count() in Spark RDD?

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When should you use spark cache?

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What are the major features/characteristics of rdd (resilient distributed datasets)?

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Why scala is used in spark?

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State the difference between persist() and cache() functions.

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What is Spark MLlib?

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Why we need compression and what are the different compression format supported?

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What is a spark shuffle?

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Explain various Apache Spark ecosystem components. In which scenarios can we use these components?

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What are the various modes in which Spark runs on YARN? (Local vs Client vs Cluster Mode)

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What is Immutable?

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What is map in spark?

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