Answer / Jitendra Verma

The core components of a distributed Spark application are: 1) SparkContext (an entry point to the Spark cluster, handling resource allocation and job scheduling); 2) RDDs (Resilient Distributed Datasets, immutable collections of data that can be processed in parallel); 3) Transformations (methods for creating new RDDs from existing ones); 4) Actions (methods that return a value or perform side effects, triggering the execution of all transformations up to that point).

Explain the key features of Spark.

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Explain the RDD properties?

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Write the command to start and stop the spark in an interactive shell?

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How many ways we can create rdd in spark?

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Do I need scala for spark?

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Define Partition and Partitioner in Apache Spark?

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Does spark use java?

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Explain coalesce operation in Apache Spark?

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What are broadcast variables in Apache Spark? Why do we need them?

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Is spark difficult to learn?

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Define Spark Streaming.

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What is flatmap?

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