Answer / Sandhi Goel

Apache Spark has several advantages over Hadoop MapReduce in terms of performance and ease-of-use:nn1. Speed: Apache Spark is significantly faster than Hadoop due to its in-memory caching, lazy evaluation of intermediate results, and efficient task scheduling.nn2. Simplicity: Apache Spark has a simpler programming API than Hadoop, which makes it easier for developers to write and maintain applications.nn3. Flexibility: Apache Spark can handle a wider variety of workloads than Hadoop, including machine learning, graph processing, and streaming data processing.nn4. Real-time processing: Apache Spark can process streaming data in real-time, while Hadoop is primarily designed for batch processing.

What is aws spark?

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What is meant by Transformation? Give some examples.

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Define RDD?

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What is in memory processing in spark?

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What happens to rdd when one of the nodes on which it is distributed goes down?

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Do I need to know hadoop to learn spark?

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Which storage level does the cache () function use?

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Explain foreach() operation in apache spark?

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Compare Transformation and Action in Apache Spark?

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Can you explain accumulators in apache spark?

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What is the difference between spark and python?

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What is the Difference SparkSession vs SparkContext in Apache Spark?

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