Answer / Manu Devi

"Apache Spark is generally faster than Apache Hadoop MapReduce due to several reasons:-
1. In-memory processing: Spark keeps intermediate results in memory, reducing the number of disk operations compared to Hadoop.
2. Faster task execution: Spark can execute tasks much more quickly due to its support for parallel computation and in-built optimizations such as lazy evaluation and lineage storage.
3. Better fault tolerance: Spark provides faster recovery from failures because it stores enough information about each task to recalculate intermediate results, reducing the need for data retransmission.
4. Simpler API: Spark has a simpler and more flexible API compared to Hadoop, making it easier to write and optimize distributed applications."

Is it possible to run Spark and Mesos along with Hadoop?

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What are the limitations of Spark?

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Why lazy evaluation is good in spark?

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Describe different transformations in dstream in apache spark streaming?

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Why do we need spark?

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What is dag – directed acyclic graph?

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What is the difference between Spark Transform in DStream and map ?

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What is skew data?

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What does rdd stand for?

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