Answer / Parvez Khan

{"Cases": "1. Real-time data processing: Spark can process and analyze real-time data faster than Hadoop MapReduce due to its in-memory caching capabilities. 2. Iterative computations: Spark is more efficient for iterative tasks like machine learning algorithms as it avoids the overhead of disk read/write operations. 3. Graph processing: With GraphX, Spark can perform graph processing much faster than Hadoop."}

List the advantage of Parquet file in Apache Spark?

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Is apache spark a tool?

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Explain reduceByKey() Spark operation?

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What is Directed Acyclic Graph in Apache Spark?

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What are the limitations of Apache Spark?

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What is apache spark architecture?

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How is rdd distributed?

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What is spark architecture?

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What are broadcast variables in spark?

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Explain the difference between Spark SQL and Hive.

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What do you understand by Lazy Evaluation?

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Why is the spark so fast?

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