Answer / Aarti Martolia

Apache Spark is used for big data processing and analysis. It can handle various tasks such as batch processing, real-time stream processing, machine learning, and graph processing. Some common use cases include data transformation, ETL (Extract, Transform, Load) operations, anomaly detection, recommendation systems, fraud detection, and more.

Explain benefits of lazy evaluation in RDD in Apache Spark?

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What is executor in spark?

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Explain about the common workflow of a Spark program?

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What is transformation in spark?

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What is the difference between spark and scala?

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What are transformations in spark?

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Why do we use persist () on links rdd?

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On which all platform can Apache Spark run?

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How does yarn work with spark?

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Does spark use yarn?

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Is spark built on top of hadoop?

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Different Running Modes of Apache Spark

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