Answer / Apurav Garg

Apache Spark achieves fault tolerance by storing multiple copies of the same data across different nodes in a cluster. When a task fails, it can be re-executed on another node that has a copy of the data. Additionally, Spark maintains lineage information, allowing it to recalculate dependencies if needed.

What do you understand by worker node?

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How do I download spark?

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What are the downsides of Spark?

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What is the spark driver?

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Explain the action count() in Spark RDD?

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How is streaming implemented in spark?

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What is the default partition in spark?

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Is apache spark an etl tool?

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How can you trigger automatic clean-ups in Spark to handle accumulated metadata?

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Why is Transformation lazy in Spark?

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Compare Transformation and Action in Apache Spark?

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

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