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Explain how can you minimize data transfers when working with spark?

Answer Posted / Amit Katiyar

Minimizing data transfers in Apache Spark can be achieved by several methods: caching RDDs that are used multiple times, using repartitioning techniques like coalesce() to reduce the number of partitions and therefore the amount of shuffle operations, and using sort-merge join instead of broadcast join when possible.

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