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