What happens if I cache the same RDD twice in Spark

Question

I\'m building a generic function which receives a RDD and does some calculations on it. Since I run more than one calculation on the input RDD I would like to cache it. For

Answer 1

Nothing. If you call cache on a cached RDD, nothing happens, RDD will be cached (once). Caching, like many other transformations, is lazy:

• When you call cache, the RDD's storageLevel is set to MEMORY_ONLY
• When you call cache again, it's set to the same value (no change)
• Upon evaluation, when underlying RDD is materialized, Spark will check the RDD's storageLevel and if it requires caching, it will cache it.

So you're safe.