What happens if I cache the same RDD twice in Spark

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 example:

public JavaRDD<String> foo(JavaRDD<String> r) {
    r.cache();
    JavaRDD t1 = r... //Some calculations
    JavaRDD t2 = r... //Other calculations
    return t1.union(t2);
}

My question is, since r is given to me it may or may not already be cached. If it is cached and I call cache on it again, will spark create a new layer of cache meaning that while t1 and t2 are calculated I will have two instances of r in the cache? or will spark is aware of the fact that r is cached and will ignore it?