Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/3193#issuecomment-63019228
@davies Did you only measure the `rdd.sample(...).count()`? Sampling 1
million took about 0.6s without replacement and 2.5s with replacement on my
computer. I think we use the same macbook model or yours is better:)
Maybe part of the time in your case was spent on broadcasting the rdd.
Could you try the following:
~~~
from pyspark.mllib.random import RandomRDDs
rdd = RandomRDDs.uniformRDD(sc, 1 << 20, 1).cache()
rdd.count()
rdd.sample(True, 0.9).count()
~~~
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