Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/18748
I don't get similar results to you (granted I have just tested locally).
```
scala> spark.time { userRecsAll.foreach(_ => Unit) }
Time taken: 122422 ms
scala> spark.time { userRecsPart.foreach(_ => Unit) }
Time taken: 50228 ms
```
Here, `userRecsPart` is a 30% sample, and the time is ~40% of the
`recommendForAllUsers` time. I will try some larger-scale tests. It could be
that the `join` and `distinct` causes the underperformance.
However, those operations would increase the number of partitions in the
computation a lot due to `spark.sql.shuffle.partitions` setting if using
defaults. Setting this to say `8` (the number of threads I have locally), I get
```
scala> spark.time { userRecsPart.foreach(_ => Unit) }
Time taken: 37362 ms
```
So, about 30% of the full time for the 30% sample.
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