Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/2622#issuecomment-58091578
@rezazadeh Could you update the example using `scopt` to parse parameters?
You can check other example code for its usage. We try to be consistent across
example code. It should take `--threshold` as a required parameter. For the
evaluation, we can do it distributively, for example:
~~~
val MAE = exact.entries.map { case MatrixEntry(i, j, u) =>
((i, j), u)
}.leftOuterJoin(
approx.entries.map { case MatrixEntry(i, j, v) =>
((i, j), v)
}).values.map {
case (u, Some(v)) =>
math.abs(u - v)
case (u, None) =>
math.abs(u)
}.mean()
~~~
I use MAE here but I'm not sure which metric matches the theory.
Btw, I created a JIRA to have a specialized version of exact similarity
computation, which doesn't require sampling. Let me know if you are interested
working on it: https://issues.apache.org/jira/browse/SPARK-3820
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