Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15450
@sethah I should say I am not trying to handle cases where clusters start
separate and converge to nearly the same point. I don't that's something we
should even try to do.
To elaborate, here are the relevant cases, I think. I'm ignoring cases
where the data size is >> k because it all behaves as desired with high
probability already.
*Case 1*. Data = [A, B], k = 3, init = random
Now, you'll get 3 centroids and definitely have a duplicate. After this
change, you'd get 2.
*Case 2*. Data = [A, A, B, B], k = 3, init = random
Now, you'll get 3 centroids and definitely have a duplicate. After this
change, same thing.
*Case 3*. Data = [A, B, C, D], k = 3, init = random
Now, you'll get 3 centroids and occasionally have a duplicate. After, this
change, you'd get 3 distinct centroids always.
*Case 4*. Data = [A, B], k = 3, init = parallel
Now, you'll get 3 centroids and definitely have a duplicate. After this
change, you should get 2 if I read the code right (that it won't pick a
centroid at distance 0 from another).
*Case 5*. Data = [A, A, B, B], k = 3, init = parallel
Now, you'll get 3 centroids and definitely have a duplicate. After this
change, you should get 2 for the same reason above.
*Case 6*. Data = [A, B, C, D], k = 3, init = parallel
Now, you'll get 3 centroids and occasionally have a duplicate. After this
change, same thing.
Case 1/4/5 are, I think, positive changes. Case 3 seems like a clear win.
Case 2 could be made consistent with 1/4/5 easily, I suppose, by calling
`.distinct`. Case 6 is the interesting one -- can we make it manage to return 3
distinct centroids always because that's clearly possible? like case 3? I
punted on that though.
I think Derrick's case is like 2 or 5. There are duplicates in the data and
not many unique points. Filtering the duplicates early is a performance win. At
least -- that is the case I am trying to solve. If that's not what is described
in the JIRA then I think it's a different issue or question.
I think there's a benefit to speed and meaningfulness of the model in case
1/2/4/5.
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