Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75123777
If we return a `JavaPairRDD`, the user code looks like the following:
~~~
for (Tuple2Long, Int assignment: assignments.collect()) {
... assignment._1()
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75121366
For PIC, the names Assignment / id / cluster sound good to me. Those would
be applicable to other clustering methods if ever needed. Assignment is a
little generic,
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75125808
LGTM except for that one comment
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Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4695#discussion_r25020128
--- Diff: docs/mllib-frequent-pattern-mining.md ---
@@ -74,11 +74,12 @@ Calling `FPGrowth.run` with transactions returns an
that stores the frequent
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75125659
Yeah, after reading the code, I like the special classes since the field
names make the code more legible.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75126769
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75178074
Merged into master and branch-1.3.
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Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/4695
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GitHub user mengxr opened a pull request:
https://github.com/apache/spark/pull/4695
[SPARK-5900][MLLIB] make PIC and FPGrowth Java-friendly
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mengxr/spark SPARK-5900
Alternatively
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75101083
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Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/4695#issuecomment-75167973
I missed those issues before! LGTM pending tests
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