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https://issues.apache.org/jira/browse/SPARK-18321?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15648529#comment-15648529
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Seth Hendrickson commented on SPARK-18321:
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I've taken a look at the new LSH additions as well as the clustering summaries
which were both added since 2.0. They seem ok.
I'd appreciate some guidance: is the main item here to comb through API docs
for Java and see that type signatures check out, as well as matching Java and
Scala APIs? What other tools are there?
> ML 2.1 QA: API: Java compatibility, docs
> ----------------------------------------
>
> Key: SPARK-18321
> URL: https://issues.apache.org/jira/browse/SPARK-18321
> Project: Spark
> Issue Type: Sub-task
> Components: Documentation, Java API, ML, MLlib
> Reporter: Joseph K. Bradley
> Priority: Blocker
>
> Check Java compatibility for this release:
> * APIs in {{spark.ml}}
> * New APIs in {{spark.mllib}} (There should be few, if any.)
> Checking compatibility means:
> * comparing with the Scala doc
> * verifying that Java docs are not messed up by Scala type incompatibilities.
> Some items to look out for are:
> ** Check for generic "Object" types where Java cannot understand complex
> Scala types.
> *** *Note*: The Java docs do not always match the bytecode. If you find a
> problem, please verify it using {{javap}}.
> ** Check Scala objects (especially with nesting!) carefully.
> ** Check for uses of Scala and Java enumerations, which can show up oddly in
> the other language's doc.
> * If needed for complex issues, create small Java unit tests which execute
> each method. (The correctness can be checked in Scala.)
> If you find issues, please comment here, or for larger items, create separate
> JIRAs and link here as "requires".
> * Remember that we should not break APIs from previous releases. If you find
> a problem, check if it was introduced in this Spark release (in which case we
> can fix it) or in a previous one (in which case we can create a java-friendly
> version of the API).
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