[jira] [Comment Edited] (SPARK-30932) ML 3.0 QA: API: Java compatibility, docs

["zhengruifeng (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-30932?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17045168#comment-17045168 ] 

zhengruifeng edited comment on SPARK-30932 at 2/27/20 4:05 AM:
---------------------------------------------------------------

I check the output result and do not find outstanding issue, -except:-

-public method {{GeneralMLWriter#context}} was removed in Spark-25908 without deprecation.-

-{{GeneralMLWriter#context}}- was already deprecated in the doc, not a problem.


was (Author: podongfeng):
I check the output result and do not find outstanding issue, except:

public method \{{GeneralMLWriter#context}} was removed in Spark-25908 without deprecation.

> ML 3.0 QA: API: Java compatibility, docs
> ----------------------------------------
>
>                 Key: SPARK-30932
>                 URL: https://issues.apache.org/jira/browse/SPARK-30932
>             Project: Spark
>          Issue Type: Sub-task
>          Components: Documentation, ML, MLlib
>    Affects Versions: 3.0.0
>            Reporter: zhengruifeng
>            Priority: Major
>         Attachments: 1_process_script.sh, added_ml_class, common_ml_class, signature.diff
>
>
> Check Java compatibility for this release:
>  * APIs in {{spark.ml}}
>  * New APIs in {{spark.mllib}} (There should be few, if any.)
> Checking compatibility means:
>  * Checking for differences in how Scala and Java handle types. 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. These may not be understood in Java, or they may be accessible only via the weirdly named Java types (with "$" or "#") which are generated by the Scala compiler.
>  ** Check for uses of Scala and Java enumerations, which can show up oddly in the other language's doc. (In {{spark.ml}}, we have largely tried to avoid using enumerations, and have instead favored plain strings.)
>  * Check for differences in generated Scala vs Java docs. E.g., one past issue was that Javadocs did not respect Scala's package private modifier.
> 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).
>  * If needed for complex issues, create small Java unit tests which execute each method. (Algorithmic correctness can be checked in Scala.)
> Recommendations for how to complete this task:
>  * There are not great tools. In the past, this task has been done by:
>  ** Generating API docs
>  ** Building JAR and outputting the Java class signatures for MLlib
>  ** Manually inspecting and searching the docs and class signatures for issues
>  * If you do have ideas for better tooling, please say so we can make this task easier in the future!



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