[ 
https://issues.apache.org/jira/browse/SPARK-14810?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15280592#comment-15280592
 ] 

Nick Pentreath edited comment on SPARK-14810 at 5/20/16 1:00 PM:
-----------------------------------------------------------------

[~josephkb] [~mengxr] [~srowen] I've made a pass through this. I think I've 
audited all the excludes added to {{MimaExcludes}} (but will take another pass 
to double check). The majority of excludes added relate to (a) private classes 
/ methods; (b) @Experimental / DeveloperAPI (c) adding methods to sealed 
traits; and (d) the change {{DataFrame}} -> {{Dataset}}.

(d) is a binary incompatible change but affects Java for all of Spark (as we 
know). So I've not worried about that.

I will check SPARK-13920 again as it added a lot of excludes (most of them 
appear to be for {{DataFrame}} -> {{Dataset}} or private, and all @Experimental 
/ DeveloperAPI, but still good to know if anything did change).

So far the the 2 issues are removing deprecated methods:
* SPARK-14089 - 1.1-1.5
** {{BinaryClassificationEvaluator.setScoreCol}}
** {{LBFGS.setMaxNumIterations}} - DeveloperAPI
** {{RDDFunctions.treeReduce}} and {{treeAggregate}} - DeveloperAPI
** {{mllib.tree.Strategy.defaultStategy}} - appears to be a spelling error in 
the method.
** {{mllib.tree.Node.build}} 
** {{MLUtils}} libsvm loaders for multiclass and load/save labeledData methods
* SPARK-14952 - 1.6
** {{ml.LinearRegression.weights}} - @Experimental
** {{ml.LogisticRegression.weights}} - @Experimental

So these are incompatible changes, but I assume are ok. I'm just wondering how 
we prefer to document these changes? Migration guide, or somewhere else?


was (Author: mlnick):
[~josephkb] [~mengxr] [~srowen] I've made a pass through this. I think I've 
audited all the excludes added to {{MimaExcludes}} (but will take another pass 
to double check). The majority of excludes added relate to (a) private classes 
/ methods; (b) @Experimental / DeveloperAPI (c) adding methods to sealed 
traits; and (d) the change {{DataFrame}} -> {{Dataset}}.

(d) is a binary incompatible change but affects Java for all of Spark (as we 
know). So I've not worried about that.

I will check SPARK-13920 again as it added a lot of excludes (most of them 
appear to be for {{DataFrame}} -> {{Dataset}} or private, and all @Experimental 
/ DeveloperAPI, but still good to know if anything did change).

So far the the 2 issues are removing deprecated methods:
* SPARK-14089 - 1.1-1.5
** {{BinaryClassificationEvaluator.setScoreCol}}
** {{LBFGS.setMaxNumIterations}} - DeveloperAPI
** {{RDDFunctions.treeReduce}} and {{treeAggregate}} - DeveloperAPI
** {mllib.tree.Strategy.defaultStategy}} - appears to be a spelling error in 
the method.
** {{mllib.tree.Node.build}} 
** {{MLUtils}} libsvm loaders for multiclass and load/save labeledData methods
* SPARK-14952 - 1.6
** {{ml.LinearRegression.weights}} - @Experimental
** {{ml.LogisticRegression.weights}} - @Experimental

So these are incompatible changes, but I assume are ok. I'm just wondering how 
we prefer to document these changes? Migration guide, or somewhere else?

> ML, Graph 2.0 QA: API: Binary incompatible changes
> --------------------------------------------------
>
>                 Key: SPARK-14810
>                 URL: https://issues.apache.org/jira/browse/SPARK-14810
>             Project: Spark
>          Issue Type: Sub-task
>          Components: Documentation, GraphX, ML, MLlib
>            Reporter: Joseph K. Bradley
>            Assignee: Nick Pentreath
>
> Generate a list of binary incompatible changes using MiMa and create new 
> JIRAs for issues found. Filter out false positives as needed.
> If you want to take this task, look at the analogous task from the previous 
> release QA, and ping the Assignee for advice.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to