[ https://issues.apache.org/jira/browse/SPARK-20504?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-20504: -------------------------------------- Fix Version/s: (was: 2.1.0) > ML 2.2 QA: API: Java compatibility, docs > ---------------------------------------- > > Key: SPARK-20504 > URL: https://issues.apache.org/jira/browse/SPARK-20504 > Project: Spark > Issue Type: Sub-task > Components: Documentation, Java API, ML, MLlib > Reporter: Joseph K. Bradley > Assignee: Seth Hendrickson > 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: > * 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! -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org