Hi all, We've had a relatively inactive year, but now we have three issues/pull requests that need to be reviewed. Once we merge them I think we can release a new version, which will support Spark all the way to Spark 3.4.x and bring us up to date with their releases. I'm writing a short description here - anyone who can, please review them. If you don't have time for an in-depth code review, checking the interface/documentation of the two new methods is also important.
The issues are: DATAFU-176 <https://issues.apache.org/jira/browse/DATAFU-176> - do dedupTopN with combiner. This is like our dedupTopN, but uses the combiner to deal with extreme skew efficiently. A use case that came up at PayPal. DATAFU-177 <https://issues.apache.org/jira/browse/DATAFU-177>- Add dedupByAllExcept. This method is for deduplicating otherwise identical rows with differing ids. Also a use case that came up at PayPal. DATAFU-179 <https://issues.apache.org/jira/browse/DATAFU-179> - support Spark 3.3.x and 3.4.x. Self-explanatory. I did this one, and it didn't take much, but I'd be glad for some good double-checking. A note to interested non-committers - *we welcome your review and comments*! Feel free to write in either the Jira issues or the Github PRs. Cheers, Eyal
