rdettai edited a comment on issue #962: URL: https://github.com/apache/arrow-datafusion/issues/962#issuecomment-909268730
As suggested by @Dandandan, we might also want to consider the fact that the statistics can be updated at runtime (like Spark AQE). In Ballista, an execution plan for a stage that takes a shuffle as input might be re-optimized according to the statistics of the shuffle boundary. For instance, this might change the optimal build/probe order of the tables for a join that has the shuffle boundary as one of its inputs. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
