jessiedanwang opened a new issue, #7030: URL: https://github.com/apache/iceberg/issues/7030
### Query engine spark on EMR ### Question We have a spark structured streaming application, streaming data into iceberg tables in AWS, using Glue catalog. Currently, we stop the streaming query every n batches to do compaction and snapshot expiration using spark actions, and restart streaming query after maintenance job are done. The other option is to run a separate spark application that periodically does iceberg table maintenance tasks, while running the streaming application at the same time. The 3rd option is run optimize and vacuum in Athena to do iceberg table maintenance. I am wondering if there is any big difference in terms of performance in the above ways, and what's the recommended way of doing table maintenance. Thanks. -- 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] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
