Hi Marlo, One of the scenarios that we're trying to improve is to add or remove one field in state serializer. Users might add or remove one field during their schema evolution, state processor could help it with another offline job while state migration could help it once we restart the new job.
Best Yun Tang ________________________________ From: Marlo Ploemen <marlo.ploe...@icloud.com.INVALID> Sent: Wednesday, June 9, 2021 15:57 To: dev@flink.apache.org <dev@flink.apache.org> Subject: State migration scenario's Hi community, I am looking into the data migration and schema evolution process for stateful streaming jobs. Currently, there is no orchestration support for performing these job evolutions and no in-job state migration or schema evolution syntax (as this is part of the separate state processor API). I am looking for examples (e.g. Github repositories) or scenarios of stateful streaming jobs where the orchestration of their state evolution process can improve development quality. Best, Marlo
