Hi Bryan,

Thanks for the interest! Unfortunately there's lack of support on committers for SPARK-28190 (I have been struggling with lack of support on structured streaming contributions). I hope things will get better, but in the meantime, could you please try out my own project instead?

https://github.com/HeartSaVioR/spark-state-tools

It's not super convenient to use as of now, as structured streaming doesn't store schema for state. The schema should be provided manually, or from actual query. The improvement is being proposed via SPARK-27237 but this is also no activity right now due to lack of support as well.

Thanks,
Jungtaek Lim (HeartSaVioR)

On Tue, Mar 31, 2020 at 4:50 AM Bryan Jeffrey <bryan.jeffrey@gmail.com> wrote:
Hi, Jungtaek.

We've been investigating the use of Spark Structured Streaming to replace our Spark Streaming operations.  We have several cases where we're using mapWithState to maintain state across batches, often with high volumes of data.  We took a look at the Structured Streaming stateful processing.  Structured Streaming state processing looks great, but has some shortcomings:
1. State can only be hydrated from checkpoint, which means that modification of the state is not possible. 
2. You cannot cleanup or normalize state data after it has been processed.

These shortcomings appear to be potentially addressed by your ticket SPARK-28190 - "Data Source - State".  I see little activity on this ticket. Can you help me to understand where this feature currently stands?

Thank you,

Bryan Jeffrey