Hi Juho,
As Aljoscha mentioned the current TTL implementation was mostly targeted to
data privacy applications
where only processing time matters.
I think the event time can be also useful for TTL and should address your
concerns.
The event time extension is on the road map for the future
Hi Juho,
The main motivation for the initial implementation of TTL was compliance with
new GDPR rules. I.e. data cannot be accessible and must be dropped according to
time in the real world, i.e. processing time. The behaviour you describe, with
data being dropped if you keep a savepoint for
Just a quick note for the docs:
https://ci.apache.org/projects/flink/flink-docs-release-1.6/dev/stream/state/state.html#state-time-to-live-ttl
On 22.08.2018 10:53, Juho Autio wrote:
First, I couldn't find anything about State TTL in Flink docs, is
there anything like that? I can manage based
First, I couldn't find anything about State TTL in Flink docs, is there
anything like that? I can manage based on Javadocs & source code, but just
wondering.
Then to main main question, why doesn't the TTL support event time, and is
there any sensible use case for the TTL if the streaming
