Understood, I was looking for a way to define these metrics that is attainable
for non-programmers to develop.
Thank you for the answer Seth
Pedro
> On 15 Sep 2021, at 18:38, Seth Wiesman wrote:
>
>
> Honestly, I don't think you need CEP or MATCH_RECOGNIZE for that use case. It
> can be s
Honestly, I don't think you need CEP or MATCH_RECOGNIZE for that use case.
It can be solved with a simple process function that tracks the state for
each id. Output a 1 when a job completes and a -1 if canceled. Output the
sum. You can use a simple timer to clear the state for a job after 6 months
Hello,
As anyone used streaming sql pattern matching as shown in this email thread to
count certain transitions on a stream?
Is it feasible?
Thank you,
Pedro Silva
> On 13 Sep 2021, at 11:16, Pedro Silva wrote:
>
>
> Hello Seth,
>
> Thank you very much for your reply. I've taken a look at
Hello Seth,
Thank you very much for your reply. I've taken a look at MATCH_RECOGNIZE
but I have the following doubt. Can I implement a state machine that detect
patterns with multiple end states?
To give you a concrete example:
I'm trying to count the number of *Jobs* that have been *cancelled* a
Hi Pedro,
The DataStream CEP library is not available in Python but you can use
`MATCH_RECOGNIZE` in the table API which is implemented on-top of the CEP
library from Python.
https://nightlies.apache.org/flink/flink-docs-release-1.13/docs/dev/table/sql/queries/match_recognize/
Seth
On Fri, Sep
