Re: Configure operator based on key

You can self-define it using keyedStream.window(GlobalWindows.create() ).trigger(self-defined-trigger). Abhinav Sharma 于2021年2月21日周日 下午3:57写道： > Hi, > > Is there some way that I can configure an operator based on the key in a > stream? > Eg: If the key is 'abcd', then create a window of size X c

Re: Run the code in the UI

Hi, Could you re-elaborate what exactly you mean? If you wish to run a Flink job within the IDE, but also have the web UI running for it, you can use `StreamExecutionEnvironment.createLocalEnvironmentWithWebUI(Configuration)` to create the execution environment. The default port 8081 will be used

Re: [Statefun] Dynamic behavior

Hi, FWIW, there is this JIRA that is tracking a pubsub / broadcast messaging primitive in StateFun: https://issues.apache.org/jira/browse/FLINK-16319 This is probably what you are looking for. And I do agree, in the case that the control stream (which updates the application logic) is high volume

[Statefun] Dynamic behavior

Hi everyone, What is the recommended way of achieving the equivalent of a broadcast in Flink when using Stateful Functions? For instance, assume we are implementing something similar to Flink's demo fraud detection but in Stat

Union fields with time attributes have different types

I'm using a query like this WITH aggs_1m AS ( SELECT `evt`, `startts` `endts`, SUM(`value`) AS `value` FROM aggregates_per_minute ), aggs_3m AS ( SELECT `evt`, TUMBLE_START(`endts`, INTERVAL '3' MINUTE) AS `startts`, TUMBLE_END(`endts`, INTERVAL '3' MINUTE) AS `en

Datastream Lag Windowing function

Hi All, I am using Flink1.12, I am trying to read realtime data from Kafka topic and as per the requirement I need to implement windowing LAG function. Approach I followed is below: DataStream vData = env.addSource(...)vData.keyBy(Id) createTemperoryViewthen apply flink sql. My sample data is lik