Hi all, Is there a way to do this? I am new to Flink, appreciate any feedback and suggestions. Thanks Anna |
Hi anna, > I need to trigger a function once every day If you want to trigger by the function itself, you can use the Timer[1]. Both types of timers (processing-time and event-time) are internally maintained by the TimerService, and onTimer() method will be called once a timer fires. If you want to trigger the function of different parallelism synchronously, then the broadcast state[2] may be helpful. Hope this helps. Hequn On Tue, Jul 10, 2018 at 7:47 AM, anna stax <[hidden email]> wrote:
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Thanks Hequn, for the links. This is my use case.. When there is no user activity for n weeks, I need to send a Notification to user. The activity stream is usually very high volume for most users. I thought it is not a good idea to use windowing for this, because of the stream volume and window size. I want to store in the state, for every user the last activity date and process them once daily. I want to make sure I am heading in the right direction. Thank you for your suggestions. -Anna On Mon, Jul 9, 2018 at 7:16 PM, Hequn Cheng <[hidden email]> wrote:
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Hi anna, According to your description, I think we can use the Timer to solve your problem. The TimerService deduplicates timers per key and timestamp. Also, note that a large number of timers can significantly increase checkpointing time. On Tue, Jul 10, 2018 at 11:38 AM, anna stax <[hidden email]> wrote:
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Thanks Hequn. I think so too, the large number of timers could be a problem. On Mon, Jul 9, 2018 at 10:23 PM, Hequn Cheng <[hidden email]> wrote:
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Hi, It depends on how many different users. In most cases, the performance will be fine. I think it worth to give a try. :-)Of course, there are ways to reduce the number of timers, for example keyBy(userId%1024), and use a MapState to store different users for the same group. On Tue, Jul 10, 2018 at 1:54 PM, anna stax <[hidden email]> wrote:
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sure. I will go ahead with this for now. Thanks for your suggestions. On Mon, Jul 9, 2018 at 11:10 PM, Hequn Cheng <[hidden email]> wrote:
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