Hi I am working on a use case where I want to start a timer for a given event type and when that timer expires it will perform certain action. This can be done using Process Function. But I also want to cancel scheduled timer in case of some other types of events. I also checked the implementation of HeapInternalTimerService which implements InternalTimerService interface has those implementations already. Also SimpleTimerService which overrides TimerService also uses InternalTimerService and simply passes VoidNamespace.INSTANCE. So in a way we are using InternalTimerService interface's implementations everywhere. So what is the reason that ProcessFunction.Context uses TimerService? Any reason 'deleteEventTimeTimer' is not exposed to users? If I want to use the deleteEvent functionality how should I go about it? Thanks and Regards, Jagadish Bihani |
Hi,
the reasoning behind the limited user facing API was that we were (are) not sure whether we would be able to support efficient deletion of timers for different ways of storing timers. @Stephan, If I remember correctly you were the strongest advocate for not allowing timer deletion. What’s your thinking on this? There was also a quick discussion on https://issues.apache.org/jira/browse/FLINK-3089 where Xiaogang explained that the (new, not merged) RocksDB based timers would have efficient timer deletion. Best, Aljoscha
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Hi!
I thought I would drop my opinion here maybe it is relevant. We have used the Flink internal timer implementation in many of our production applications, this supports the Timer deletion but the deletion actually turned out to be a huge performance bottleneck because of the bad deletion performance of the Priority queue. In many of our cases deletion could have been avoided by some more clever registration/firing logic and we also ended up completely avoiding deletion and instead using "tombstone" markers by setting a flag in the state which timers not to fire when they actually trigger. Gyula Aljoscha Krettek <[hidden email]> ezt írta (időpont: 2017. ápr. 21., P, 14:47):
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A bit curious: wouldn't using "tombstone" markers constitute some memory leak (since Timers are not released) ? Cheers On Fri, Apr 21, 2017 at 12:23 PM, Gyula Fóra <[hidden email]> wrote:
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The timer will actually fire and will be removed at the original time, but we don't trigger any action on it. We also remove the tombstone state afterwards. So we use more memory yes depending on the length and number of timers that were deleted. But it is eventually cleaned up. Gyula Ted Yu <[hidden email]> ezt írta (időpont: 2017. ápr. 21., P, 21:38):
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Benjamin has an implementation for Hierarchical Timing Wheels (Apache License) : If there is some interest, we can port the above over. Cheers On Fri, Apr 21, 2017 at 12:44 PM, Gyula Fóra <[hidden email]> wrote:
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Hi, I am not familiar with this data structure, I will try to read up on it. But it looks interesting. For some reference, some links: https://www.confluent.io/blog/apache-kafka-purgatory-hierarchical-timing-wheels/ http://www.cs.columbia.edu/~nahum/w6998/papers/sosp87-timing-wheels.pdf Cheers, On Sat, Apr 22, 2017, 00:35 Ted Yu <[hidden email]> wrote:
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Logged FLINK-6359, referring to this thread. FYI On Sat, Apr 22, 2017 at 1:10 AM, Gyula Fóra <[hidden email]> wrote:
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Here are the thoughts why I advocated to not expose the "delete" initially: (1) The original heap timer structure was not very sophisticated and could not support efficient timer deletion (as Gyula indicated). As a core rule in large scale systems: Never expose an operation you cannot do efficiently, hence there should be no delete operation until there is a better heap timer structure. (2) In general, we need timers to be able to go out-of core as well (there may be many many timers in certain cases). That's why we picked a RocksDB Timer Service for the large scale timers. (3) An additional challenge is that timers are per key and need to be stored in a key-partitioned fashion on checkpoint. Any implementation needs to handle that as well (so we probably need an extension of the classical time wheel structures) If all this is solved and supports efficient deletes, then we can add that operation again, in my opinion. On Sat, Apr 22, 2017 at 4:43 PM, Ted Yu <[hidden email]> wrote:
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In reply to this post by Ted Yu
Hi
Thanks for the multiple responses on this question. Please correct me if I am wrong about the 3 possible ways of it: 1. As per FLINK-3089, RocksDB based timer implementation is efficient. But it is not merged yet. Which release this will be part of? 2. FLINK-6359 suggests alternate approach based using Hierarchical timing wheels. 3. We can use state to indicate whether to trigger or not but timer will fire in all the cases. So this is not actually a cancellation of timer. In our use case we have ~ 1000 events per sec. But number of cancellations done will be much more. (i.e. as per the business logic, number of timers which will need to be cancelled are more say 70%), so solution 3 can be inefficient and a bit of wastage of resources. So, Could you please recommend how should I go about it? -- Which release item 1 or item 3 can be part of? -- About the existing implementation, are there any approximate data points about how slow deletion is? (if RPS is 1000 and assuming any standard AWS instance type.) I can derive from that and decide based on data that to go with cancellations or not. On Sat, Apr 22, 2017 at 8:13 PM, Ted Yu <[hidden email]> wrote:
Thanks and Regards, Jagadish Bihani |
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