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ASF GitHub Bot commented on FLINK-5544: --------------------------------------- Github user StefanRRichter commented on the issue: https://github.com/apache/flink/pull/3359 One additional comment, also as reminder for @aljoscha and me: after this PR is rebased, we have access to `InternalKeyContext`, which should be somehow integrated with the already existing `KeyContext` interface. This would reduce several constructor parameters and some members, e.g. the `KeyGroupRange`s and `TypeSerializer<K>`s. > Implement Internal Timer Service in RocksDB > ------------------------------------------- > > Key: FLINK-5544 > URL: https://issues.apache.org/jira/browse/FLINK-5544 > Project: Flink > Issue Type: New Feature > Components: State Backends, Checkpointing > Reporter: Xiaogang Shi > Assignee: Xiaogang Shi > > Now the only implementation of internal timer service is > HeapInternalTimerService which stores all timers in memory. In the cases > where the number of keys is very large, the timer service will cost too much > memory. A implementation which stores timers in RocksDB seems good to deal > with these cases. > It might be a little challenging to implement a RocksDB timer service because > the timers are accessed in different ways. When timers are triggered, we need > to access timers in the order of timestamp. But when performing checkpoints, > we must have a method to obtain all timers of a given key group. > A good implementation, as suggested by [~StephanEwen], follows the idea of > merge sorting. We can store timers in RocksDB with the format > {{KEY_GROUP#TIMER#KEY}}. In this way, the timers under a key group are put > together and are sorted. > Then we can deploy an in-memory heap which keeps the first timer of each key > group to get the next timer to trigger. When a key group's first timer is > updated, we can efficiently update the heap. -- This message was sent by Atlassian JIRA (v6.3.15#6346)