Hi Florian, The memory usage depends on the types of keys and namespaces.
We have not experienced that many concurrently open windows. But given that each open window needs several bytes for its timer, 2M open windows may cost up to hundreds of MB. Regards Xiaogang 2017-01-18 14:45 GMT+08:00 Florian König <florian.koe...@micardo.com>: > Hi, > > that sounds very useful. We are using quite a lot of timers in custom > windows. Does anybody have experience with the memory requirements of, > let’s say, 2 million concurrently open windows and the associated timers? > > Thanks > Florian > > > Am 18.01.2017 um 04:40 schrieb Xiaogang Shi (JIRA) <j...@apache.org>: > > > > Xiaogang Shi created FLINK-5544: > > ----------------------------------- > > > > Summary: Implement Internal Timer Service in RocksDB > > Key: FLINK-5544 > > URL: https://issues.apache.org/jira/browse/FLINK-5544 > > Project: Flink > > Issue Type: Bug > > Components: Streaming > > Reporter: 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 > > (v6.3.4#6332) > > >
