Hi, If I remember correctly, there was actually an effort to change the RocksDB list state the way you described. I'm cc'ing Stephan, who was involved in that and this is the Jira issue: https://issues.apache.org/jira/browse/FLINK-5756 <https://issues.apache.org/jira/browse/FLINK-5756>
Best, Aljoscha > On 12. Dec 2017, at 14:47, Ovidiu-Cristian MARCU > <ovidiu-cristian.ma...@inria.fr> wrote: > > Hi Jan, > > You could associate a key to each element of your Key's list (e.g., hashing > the value), keep only the keys in heap (e.g., in a list) and the associated > state key-value/s in an external store like RocksDB/Redis, but you will > notice large overheads due to de/serializing - a huge penatly for more than > 1000s of elements (see https://hal.inria.fr/hal-01530744/document > <https://hal.inria.fr/hal-01530744/document> for some experimental settings) > for relatively small rate of new events per Key, if needed to process all > values of a Key for each new event. Best case you can do some incremental > processing unless your non-combining means non-associative operations per Key. > > Best, > Ovidiu >> On 12 Dec 2017, at 11:54, Jan Lukavský <je...@seznam.cz> wrote: >> >> Hi Fabian, >> >> thanks for quick reply, what you suggest seems to work at first sight, I >> will try it. Is there any reason not to implement a RocksDBListState this >> way in general? Is there any increased overhead of this approach? >> >> Thanks, >> >> Jan >> >> >> On 12/12/2017 11:17 AM, Fabian Hueske wrote: >>> Hi Jan, >>> >>> I cannot comment on the internal design, but you could put the data into a >>> RocksDBStateBackend MapState<Integer, X> where the value X is your data >>> type and the key is the list index. You would need another ValueState for >>> the current number of elements that you put into the MapState. >>> A MapState allows to fetch and traverse the key, value, or entry set of the >>> Map without loading it completely into memory. >>> The sets are traversed in sort order of the key, so should be in insertion >>> order (given that you properly increment the list index). >>> >>> Best, Fabian >>> >>> 2017-12-12 10:23 GMT+01:00 Jan Lukavský <je...@seznam.cz>: >>> >>>> Hi all, >>>> >>>> I have a question that appears as a user@ question, but brought me into >>>> the dev@ mailing list while I was browsing through the Flink's source >>>> codes. First I'll try to briefly describe my use case. I'm trying to do a >>>> group-by-key operation with a limited number of distinct keys (which I >>>> cannot control), but a non trivial count of values. The operation in the >>>> GBK is non-combining, so that all values per key (many) have to be stored >>>> in a state. Running this on testing data led to a surprise (for me), that >>>> even when using RocksDBStateBackend, the whole list of data is serialized >>>> into single binary blob and then deserialized into List, and therefore has >>>> to fit in memory (multiple times, in fact). >>>> >>>> I tried to create an alternative RocksDBStateBackend, that would store >>>> each element of list in ListState to a separate key in RocksDB, so that the >>>> whole blob would not have to be loaded by a single get, but a scan over >>>> multiple keys could be made. Digging into the source code I found there was >>>> a hierarchy of classes mirroring the public API in 'internal' package - >>>> InternalKvState, InternalMergingState, InternalListState, and so on. These >>>> classes however have different hierarchy than the public API classes that >>>> they mirror, most notably InternalKvState is superinterface of all others. >>>> This fact seems to be used on multiple places throughout the source code. >>>> >>>> My question is - is this intentional? Would it be possible to store each >>>> element of a ListState in a separate key in RocksDB (probably by adding >>>> some suffix to the actual key of the state for each element)? What are the >>>> pitfalls? And is it necessary for the InternalListState to be actually >>>> subinterface of InternalKvState? I find this to be a related problem. >>>> >>>> Many thanks for any comments or thoughts, >>>> >>>> Jan >>>> >>>> >> >
