Hi Jan! One could implement the RocksDB ListState like you suggested.
We did it the current way because that pattern is actually quite efficient if you list fits into memory - The list append is constant and the list access is the first time the values are concatenated. Especially for typical windowing patterns (frequent append(), occasional get()) this works quite well. It falls short when the lists get too large, that is correct. To break it into individual elements means to have a range iterator for list.get() access which I think is a bit more costly. It also needs a nifty way to add a 'position' number into the key to make sure the list remains ordered, and to not have to have extra read-modify-write state every time this number is updated. But all in all, it should be possible. Are you interested in working on something like that and contributing it? Best, Stephan On Wed, Dec 13, 2017 at 2:22 PM, Aljoscha Krettek <aljos...@apache.org> wrote: > 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-01530 > 744/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 > >>>> > >>>> > >> > > > >
