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From Nam-Luc Tran <namluc.t...@euranova.eu>
Subject Re: Streaming KV store abstraction
Date Fri, 18 Mar 2016 17:24:47 GMT
Hi Gyula,

I'm currently looking after ways to enrich streams with external data. Have
you got any update on the topic in general or on StreamKV?

I've checked out the code but it won't build, mainly because
StateCheckpointer has been removed since [FLINK-2808]. Any hint on a quick
replacement, before I dive in deeper?

Cheers,

2015-09-15 20:29 GMT+02:00 Stephan Ewen <sewen@apache.org>:

> I think that is actually a cool way to kick of an addition to the system.
> Gives you a lot of flexibility and releasing and testing...
>
> It helps, though, to upload maven artifacts for it!
>
> On Tue, Sep 15, 2015 at 7:18 PM, Gyula Fóra <gyfora@apache.org> wrote:
>
> > Hey All,
> >
> > We decided to make this a standalone library until it is stable enough
> and
> > then we can decide whether we want to keep it like that or include in the
> > project:
> >
> > https://github.com/gyfora/StreamKV
> >
> > Cheers,
> > Gyula
> >
> > Gianmarco De Francisci Morales <gdfm@apache.org> ezt írta (időpont:
> 2015.
> > szept. 9., Sze, 20:25):
> >
> > > Yes, pretty clear. I guess semantically it's still a co-group, but
> > > implemented slightly differently.
> > >
> > > Thanks!
> > >
> > > --
> > > Gianmarco
> > >
> > > On 9 September 2015 at 15:37, Gyula Fóra <gyula.fora@gmail.com> wrote:
> > >
> > > > Hey Gianmarco,
> > > >
> > > > So the implementation looks something different:
> > > >
> > > > The update stream is received by a stateful KVStoreOperator which
> > stores
> > > > the K-V pairs as their partitioned state.
> > > >
> > > > The query for the 2 cities is assigned an ID yes, and is split to
> the 2
> > > > cities, and each of these are  sent to the same KVStoreOperator as
> the
> > > > update stream. The output is the value for each key practically (qid,
> > > > city1, temp1) which is retreived from the operator state , and this
> > > output
> > > > is merged in a next operator to form the KV[] output on which the
> user
> > > can
> > > > execute the difference if he wants.
> > > >
> > > > So actually no co-group is happening although semantically it might
> be
> > > > similar. Instead I use stateful operators to be much more efficient.
> > > >
> > > > Does this answer you question?
> > > >
> > > > Gyula
> > > >
> > > > Gianmarco De Francisci Morales <gdfm@apache.org> ezt írta (időpont:
> > > 2015.
> > > > szept. 9., Sze, 14:29):
> > > >
> > > > > Just a silly question.
> > > > > For the example you described, in a data flow model, you would do
> > > > something
> > > > > like this:
> > > > >
> > > > > Have query ids added to the city pairs (qid, city1, city2),
> > > > > then split the query stream on the two cities and co-group it with
> > the
> > > > > updates stream ((city1, qid) , (city, temp)), same for city2,
> > > > > then emit (qid, city1, temp1), (qid, city2, temp2) from the two
> > > > co-groups,
> > > > > group on the qid, and apply a difference operator to get the final
> > > > answer.
> > > > >
> > > > > Is your  idea to implement a way to generalize this logic, or it
> > would
> > > > use
> > > > > remote read/write to a KV-store?
> > > > >
> > > > > --
> > > > > Gianmarco
> > > > >
> > > > > On 8 September 2015 at 16:27, Aljoscha Krettek <
> aljoscha@apache.org>
> > > > > wrote:
> > > > >
> > > > > > That's a very nice application of the Stream API and partitioned
> > > state.
> > > > > :D
> > > > > >
> > > > > > I think we should run some tests on a cluster  based on this
to
> see
> > > > what
> > > > > > kind of throughput the partitioned state system can handle and
> also
> > > how
> > > > > it
> > > > > > behaves with larger numbers of keys. The KVStore is just an
> > interface
> > > > and
> > > > > > the really heavy lifting is done by the state system so this
> would
> > > be a
> > > > > > good test for it.
> > > > > >
> > > > > >
> > > > > > On Tue, 8 Sep 2015 at 15:10 Gyula Fóra <gyula.fora@gmail.com>
> > wrote:
> > > > > >
> > > > > > > @Stephan:
> > > > > > >
> > > > > > > Technically speaking this is really just a partitioned
> key-value
> > > > state
> > > > > > and
> > > > > > > a fancy operator executing special operations on this state.
> > > > > > >
> > > > > > > From the user's perspective though this is something hard
to
> > > > implement.
> > > > > > If
> > > > > > > you want to share state between two stream for instance
this
> way
> > > > > (getting
> > > > > > > updates from one stream and enriching the other one) you
would
> > > > probably
> > > > > > use
> > > > > > > a connected datastream and custom implement the Key-value
store
> > > > logic.
> > > > > > But
> > > > > > > once you have one(or more) update stream and many get streams
> > this
> > > > > > > implementation will not work. So either the user end up
> > replicating
> > > > the
> > > > > > > whole state in multiple connected operators, or custom
> implement
> > > some
> > > > > > > inefficient wrapper class to take care of all the put/get
> > > operations.
> > > > > > >
> > > > > > > The Idea behind this is to give a very simple abstraction
for
> > this
> > > > type
> > > > > > of
> > > > > > > processing that uses the flink runtime efficiently instead
of
> > > relying
> > > > > on
> > > > > > > custom implementations.
> > > > > > >
> > > > > > > Let me give you a stupid example:
> > > > > > >
> > > > > > > You receive Temperature data in the form of (city,
> temperature),
> > > and
> > > > > you
> > > > > > > are computing a rolling avg for each city.
> > > > > > > Now you have 2 other incoming streams: first is a stream
of
> some
> > > > other
> > > > > > info
> > > > > > > about the city let's say population (city, population)
and you
> > want
> > > > to
> > > > > > > combine it with the last known avg temperature to produce
> (city,
> > > > temp,
> > > > > > pop)
> > > > > > > triplets. The second stream is a pair of cities (city,city)
and
> > you
> > > > are
> > > > > > > interested in the difference of the temperature.
> > > > > > >
> > > > > > > For enriching the (city, pop) to (city,temp,pop) you would
> > probably
> > > > > use a
> > > > > > > CoFlatMap and store the last known rolling avg as state.
For
> > > > computing
> > > > > > the
> > > > > > > (city,city) temperature difference it is a little more
> difficult,
> > > as
> > > > > you
> > > > > > > need to get the temperature for both cities then combine
in a
> > > second
> > > > > > > operator. If you don't want to replicate your state, you
have
> to
> > > > > combine
> > > > > > > these two problems to a common wrapper type and execute
them
> on a
> > > > same
> > > > > > > operator which will keep the avg state.
> > > > > > >
> > > > > > > With the KVStore abstraction this is very simple:
> > > > > > > you create a KVStore<City, Temp>
> > > > > > > For enriching you use kvStore.getWithKeySelector() which
will
> > give
> > > > you
> > > > > > > ((cit,pop), temp) pairs and you are done. For computing
the
> > > > difference,
> > > > > > you
> > > > > > > can use kvStore.multiget(...) and get for the 2 cities
at the
> > same
> > > > > type.
> > > > > > > The kv store will abstract away the getting of the 2 keys
> > > separately
> > > > > and
> > > > > > > merging them so it will return [(city1, t1), (city2,t2)].
> > > > > > >
> > > > > > > This might be slightly artificial example but I think it
makes
> > the
> > > > > point.
> > > > > > > Implementing these jobs efficiently is not trivial for
the
> users
> > > but
> > > > I
> > > > > > > think it is a very common problem.
> > > > > > >
> > > > > > > Stephan Ewen <sewen@apache.org> ezt írta (időpont:
2015.
> szept.
> > > 8.,
> > > > K,
> > > > > > > 14:53):
> > > > > > >
> > > > > > > > @Gyula
> > > > > > > >
> > > > > > > > Can you explain a bit what this KeyValue store would
do more
> > then
> > > > the
> > > > > > > > partitioned key/value state?
> > > > > > > >
> > > > > > > > On Tue, Sep 8, 2015 at 2:49 PM, Gábor Gévay <
> ggab90@gmail.com>
> > > > > wrote:
> > > > > > > >
> > > > > > > > > Hello,
> > > > > > > > >
> > > > > > > > > As for use cases, in my old job at Ericsson we
were
> building
> > a
> > > > > > > > > streaming system that was processing data from
telephone
> > > > networks,
> > > > > > and
> > > > > > > > > it was using key-value stores a LOT. For example,
keeping
> > track
> > > > of
> > > > > > > > > various state info of the users (which cell are
they
> > currently
> > > > > > > > > connected to, what bearers do they have, ...);
mapping from
> > IDs
> > > > of
> > > > > > > > > users in one subsystem of the telephone network
to the IDs
> of
> > > the
> > > > > > same
> > > > > > > > > users in an other subsystem; mapping from IDs
of phone
> calls
> > to
> > > > > lists
> > > > > > > > > of IDs of participating users; etc.
> > > > > > > > > So I imagine they would like this a lot. (At
least, if they
> > > were
> > > > > > > > > considering moving to Flink :))
> > > > > > > > >
> > > > > > > > > Best,
> > > > > > > > > Gabor
> > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > > > 2015-09-08 13:35 GMT+02:00 Gyula Fóra <gyfora@apache.org>:
> > > > > > > > > > Hey All,
> > > > > > > > > >
> > > > > > > > > > The last couple of days I have been playing
around with
> the
> > > > idea
> > > > > of
> > > > > > > > > > building a streaming key-value store abstraction
using
> > > stateful
> > > > > > > > streaming
> > > > > > > > > > operators that can be used within Flink
Streaming
> programs
> > > > > > > seamlessly.
> > > > > > > > > >
> > > > > > > > > > Operations executed on this KV store would
be fault
> > tolerant
> > > as
> > > > > it
> > > > > > > > > > integrates with the checkpointing mechanism,
and if we
> add
> > > > > > timestamps
> > > > > > > > to
> > > > > > > > > > each put/get/... operation we can use the
watermarks to
> > > create
> > > > > > fully
> > > > > > > > > > deterministic results. This functionality
is very useful
> > for
> > > > many
> > > > > > > > > > applications, and is very hard to implement
properly with
> > > some
> > > > > > > > dedicates
> > > > > > > > > kv
> > > > > > > > > > store.
> > > > > > > > > >
> > > > > > > > > > The KVStore abstraction could look as follows:
> > > > > > > > > >
> > > > > > > > > > KVStore<K,V> store = new KVStore<>;
> > > > > > > > > >
> > > > > > > > > > Operations:
> > > > > > > > > >
> > > > > > > > > > store.put(DataStream<Tuple2<K,V>>)
> > > > > > > > > > store.get(DataStream<K>) -> DataStream<KV<K,V>>
> > > > > > > > > > store.remove(DataStream<K>) ->
DataStream<KV<K,V>>
> > > > > > > > > > store.multiGet(DataStream<K[]>) ->
DataStream<KV<K,V>[]>
> > > > > > > > > > store.getWithKeySelector(DataStream<X>,
KeySelector<X,K>)
> > ->
> > > > > > > > > > DataStream<KV<X,V>[]>
> > > > > > > > > >
> > > > > > > > > > For the resulting streams I used a special
KV abstraction
> > > which
> > > > > > let's
> > > > > > > > us
> > > > > > > > > > return null values.
> > > > > > > > > >
> > > > > > > > > > The implementation uses a simple streaming
operator for
> > > > executing
> > > > > > > most
> > > > > > > > of
> > > > > > > > > > the operations (for multi get there is an
additional
> merge
> > > > > > operator)
> > > > > > > > with
> > > > > > > > > > either local or partitioned states for storing
the
> > kev-value
> > > > > pairs
> > > > > > > (my
> > > > > > > > > > current prototype uses local states). And
it can either
> > > execute
> > > > > > > > > operations
> > > > > > > > > > eagerly (which would not provide deterministic
results),
> or
> > > > > buffer
> > > > > > up
> > > > > > > > > > operations and execute them in order upon
watermarks.
> > > > > > > > > >
> > > > > > > > > > As for use cases you can probably come up
with many I
> will
> > > save
> > > > > > that
> > > > > > > > for
> > > > > > > > > > now :D
> > > > > > > > > >
> > > > > > > > > > I have a prototype implementation here that
can execute
> the
> > > > > > > operations
> > > > > > > > > > described above (does not handle watermarks
and time
> yet):
> > > > > > > > > >
> > > > > > > > > > https://github.com/gyfora/flink/tree/KVStore
> > > > > > > > > > And also an example job:
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > >
> > > > > > > >
> > > > > > >
> > > > > >
> > > > >
> > > >
> > >
> >
> https://github.com/gyfora/flink/blob/KVStore/flink-staging/flink-streaming/flink-streaming-core/src/test/java/org/apache/flink/streaming/api/KVStreamExample.java
> > > > > > > > > >
> > > > > > > > > > What do you think?
> > > > > > > > > > If you like it I will work on writing tests
and it still
> > > needs
> > > > a
> > > > > > lot
> > > > > > > of
> > > > > > > > > > tweaking and refactoring. This might be
something we want
> > to
> > > > > > include
> > > > > > > > with
> > > > > > > > > > the standard streaming libraries at one
point.
> > > > > > > > > >
> > > > > > > > > > Cheers,
> > > > > > > > > > Gyula
> > > > > > > > >
> > > > > > > >
> > > > > > >
> > > > > >
> > > > >
> > > >
> > >
> >
>



-- 

*Nam-Luc TRAN*

R&D Manager

EURA NOVA

(M) +32 498 37 36 23

*euranova.eu <http://euranova.eu>*

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