Alex, It seams to me that replace semantic can be implemented with StreamReceiver, no?
D. On Sat, Dec 10, 2016 at 2:54 AM, Alexander Paschenko < alexander.a.pasche...@gmail.com> wrote: > Sorry, "no relation w/JDBC" in my previous message should read "no relation > w/JDBC batching". > > — Alex > 10 дек. 2016 г. 1:52 PM пользователь "Alexander Paschenko" < > alexander.a.pasche...@gmail.com> написал: > > > Dima, > > > > I would like to point out that data streamer support had already been > > implemented in the course of work on DML in 1.8 exactly as you are > > suggesting now (turned on via connection flag; allowed only MERGE — data > > streamer can't do putIfAbsent stuff, right?; absolutely no relation > > w/JDBC), *but* that patch had been reverted — by advice from Vlad which I > > believe had been agreed with you, so it didn't make it to 1.8 after all. > > Also, while it's possible to maintain INSERT vs MERGE semantic using > > streamer's allowOverwrite flag, I can't see how we could mimic UPDATE > here > > as long as the streamer does not put data to cache only in case when key > is > > present AND allowOverwrite is false, while UPDATE should not put anything > > when the key is *missing* — i.e., there's no way to emulate cache's > > *replace* operation semantic with streamer (update value only if key is > > present, otherwise do nothing). > > > > — Alex > > 9 дек. 2016 г. 10:00 PM пользователь "Dmitriy Setrakyan" < > > dsetrak...@apache.org> написал: > > > >> On Fri, Dec 9, 2016 at 12:45 AM, Vladimir Ozerov <voze...@gridgain.com> > >> wrote: > >> > >> > I already expressed my concern - this is counterintuitive approach. > >> Because > >> > without happens-before pure streaming model can be applied only on > >> > independent chunks of data. It mean that mentioned ETL use case is not > >> > feasible - ETL always depend on implicit or explicit links between > >> tables, > >> > and hence streaming is not applicable here. My question stands still - > >> what > >> > products except of possibly Ignite do this kind of JDBC streaming? > >> > > >> > >> Vova, we have 2 mechanisms in the product: IgniteCache.putAll() or > >> DataStreamer.addData(). > >> > >> JDBC batching and putAll() are absolutely identical. If you see it as > >> counter-intuitive, I would ask for a concrete example. > >> > >> As far as links between data, Ignite does not have foreign-key > >> constraints, > >> so DataStreamer can insert data in any order (but again, not as part of > >> JDBC batch). > >> > >> > >> > > >> > Another problem is that connection-wide property doesn't fit well in > >> JDBC > >> > pooling model. Users will have use different connections for streaming > >> and > >> > non-streaming approaches. > >> > > >> > >> Using DataStreamer is not possible within JDBC batching paradigm, > period. > >> I > >> wish we could drop the high-level-feels-good discussions altogether, > >> because it seems like we are spinning wheels here. > >> > >> There is no way to use the streamer in JDBC context, unless we add a > >> connection flag. Again, if you disagree, I would prefer to see a > concrete > >> example explaining why. > >> > >> > >> > Please see how Oracle did that, this is precisely what I am talking > >> about: > >> > https://docs.oracle.com/cd/B28359_01/java.111/b31224/oraperf > >> .htm#i1056232 > >> > Two batching modes - one with explicit flush, another one with > implicit > >> > flush, when Oracle decides on it's own when it is better to > communicate > >> the > >> > server. Batching mode can be declared globally or on per-statement > >> level. > >> > Simple and flexible. > >> > > >> > > >> > On Fri, Dec 9, 2016 at 4:40 AM, Dmitriy Setrakyan < > >> dsetrak...@apache.org> > >> > wrote: > >> > > >> > > Gents, > >> > > > >> > > As Sergi suggested, batching and streaming are very different > >> > semantically. > >> > > > >> > > To use standard JDBC batching, all we need to do is convert it to a > >> > > cache.putAll() method, as semantically a putAll(...) call is > identical > >> > to a > >> > > JDBC batch. Of course, if we see and UPDATE with a WHERE clause in > >> > between, > >> > > then we may have to break a batch into several chunks and execute > the > >> > > update in between. The DataStreamer should not be used here. > >> > > > >> > > I believe that for streaming we need to add a special JDBC/ODBC > >> > connection > >> > > flag. Whenever this flag is set to true, then we only should allow > >> INSERT > >> > > or single-UPDATE operations and use DataStreamer API internally. All > >> > > operations other than INSERT or single-UPDATE should be prohibited. > >> > > > >> > > I think this design is semantically clear. Any objections? > >> > > > >> > > D. > >> > > > >> > > On Thu, Dec 8, 2016 at 5:02 AM, Sergi Vladykin < > >> sergi.vlady...@gmail.com > >> > > > >> > > wrote: > >> > > > >> > > > If we use Streamer, then we always have `happens-before` broken. > >> This > >> > is > >> > > > ok, because Streamer is for data loading, not for usual operating. > >> > > > > >> > > > We are not inventing any bicycles, just separating concerns: > >> Batching > >> > and > >> > > > Streaming. > >> > > > > >> > > > My point here is that they should not depend on each other at all: > >> > > Batching > >> > > > can work with or without Streaming, as well as Streaming can work > >> with > >> > or > >> > > > without Batching. > >> > > > > >> > > > Your proposal is a set of non-obvious rules for them to work. I > see > >> no > >> > > > reasons for these complications. > >> > > > > >> > > > Sergi > >> > > > > >> > > > > >> > > > 2016-12-08 15:49 GMT+03:00 Vladimir Ozerov <voze...@gridgain.com > >: > >> > > > > >> > > > > Sergi, > >> > > > > > >> > > > > If user call single *execute() *operation, than most likely it > is > >> not > >> > > > > batching. We should not rely on strange case where user perform > >> > > batching > >> > > > > without using standard and well-adopted batching JDBC API. The > >> main > >> > > > problem > >> > > > > with streamer is that it is async and hence break happens-before > >> > > > guarantees > >> > > > > in a single thread: SELECT after INSERT might not return > inserted > >> > > value. > >> > > > > > >> > > > > Honestly, I do not really understand why we are trying to > >> re-invent a > >> > > > > bicycle here. There is standard API - let's just use it and make > >> > > flexible > >> > > > > enough to take advantage of IgniteDataStreamer if needed. > >> > > > > > >> > > > > Is there any use case which is not covered with this solution? > Or > >> let > >> > > me > >> > > > > ask from the opposite side - are there any well-known JDBC > drivers > >> > > which > >> > > > > perform batching/streaming from non-batched update statements? > >> > > > > > >> > > > > Vladimir. > >> > > > > > >> > > > > On Thu, Dec 8, 2016 at 3:38 PM, Sergi Vladykin < > >> > > sergi.vlady...@gmail.com > >> > > > > > >> > > > > wrote: > >> > > > > > >> > > > > > Vladimir, > >> > > > > > > >> > > > > > I see no reason to forbid Streamer usage from non-batched > >> statement > >> > > > > > execution. > >> > > > > > It is common that users already have their ETL tools and you > >> can't > >> > be > >> > > > > sure > >> > > > > > if they use batching or not. > >> > > > > > > >> > > > > > Alex, > >> > > > > > > >> > > > > > I guess we have to decide on Streaming first and then we will > >> > discuss > >> > > > > > Batching separately, ok? Because this decision may become > >> important > >> > > for > >> > > > > > batching implementation. > >> > > > > > > >> > > > > > Sergi > >> > > > > > > >> > > > > > 2016-12-08 15:31 GMT+03:00 Andrey Gura <ag...@apache.org>: > >> > > > > > > >> > > > > > > Alex, > >> > > > > > > > >> > > > > > > In most cases JdbcQueryTask should be executed locally on > >> client > >> > > node > >> > > > > > > started by JDBC driver. > >> > > > > > > > >> > > > > > > JdbcQueryTask.QueryResult res = > >> > > > > > > loc ? qryTask.call() : > >> > > > > > > ignite.compute(ignite.cluster().forNodeId(nodeId)).call( > >> > qryTask); > >> > > > > > > > >> > > > > > > Is it valid behavior after introducing DML functionality? > >> > > > > > > > >> > > > > > > In cases when user wants to execute query on specific node > he > >> > > should > >> > > > > > > fully understand what he wants and what can go in wrong way. > >> > > > > > > > >> > > > > > > > >> > > > > > > On Thu, Dec 8, 2016 at 3:20 PM, Alexander Paschenko > >> > > > > > > <alexander.a.pasche...@gmail.com> wrote: > >> > > > > > > > Sergi, > >> > > > > > > > > >> > > > > > > > JDBC batching might work quite differently from driver to > >> > driver. > >> > > > > Say, > >> > > > > > > > MySQL happily rewrites queries as I had suggested in the > >> > > beginning > >> > > > of > >> > > > > > > > this thread (it's not the only strategy, but one of the > >> > possible > >> > > > > > > > options) - and, BTW, would like to hear at least an > opinion > >> > about > >> > > > it. > >> > > > > > > > > >> > > > > > > > On your first approach, section before streamer: you > suggest > >> > that > >> > > > we > >> > > > > > > > send single statement and multiple param sets as a single > >> query > >> > > > task, > >> > > > > > > > am I right? (Just to make sure that I got you properly.) > If > >> so, > >> > > do > >> > > > > you > >> > > > > > > > also mean that API (namely JdbcQueryTask) between server > and > >> > > client > >> > > > > > > > should also change? Or should new API means be added to > >> > > facilitate > >> > > > > > > > batching tasks? > >> > > > > > > > > >> > > > > > > > - Alex > >> > > > > > > > > >> > > > > > > > 2016-12-08 15:05 GMT+03:00 Sergi Vladykin < > >> > > > sergi.vlady...@gmail.com > >> > > > > >: > >> > > > > > > >> Guys, > >> > > > > > > >> > >> > > > > > > >> I discussed this feature with Dmitriy and we came to > >> > conclusion > >> > > > that > >> > > > > > > >> batching in JDBC and Data Streaming in Ignite have > >> different > >> > > > > semantics > >> > > > > > > and > >> > > > > > > >> performance characteristics. Thus they are independent > >> > features > >> > > > > (they > >> > > > > > > may > >> > > > > > > >> work together, may separately, but this is another > story). > >> > > > > > > >> > >> > > > > > > >> Let me explain. > >> > > > > > > >> > >> > > > > > > >> This is how JDBC batching works: > >> > > > > > > >> - Add N sets of parameters to a prepared statement. > >> > > > > > > >> - Manually execute prepared statement. > >> > > > > > > >> - Repeat until all the data is loaded. > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> This is how data streamer works: > >> > > > > > > >> - Keep adding data. > >> > > > > > > >> - Streamer will buffer and load buffered per-node batches > >> when > >> > > > they > >> > > > > > are > >> > > > > > > big > >> > > > > > > >> enough. > >> > > > > > > >> - Close streamer to make sure that everything is loaded. > >> > > > > > > >> > >> > > > > > > >> As you can see we have a difference in semantics of when > we > >> > send > >> > > > > data: > >> > > > > > > if > >> > > > > > > >> in our JDBC we will allow sending batches to nodes > without > >> > > calling > >> > > > > > > >> `execute` (and probably we will need to make `execute` to > >> > no-op > >> > > > > here), > >> > > > > > > then > >> > > > > > > >> we are violating semantics of JDBC, if we will disallow > >> this > >> > > > > behavior, > >> > > > > > > then > >> > > > > > > >> this batching will underperform. > >> > > > > > > >> > >> > > > > > > >> Thus I suggest keeping these features (JDBC Batching and > >> JDBC > >> > > > > > > Streaming) as > >> > > > > > > >> separate features. > >> > > > > > > >> > >> > > > > > > >> As I already said they can work together: Batching will > >> batch > >> > > > > > parameters > >> > > > > > > >> and on `execute` they will go to the Streamer in one shot > >> and > >> > > > > Streamer > >> > > > > > > will > >> > > > > > > >> deal with the rest. > >> > > > > > > >> > >> > > > > > > >> Sergi > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> > >> > > > > > > >> 2016-12-08 14:16 GMT+03:00 Vladimir Ozerov < > >> > > voze...@gridgain.com > >> > > > >: > >> > > > > > > >> > >> > > > > > > >>> Hi Alex, > >> > > > > > > >>> > >> > > > > > > >>> To my understanding there are two possible approaches to > >> > > batching > >> > > > > in > >> > > > > > > JDBC > >> > > > > > > >>> layer: > >> > > > > > > >>> > >> > > > > > > >>> 1) Rely on default batching API. Specifically > >> > > > > > > >>> *PreparedStatement.addBatch()* [1] > >> > > > > > > >>> and others. This is nice and clear API, users are used > to > >> it, > >> > > and > >> > > > > > it's > >> > > > > > > >>> adoption will minimize user code changes when migrating > >> from > >> > > > other > >> > > > > > JDBC > >> > > > > > > >>> sources. We simply copy updates locally and then execute > >> them > >> > > all > >> > > > > at > >> > > > > > > once > >> > > > > > > >>> with only a single network hop to servers. > >> > *IgniteDataStreamer* > >> > > > can > >> > > > > > be > >> > > > > > > used > >> > > > > > > >>> underneath. > >> > > > > > > >>> > >> > > > > > > >>> 2) Or we can have separate connection flag which will > move > >> > all > >> > > > > > > >>> INSERT/UPDATE/DELETE statements through streamer. > >> > > > > > > >>> > >> > > > > > > >>> I prefer the first approach > >> > > > > > > >>> > >> > > > > > > >>> Also we need to keep in mind that data streamer has poor > >> > > > > performance > >> > > > > > > when > >> > > > > > > >>> adding single key-value pairs due to high overhead on > >> > > concurrency > >> > > > > and > >> > > > > > > other > >> > > > > > > >>> bookkeeping. Instead, it is better to pre-batch > key-value > >> > pairs > >> > > > > > before > >> > > > > > > >>> giving them to streamer. > >> > > > > > > >>> > >> > > > > > > >>> Vladimir. > >> > > > > > > >>> > >> > > > > > > >>> [1] > >> > > > > > > >>> https://docs.oracle.com/javase/8/docs/api/java/sql/ > >> > > > > > > PreparedStatement.html# > >> > > > > > > >>> addBatch-- > >> > > > > > > >>> > >> > > > > > > >>> On Thu, Dec 8, 2016 at 1:21 PM, Alexander Paschenko < > >> > > > > > > >>> alexander.a.pasche...@gmail.com> wrote: > >> > > > > > > >>> > >> > > > > > > >>> > Hello Igniters, > >> > > > > > > >>> > > >> > > > > > > >>> > One of the major improvements to DML has to be support > >> of > >> > > batch > >> > > > > > > >>> > statements. I'd like to discuss its implementation. > The > >> > > > suggested > >> > > > > > > >>> > approach is to rewrite given query turning it from few > >> > > INSERTs > >> > > > > into > >> > > > > > > >>> > single statement and processing arguments > accordingly. I > >> > > > suggest > >> > > > > > this > >> > > > > > > >>> > as long as the whole point of batching is to make as > >> little > >> > > > > > > >>> > interactions with cluster as possible and to make > >> > operations > >> > > as > >> > > > > > > >>> > condensed as possible, and in case of Ignite it means > >> that > >> > we > >> > > > > > should > >> > > > > > > >>> > send as little JdbcQueryTasks as possible. And, as > long > >> as > >> > a > >> > > > > query > >> > > > > > > >>> > task holds single query and its arguments, this > approach > >> > will > >> > > > not > >> > > > > > > >>> > require any changes to be done to current design and > >> won't > >> > > > break > >> > > > > > any > >> > > > > > > >>> > backward compatibility - all dirty work on rewriting > >> will > >> > be > >> > > > done > >> > > > > > by > >> > > > > > > >>> > JDBC driver. > >> > > > > > > >>> > Without rewriting, we could introduce some new query > >> task > >> > for > >> > > > > batch > >> > > > > > > >>> > operations, but that would make impossible sending > such > >> > > > requests > >> > > > > > from > >> > > > > > > >>> > newer clients to older servers (say, servers of > version > >> > > 1.8.0, > >> > > > > > which > >> > > > > > > >>> > does not know about batching, let alone older > versions). > >> > > > > > > >>> > I'd like to hear comments and suggestions from the > >> > community. > >> > > > > > Thanks! > >> > > > > > > >>> > > >> > > > > > > >>> > - Alex > >> > > > > > > >>> > > >> > > > > > > >>> > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > > >> > > >> > -- > >> > Vladimir Ozerov > >> > Senior Software Architect > >> > GridGain Systems > >> > www.gridgain.com > >> > *+7 (960) 283 98 40* > >> > > >> > > >
