Some users have expressed the need to have some sort of forEach operation that is performed where the Consumer is called while holding the lock for the given key and subsequently released after the Consumer operation completes. Due to the nature of how streams work with retries and performing the operation on the primary owner, this works out quite well with forEach to be done in an efficient way. The problem is that this only really works well with non tx and pessimistic tx. This obviously leaves out optimistic tx, which at first I was a little worried about. But after thinking about it more, this prelocking and optimistic tx don't really fit that well together anyways. So I am thinking whenever this operation is performed it would throw an exception not letting the user use this feature in optimistic transactions. Another question is what does the API for this look like. I was debating between 3 options myself: 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> consumer) This require the least amount of changes, however the user can't customize certain parameters that CacheStream currently provides (listed below - big one being filterKeys). 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> consumer) This method would only be allowed to be invoked on the Stream if no other intermediate operations were invoked, otherwise an exception would be thrown. This still gives us access to all of the CacheStream methods that aren't on the Stream interface (ie. sequentialDistribution, parallelDistribution, parallel, sequential, filterKeys, filterKeySegments, distributedBatchSize, disableRehashAware, timeout). 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() This requires the most changes, however the API would be the most explicit. In this case the LockedStream would only have the methods on it that are able to be invoked as noted above and forEach. I personally feel that #3 might be the cleanest, but obviously requires adding more classes. Let me know what you guys think and if you think the optimistic exclusion is acceptable. Thanks, - Will _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On 21 Mar 2017, at 17:16, Dan Berindei <dan.berindei(a)gmail.com&gt; wrote: I'm leaning towards option 1. Are you thinking about also allowing the consumer to modify the entry, like JCache's EntryProcessors? For a consumer that can only modify the current entry, we could even "emulate" locking in an optimistic cache by catching the WriteSkewException and running the consumer again. I wouldn't allow this to be mixed with other operations in a stream, because then you may have to run filters/mappers/sorting while holding the lock as well.

Cheers Dan On Tue, Mar 21, 2017 at 5:37 PM, William Burns <mudokonman(a)gmail.com&gt; wrote: > Some users have expressed the need to have some sort of forEach operation > that is performed where the Consumer is called while holding the lock for > the given key and subsequently released after the Consumer operation > completes. > > Due to the nature of how streams work with retries and performing the > operation on the primary owner, this works out quite well with forEach to be > done in an efficient way. > > The problem is that this only really works well with non tx and pessimistic > tx. This obviously leaves out optimistic tx, which at first I was a little > worried about. But after thinking about it more, this prelocking and > optimistic tx don't really fit that well together anyways. So I am thinking > whenever this operation is performed it would throw an exception not letting > the user use this feature in optimistic transactions. > > Another question is what does the API for this look like. I was debating > between 3 options myself: > > 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > consumer) > > This require the least amount of changes, however the user can't customize > certain parameters that CacheStream currently provides (listed below - big > one being filterKeys). > > 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> consumer) > > This method would only be allowed to be invoked on the Stream if no other > intermediate operations were invoked, otherwise an exception would be > thrown. This still gives us access to all of the CacheStream methods that > aren't on the Stream interface (ie. sequentialDistribution, > parallelDistribution, parallel, sequential, filterKeys, filterKeySegments, > distributedBatchSize, disableRehashAware, timeout). > > 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > > This requires the most changes, however the API would be the most explicit. > In this case the LockedStream would only have the methods on it that are > able to be invoked as noted above and forEach. > > I personally feel that #3 might be the cleanest, but obviously requires > adding more classes. Let me know what you guys think and if you think the > optimistic exclusion is acceptable. > > Thanks, > > - Will > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On Mon, Mar 27, 2017 at 9:02 PM Galder Zamarreño <galder(a)redhat.com&gt; wrote: > > > -- > Galder Zamarreño > Infinispan, Red Hat > > > On 21 Mar 2017, at 17:16, Dan Berindei <dan.berindei(a)gmail.com&gt; wrote: > > > > I'm leaning towards option 1. > > > > Are you thinking about also allowing the consumer to modify the entry, > > like JCache's EntryProcessors? For a consumer that can only modify the > > current entry, we could even "emulate" locking in an optimistic cache > > by catching the WriteSkewException and running the consumer again. > > > > I wouldn't allow this to be mixed with other operations in a stream, > > because then you may have to run filters/mappers/sorting while holding > > the lock as well. > > ^ Would forEach w/ lock still run for all entries in originator? If so, > not being able to filter could be a pain. IOW, you'd be forcing all entries > to be shipped to a node and user to do its own filtering. Not ideal :\ No the primary owner would run the operation per entry. I was thinking we would have 2 levels of filtering in my proposal above. We would have the first one which is using filterKeys on the CacheStream method. This requires serializing keys sent to each node (only primary owned keys are sent). While it has the cost of serialization it makes up for by having constant time lookups (no iterating memory/stores) for the keys as it creates a stream using Cache.get to populate it. The second was to support the filter method on the Stream API which would allow for a Predicate so you don't have to serialize keys. In this case you wouldn't want to include keys in this Predicate as all keys would be serialized to all nodes and then you still have to iterate and check the entire data container/store. You could actually do both as well. So if you only want a subset of known keys where their values match a Predicate this can be done too. cache.lockedStream().filterKeys(keys).filter(predicate).forEach(); > > > > > > > Cheers > > Dan > > > > > > On Tue, Mar 21, 2017 at 5:37 PM, William Burns <mudokonman(a)gmail.com&gt; > > wrote: > >> Some users have expressed the need to have some sort of forEach > >> operation > >> that is performed where the Consumer is called while holding the lock > >> for > >> the given key and subsequently released after the Consumer operation > >> completes. > >> > >> Due to the nature of how streams work with retries and performing the > >> operation on the primary owner, this works out quite well with forEach > >> to be > >> done in an efficient way. > >> > >> The problem is that this only really works well with non tx and > >> pessimistic > >> tx. This obviously leaves out optimistic tx, which at first I was a > >> little > >> worried about. But after thinking about it more, this prelocking and > >> optimistic tx don't really fit that well together anyways. So I am > >> thinking > >> whenever this operation is performed it would throw an exception not > >> letting > >> the user use this feature in optimistic transactions. > >> > >> Another question is what does the API for this look like. I was > >> debating > >> between 3 options myself: > >> > >> 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > >> consumer) > >> > >> This require the least amount of changes, however the user can't > >> customize > >> certain parameters that CacheStream currently provides (listed below - > >> big > >> one being filterKeys). > >> > >> 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > >> consumer) > >> > >> This method would only be allowed to be invoked on the Stream if no > >> other > >> intermediate operations were invoked, otherwise an exception would be > >> thrown. This still gives us access to all of the CacheStream methods > >> that > >> aren't on the Stream interface (ie. sequentialDistribution, > >> parallelDistribution, parallel, sequential, filterKeys, > >> filterKeySegments, > >> distributedBatchSize, disableRehashAware, timeout). > >> > >> 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > >> > >> This requires the most changes, however the API would be the most > >> explicit. > >> In this case the LockedStream would only have the methods on it that > >> are > >> able to be invoked as noted above and forEach. > >> > >> I personally feel that #3 might be the cleanest, but obviously requires > >> adding more classes. Let me know what you guys think and if you think > >> the > >> optimistic exclusion is acceptable. > >> > >> Thanks, > >> > >> - Will > >> > >> _______________________________________________ > >> infinispan-dev mailing list > >> infinispan-dev(a)lists.jboss.org > >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > > _______________________________________________ > > infinispan-dev mailing list > > infinispan-dev(a)lists.jboss.org > > https://lists.jboss.org/mailman/listinfo/infinispan-dev > > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On Tue, Mar 28, 2017 at 11:24 AM Sanne Grinovero <sanne(a)infinispan.org&gt; wrote: > > Hi Will, > > I'm confused about the premise; when you state > > " the Consumer is called while holding the lock for the given key and > subsequently released after the Consumer operation completes." > > What are the transaction boundaries? > I see two options, please correct me so I understand: > > A) > > transaction.begin(); > cache.lockedStream().filterKeys(keys).filter(predicate).forEach( > someOperation ); > transaction.commit(); <-- release all locks > > B) > > cache.lockedStream().filterKeys(keys).filter(predicate).forEach( > transaction.begin(); > //to stuff on entry > /transaction.commit(); <-- release this single entry's lock > ); The user code doesn't really affect this, it is done internally by Infinispan. We would acquire the lock on the user's behalf in the stream operation then call the user's accept method. Then after they return we would unlock the lock. The way I have it implemented at the moment in my PoC (which could change) is I don't even start a transaction. It just locks the key and then if the user were to invoke an operation that requires a transaction it adds the lock owner to their tx context at that point so they have ownership of the key. Also to note that a commit or rollback in the Consumer currently doesn't release the lock on the key. Although this could be discussed to be possibly changed.

> > > > I think it's important to clarify this as I suspect that #A is not > implementable within reasonable guarantees, while in the case of B# I > see no use for optimistic locking *from a user's perspective*. Exactly my thoughts regarding optimistic. I don't think #A is even feasible given constraints of having a distributed transaction like this.

> > > Also: what kind of guarantees do you expect about having the operation > being applied on some entry which is strictly *still* a subset of the > keys as defined by the filter predicates? > I take it you'd want to acquire the locks during the filtering process? That is a good question. I hadn't thought about the details but what I had implemented was we have to first read the entry, lock the key, reread the entry (in case of concurrent update) and then finally call their Predicate. Another reason the filterKeys is much more efficient :) Note this read, locking and reread is done even without a Predicate supplied. And actually I can also optimize filterKeys to not do the initial read since we already have the key.

> > > That would require the move the transaction boundary to the scenario > A# which seems undesirable. > Technically if I were to need something like this I guess I'd expect > to have a user experience akin to B# but have Infinispan essentially > use optimistic locking (and auto-skip) on entries which are mutated > and fall out of the filter predicate during the lock attempt. > > Essentially I suspect that we'd not want to implement different > versions of this depending on the transaction mode, but figure out the > use case and implement a one and only transaction mode which suites > such use cases. So for example we'd simply not offer a mode which > requires to copy the whole grid into the current TX context. This was never the intent and in my follow up emails I came to what seems like the same conclusion that basically this can't be done with the user controlling the transaction and it doesn't really make sense in an optimistic transaction (since you are already at that node, you are already doing everything pessimistically).

> > > Thanks, > Sanne > > > > On 28 March 2017 at 14:49, William Burns <mudokonman(a)gmail.com&gt; wrote: > > > > > > On Mon, Mar 27, 2017 at 9:02 PM Galder Zamarreño <galder(a)redhat.com&gt; > > wrote: > >> > >> > >> -- > >> Galder Zamarreño > >> Infinispan, Red Hat > >> > >> > On 21 Mar 2017, at 17:16, Dan Berindei <dan.berindei(a)gmail.com&gt; > >> > wrote: > >> > > >> > I'm leaning towards option 1. > >> > > >> > Are you thinking about also allowing the consumer to modify the > >> > entry, > >> > like JCache's EntryProcessors? For a consumer that can only modify > >> > the > >> > current entry, we could even "emulate" locking in an optimistic cache > >> > by catching the WriteSkewException and running the consumer again. > >> > > >> > I wouldn't allow this to be mixed with other operations in a stream, > >> > because then you may have to run filters/mappers/sorting while > >> > holding > >> > the lock as well. > >> > >> ^ Would forEach w/ lock still run for all entries in originator? If so, > >> not being able to filter could be a pain. IOW, you'd be forcing all > >> entries > >> to be shipped to a node and user to do its own filtering. Not ideal :\ > > > > > > No the primary owner would run the operation per entry. I was thinking > > we > > would have 2 levels of filtering in my proposal above. > > > > We would have the first one which is using filterKeys on the CacheStream > > method. This requires serializing keys sent to each node (only primary > > owned > > keys are sent). While it has the cost of serialization it makes up for > > by > > having constant time lookups (no iterating memory/stores) for the keys > > as it > > creates a stream using Cache.get to populate it. > > > > The second was to support the filter method on the Stream API which > > would > > allow for a Predicate so you don't have to serialize keys. In this case > > you > > wouldn't want to include keys in this Predicate as all keys would be > > serialized to all nodes and then you still have to iterate and check the > > entire data container/store. > > > > You could actually do both as well. So if you only want a subset of > > known > > keys where their values match a Predicate this can be done too. > > > > cache.lockedStream().filterKeys(keys).filter(predicate).forEach(); > > > >> > >> > >> > >> > > >> > Cheers > >> > Dan > >> > > >> > > >> > On Tue, Mar 21, 2017 at 5:37 PM, William Burns <mudokonman(a)gmail.com&gt; > >> > wrote: > >> >> Some users have expressed the need to have some sort of forEach > >> >> operation > >> >> that is performed where the Consumer is called while holding the > >> >> lock > >> >> for > >> >> the given key and subsequently released after the Consumer operation > >> >> completes. > >> >> > >> >> Due to the nature of how streams work with retries and performing > >> >> the > >> >> operation on the primary owner, this works out quite well with > >> >> forEach > >> >> to be > >> >> done in an efficient way. > >> >> > >> >> The problem is that this only really works well with non tx and > >> >> pessimistic > >> >> tx. This obviously leaves out optimistic tx, which at first I was a > >> >> little > >> >> worried about. But after thinking about it more, this prelocking and > >> >> optimistic tx don't really fit that well together anyways. So I am > >> >> thinking > >> >> whenever this operation is performed it would throw an exception not > >> >> letting > >> >> the user use this feature in optimistic transactions. > >> >> > >> >> Another question is what does the API for this look like. I was > >> >> debating > >> >> between 3 options myself: > >> >> > >> >> 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > >> >> consumer) > >> >> > >> >> This require the least amount of changes, however the user can't > >> >> customize > >> >> certain parameters that CacheStream currently provides (listed below > >> >> - > >> >> big > >> >> one being filterKeys). > >> >> > >> >> 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > >> >> consumer) > >> >> > >> >> This method would only be allowed to be invoked on the Stream if no > >> >> other > >> >> intermediate operations were invoked, otherwise an exception would > >> >> be > >> >> thrown. This still gives us access to all of the CacheStream methods > >> >> that > >> >> aren't on the Stream interface (ie. sequentialDistribution, > >> >> parallelDistribution, parallel, sequential, filterKeys, > >> >> filterKeySegments, > >> >> distributedBatchSize, disableRehashAware, timeout). > >> >> > >> >> 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > >> >> > >> >> This requires the most changes, however the API would be the most > >> >> explicit. > >> >> In this case the LockedStream would only have the methods on it that > >> >> are > >> >> able to be invoked as noted above and forEach. > >> >> > >> >> I personally feel that #3 might be the cleanest, but obviously > >> >> requires > >> >> adding more classes. Let me know what you guys think and if you > >> >> think > >> >> the > >> >> optimistic exclusion is acceptable. > >> >> > >> >> Thanks, > >> >> > >> >> - Will > >> >> > >> >> _______________________________________________ > >> >> infinispan-dev mailing list > >> >> infinispan-dev(a)lists.jboss.org > >> >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> > _______________________________________________ > >> > infinispan-dev mailing list > >> > infinispan-dev(a)lists.jboss.org > >> > https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> > >> > >> _______________________________________________ > >> infinispan-dev mailing list > >> infinispan-dev(a)lists.jboss.org > >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > > > > > > _______________________________________________ > > infinispan-dev mailing list > > infinispan-dev(a)lists.jboss.org > > https://lists.jboss.org/mailman/listinfo/infinispan-dev > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On Tue, Mar 28, 2017 at 12:52 PM Dan Berindei <dan.berindei(a)gmail.com&gt; wrote: > > On Tue, Mar 28, 2017 at 6:44 PM, William Burns <mudokonman(a)gmail.com&gt; > wrote: > > > > > > On Tue, Mar 28, 2017 at 11:24 AM Sanne Grinovero <sanne(a)infinispan.org&gt; > > wrote: > >> > >> Hi Will, > >> > >> I'm confused about the premise; when you state > >> > >> " the Consumer is called while holding the lock for the given key and > >> subsequently released after the Consumer operation completes." > >> > >> What are the transaction boundaries? > >> I see two options, please correct me so I understand: > >> > >> A) > >> > >> transaction.begin(); > >> cache.lockedStream().filterKeys(keys).filter(predicate).forEach( > >> someOperation ); > >> transaction.commit(); <-- release all locks > >> > >> B) > >> > >> cache.lockedStream().filterKeys(keys).filter(predicate).forEach( > >> transaction.begin(); > >> //to stuff on entry > >> /transaction.commit(); <-- release this single entry's lock > >> ); > > > > > > The user code doesn't really affect this, it is done internally by > > Infinispan. We would acquire the lock on the user's behalf in the stream > > operation then call the user's accept method. Then after they return we > > would unlock the lock. The way I have it implemented at the moment in my > > PoC > > (which could change) is I don't even start a transaction. It just locks > > the > > key and then if the user were to invoke an operation that requires a > > transaction it adds the lock owner to their tx context at that point so > > they > > have ownership of the key. > > > > Also to note that a commit or rollback in the Consumer currently doesn't > > release the lock on the key. Although this could be discussed to be > > possibly > > changed. > > > > With a transactional cache I was assuming you manage the transaction > yourself... if the user has to call > transactionManager.begin()/commit()/rollback() anyway, why not use a > regular stream? The user would be using an implicit transaction or explicit. Like I said this is up for discussion. The main reason I am staying away from managing the transaction is that the user can mess with the transaction as well which would possibly release the lock. It is much simpler if all I am doing is managing the lock. And if the user doesn't require a transaction in Infinispan we didn't waste time starting one and releasing one.

> > > >> > >> > >> > >> I think it's important to clarify this as I suspect that #A is not > >> implementable within reasonable guarantees, while in the case of B# I > >> see no use for optimistic locking *from a user's perspective*. > > > > > > Exactly my thoughts regarding optimistic. I don't think #A is even > > feasible > > given constraints of having a distributed transaction like this. > > > > Totally agree that #A can't work with any kind of transaction > configuration. > > As to optimistic locking, I would like having "feature parity" between > pessimistic and optimistic caches as much as possible, but I agree > locking eagerly and retrying the consumer on WriteSkewException are a > bit too different to fit under the same API. Yeah I would definitely like to have it as well, but I just can't see how it fits in. This is despite the implementation detail that it is quite difficult to get it working currently :D > > > >> > >> > >> Also: what kind of guarantees do you expect about having the operation > >> being applied on some entry which is strictly *still* a subset of the > >> keys as defined by the filter predicates? > >> I take it you'd want to acquire the locks during the filtering process? > > > > > > That is a good question. I hadn't thought about the details but what I > > had > > implemented was we have to first read the entry, lock the key, reread > > the > > entry (in case of concurrent update) and then finally call their > > Predicate. > > Another reason the filterKeys is much more efficient :) Note this read, > > locking and reread is done even without a Predicate supplied. And > > actually I > > can also optimize filterKeys to not do the initial read since we already > > have the key. > > > > Would this be more efficient than the consumer reading the key with > FORCE_WRITE_LOCK and deciding what to do based on the value? > The problem with this is you have to go remote to lock the key, return the value then do something for every key (not to mention pulling those keys using an iterator). Very costly! The main benefit of the stream with lock is that you are performing everything on the primary owner of the data with the lock already acquired. The only piece sent remotely is the consumer and some internal classes, very light weight and you have all the benefits of data locality.

> > >> > >> > >> That would require the move the transaction boundary to the scenario > >> A# which seems undesirable. > >> Technically if I were to need something like this I guess I'd expect > >> to have a user experience akin to B# but have Infinispan essentially > >> use optimistic locking (and auto-skip) on entries which are mutated > >> and fall out of the filter predicate during the lock attempt. > >> > >> Essentially I suspect that we'd not want to implement different > >> versions of this depending on the transaction mode, but figure out the > >> use case and implement a one and only transaction mode which suites > >> such use cases. So for example we'd simply not offer a mode which > >> requires to copy the whole grid into the current TX context. > > > > > > This was never the intent and in my follow up emails I came to what > > seems > > like the same conclusion that basically this can't be done with the user > > controlling the transaction and it doesn't really make sense in an > > optimistic transaction (since you are already at that node, you are > > already > > doing everything pessimistically). > > > > Even local caches can use optimistic locking :) Yes I know :) I was just framing it in the notion of remote. If anyone can think of a nice way of using this with optimistic transactions I would all be for it. But optimistic transactions just doesn't make any sense to me when you are locking a key eagerly for someone to do something with it (definition of pessimistic transaction).

> > > >> > >> > >> Thanks, > >> Sanne > >> > >> > >> > >> On 28 March 2017 at 14:49, William Burns <mudokonman(a)gmail.com&gt; wrote: > >> > > >> > > >> > On Mon, Mar 27, 2017 at 9:02 PM Galder Zamarreño <galder(a)redhat.com&gt; > >> > wrote: > >> >> > >> >> > >> >> -- > >> >> Galder Zamarreño > >> >> Infinispan, Red Hat > >> >> > >> >> > On 21 Mar 2017, at 17:16, Dan Berindei <dan.berindei(a)gmail.com&gt; > >> >> > wrote: > >> >> > > >> >> > I'm leaning towards option 1. > >> >> > > >> >> > Are you thinking about also allowing the consumer to modify the > >> >> > entry, > >> >> > like JCache's EntryProcessors? For a consumer that can only modify > >> >> > the > >> >> > current entry, we could even "emulate" locking in an optimistic > >> >> > cache > >> >> > by catching the WriteSkewException and running the consumer again. > >> >> > > >> >> > I wouldn't allow this to be mixed with other operations in a > >> >> > stream, > >> >> > because then you may have to run filters/mappers/sorting while > >> >> > holding > >> >> > the lock as well. > >> >> > >> >> ^ Would forEach w/ lock still run for all entries in originator? If > >> >> so, > >> >> not being able to filter could be a pain. IOW, you'd be forcing all > >> >> entries > >> >> to be shipped to a node and user to do its own filtering. Not ideal > >> >> :\ > >> > > >> > > >> > No the primary owner would run the operation per entry. I was > >> > thinking > >> > we > >> > would have 2 levels of filtering in my proposal above. > >> > > >> > We would have the first one which is using filterKeys on the > >> > CacheStream > >> > method. This requires serializing keys sent to each node (only > >> > primary > >> > owned > >> > keys are sent). While it has the cost of serialization it makes up > >> > for > >> > by > >> > having constant time lookups (no iterating memory/stores) for the > >> > keys > >> > as it > >> > creates a stream using Cache.get to populate it. > >> > > >> > The second was to support the filter method on the Stream API which > >> > would > >> > allow for a Predicate so you don't have to serialize keys. In this > >> > case > >> > you > >> > wouldn't want to include keys in this Predicate as all keys would be > >> > serialized to all nodes and then you still have to iterate and check > >> > the > >> > entire data container/store. > >> > > >> > You could actually do both as well. So if you only want a subset of > >> > known > >> > keys where their values match a Predicate this can be done too. > >> > > >> > cache.lockedStream().filterKeys(keys).filter(predicate).forEach(); > >> > > >> >> > >> >> > >> >> > >> >> > > >> >> > Cheers > >> >> > Dan > >> >> > > >> >> > > >> >> > On Tue, Mar 21, 2017 at 5:37 PM, William Burns > >> >> > <mudokonman(a)gmail.com&gt; > >> >> > wrote: > >> >> >> Some users have expressed the need to have some sort of forEach > >> >> >> operation > >> >> >> that is performed where the Consumer is called while holding the > >> >> >> lock > >> >> >> for > >> >> >> the given key and subsequently released after the Consumer > >> >> >> operation > >> >> >> completes. > >> >> >> > >> >> >> Due to the nature of how streams work with retries and performing > >> >> >> the > >> >> >> operation on the primary owner, this works out quite well with > >> >> >> forEach > >> >> >> to be > >> >> >> done in an efficient way. > >> >> >> > >> >> >> The problem is that this only really works well with non tx and > >> >> >> pessimistic > >> >> >> tx. This obviously leaves out optimistic tx, which at first I was > >> >> >> a > >> >> >> little > >> >> >> worried about. But after thinking about it more, this prelocking > >> >> >> and > >> >> >> optimistic tx don't really fit that well together anyways. So I > >> >> >> am > >> >> >> thinking > >> >> >> whenever this operation is performed it would throw an exception > >> >> >> not > >> >> >> letting > >> >> >> the user use this feature in optimistic transactions. > >> >> >> > >> >> >> Another question is what does the API for this look like. I was > >> >> >> debating > >> >> >> between 3 options myself: > >> >> >> > >> >> >> 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, > >> >> >> V>> > >> >> >> consumer) > >> >> >> > >> >> >> This require the least amount of changes, however the user can't > >> >> >> customize > >> >> >> certain parameters that CacheStream currently provides (listed > >> >> >> below > >> >> >> - > >> >> >> big > >> >> >> one being filterKeys). > >> >> >> > >> >> >> 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, > >> >> >> V>> > >> >> >> consumer) > >> >> >> > >> >> >> This method would only be allowed to be invoked on the Stream if > >> >> >> no > >> >> >> other > >> >> >> intermediate operations were invoked, otherwise an exception > >> >> >> would > >> >> >> be > >> >> >> thrown. This still gives us access to all of the CacheStream > >> >> >> methods > >> >> >> that > >> >> >> aren't on the Stream interface (ie. sequentialDistribution, > >> >> >> parallelDistribution, parallel, sequential, filterKeys, > >> >> >> filterKeySegments, > >> >> >> distributedBatchSize, disableRehashAware, timeout). > >> >> >> > >> >> >> 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > >> >> >> > >> >> >> This requires the most changes, however the API would be the most > >> >> >> explicit. > >> >> >> In this case the LockedStream would only have the methods on it > >> >> >> that > >> >> >> are > >> >> >> able to be invoked as noted above and forEach. > >> >> >> > >> >> >> I personally feel that #3 might be the cleanest, but obviously > >> >> >> requires > >> >> >> adding more classes. Let me know what you guys think and if you > >> >> >> think > >> >> >> the > >> >> >> optimistic exclusion is acceptable. > >> >> >> > >> >> >> Thanks, > >> >> >> > >> >> >> - Will > >> >> >> > >> >> >> _______________________________________________ > >> >> >> infinispan-dev mailing list > >> >> >> infinispan-dev(a)lists.jboss.org > >> >> >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> >> > _______________________________________________ > >> >> > infinispan-dev mailing list > >> >> > infinispan-dev(a)lists.jboss.org > >> >> > https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> >> > >> >> > >> >> _______________________________________________ > >> >> infinispan-dev mailing list > >> >> infinispan-dev(a)lists.jboss.org > >> >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> > > >> > > >> > _______________________________________________ > >> > infinispan-dev mailing list > >> > infinispan-dev(a)lists.jboss.org > >> > https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> > >> _______________________________________________ > >> infinispan-dev mailing list > >> infinispan-dev(a)lists.jboss.org > >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > > > > > > _______________________________________________ > > infinispan-dev mailing list > > infinispan-dev(a)lists.jboss.org > > https://lists.jboss.org/mailman/listinfo/infinispan-dev > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On Wed, Mar 29, 2017 at 4:05 AM Dan Berindei <dan.berindei(a)gmail.com&gt; wrote: > > On Tue, Mar 28, 2017 at 8:54 PM, William Burns <mudokonman(a)gmail.com&gt; > wrote: > > > > > > On Tue, Mar 28, 2017 at 12:52 PM Dan Berindei <dan.berindei(a)gmail.com&gt; > > wrote: > >> > >> On Tue, Mar 28, 2017 at 6:44 PM, William Burns <mudokonman(a)gmail.com&gt; > >> wrote: > >> > > >> > > >> > On Tue, Mar 28, 2017 at 11:24 AM Sanne Grinovero > >> > <sanne(a)infinispan.org&gt; > >> > wrote: > >> >> > >> >> Hi Will, > >> >> > >> >> I'm confused about the premise; when you state > >> >> > >> >> " the Consumer is called while holding the lock for the given key > >> >> and > >> >> subsequently released after the Consumer operation completes." > >> >> > >> >> What are the transaction boundaries? > >> >> I see two options, please correct me so I understand: > >> >> > >> >> A) > >> >> > >> >> transaction.begin(); > >> >> cache.lockedStream().filterKeys(keys).filter(predicate).forEach( > >> >> someOperation ); > >> >> transaction.commit(); <-- release all locks > >> >> > >> >> B) > >> >> > >> >> cache.lockedStream().filterKeys(keys).filter(predicate).forEach( > >> >> transaction.begin(); > >> >> //to stuff on entry > >> >> /transaction.commit(); <-- release this single entry's lock > >> >> ); > >> > > >> > > >> > The user code doesn't really affect this, it is done internally by > >> > Infinispan. We would acquire the lock on the user's behalf in the > >> > stream > >> > operation then call the user's accept method. Then after they return > >> > we > >> > would unlock the lock. The way I have it implemented at the moment in > >> > my > >> > PoC > >> > (which could change) is I don't even start a transaction. It just > >> > locks > >> > the > >> > key and then if the user were to invoke an operation that requires a > >> > transaction it adds the lock owner to their tx context at that point > >> > so > >> > they > >> > have ownership of the key. > >> > > >> > Also to note that a commit or rollback in the Consumer currently > >> > doesn't > >> > release the lock on the key. Although this could be discussed to be > >> > possibly > >> > changed. > >> > > >> > >> With a transactional cache I was assuming you manage the transaction > >> yourself... if the user has to call > >> transactionManager.begin()/commit()/rollback() anyway, why not use a > >> regular stream? > > > > > > The user would be using an implicit transaction or explicit. Like I said > > this is up for discussion. The main reason I am staying away from > > managing > > the transaction is that the user can mess with the transaction as well > > which > > would possibly release the lock. It is much simpler if all I am doing is > > managing the lock. And if the user doesn't require a transaction in > > Infinispan we didn't waste time starting one and releasing one. > > > > Every write to a transactional cache will start an implicit > transaction, so I don't think we really have the option of not > starting a transaction. Yes a write to it will, but the stream stuff doesn't write to it, it just locks. So if the user doesn't have to actually write to the cache, they may want to just update a 3rd party system for example.

> > > >> > >> > >> >> > >> >> > >> >> > >> >> I think it's important to clarify this as I suspect that #A is not > >> >> implementable within reasonable guarantees, while in the case of B# > >> >> I > >> >> see no use for optimistic locking *from a user's perspective*. > >> > > >> > > >> > Exactly my thoughts regarding optimistic. I don't think #A is even > >> > feasible > >> > given constraints of having a distributed transaction like this. > >> > > >> > >> Totally agree that #A can't work with any kind of transaction > >> configuration. > >> > >> As to optimistic locking, I would like having "feature parity" between > >> pessimistic and optimistic caches as much as possible, but I agree > >> locking eagerly and retrying the consumer on WriteSkewException are a > >> bit too different to fit under the same API. > > > > > > Yeah I would definitely like to have it as well, but I just can't see > > how it > > fits in. This is despite the implementation detail that it is quite > > difficult to get it working currently :D > > > >> > >> > >> >> > >> >> > >> >> Also: what kind of guarantees do you expect about having the > >> >> operation > >> >> being applied on some entry which is strictly *still* a subset of > >> >> the > >> >> keys as defined by the filter predicates? > >> >> I take it you'd want to acquire the locks during the filtering > >> >> process? > >> > > >> > > >> > That is a good question. I hadn't thought about the details but what > >> > I > >> > had > >> > implemented was we have to first read the entry, lock the key, reread > >> > the > >> > entry (in case of concurrent update) and then finally call their > >> > Predicate. > >> > Another reason the filterKeys is much more efficient :) Note this > >> > read, > >> > locking and reread is done even without a Predicate supplied. And > >> > actually I > >> > can also optimize filterKeys to not do the initial read since we > >> > already > >> > have the key. > >> > > >> > >> Would this be more efficient than the consumer reading the key with > >> FORCE_WRITE_LOCK and deciding what to do based on the value? > >> > > > > The problem with this is you have to go remote to lock the key, return > > the > > value then do something for every key (not to mention pulling those keys > > using an iterator). Very costly! The main benefit of the stream with > > lock is > > that you are performing everything on the primary owner of the data with > > the > > lock already acquired. The only piece sent remotely is the consumer and > > some > > internal classes, very light weight and you have all the benefits of > > data > > locality. > > > > I meant using cache.withFlags(FORCE_WRITE_LOCK).get(key) in the > Consumer itself, and assuming it runs on the primary owner. Ah yes you could for pessimistic, but not optimistic or nontx :( In this case it would be very similar. > > > >> > >> >> > >> >> > >> >> That would require the move the transaction boundary to the scenario > >> >> A# which seems undesirable. > >> >> Technically if I were to need something like this I guess I'd expect > >> >> to have a user experience akin to B# but have Infinispan essentially > >> >> use optimistic locking (and auto-skip) on entries which are mutated > >> >> and fall out of the filter predicate during the lock attempt. > >> >> > >> >> Essentially I suspect that we'd not want to implement different > >> >> versions of this depending on the transaction mode, but figure out > >> >> the > >> >> use case and implement a one and only transaction mode which suites > >> >> such use cases. So for example we'd simply not offer a mode which > >> >> requires to copy the whole grid into the current TX context. > >> > > >> > > >> > This was never the intent and in my follow up emails I came to what > >> > seems > >> > like the same conclusion that basically this can't be done with the > >> > user > >> > controlling the transaction and it doesn't really make sense in an > >> > optimistic transaction (since you are already at that node, you are > >> > already > >> > doing everything pessimistically). > >> > > >> > >> Even local caches can use optimistic locking :) > > > > > > Yes I know :) I was just framing it in the notion of remote. If anyone > > can > > think of a nice way of using this with optimistic transactions I would > > all > > be for it. But optimistic transactions just doesn't make any sense to me > > when you are locking a key eagerly for someone to do something with it > > (definition of pessimistic transaction). > > > > Maybe I didn't explain properly... > > I meant in optimistic caches we wouldn't acquire the lock at all. The > stream would just start an optimistic transaction, run the consumer, > and try to commit. If the prepare fails because of a > WriteSkewException, start from the beginning. This assumes the user will be updating the cache, I am not sure we can always assume that (in regards to starting a transaction). But this is a good point (I misunderstood earlier), it should be pretty easy to just catch WriteSkewException and retry the given Consumer with the new entry (if it exists still). > > > >> > >> > >> >> > >> >> > >> >> Thanks, > >> >> Sanne > >> >> > >> >> > >> >> > >> >> On 28 March 2017 at 14:49, William Burns <mudokonman(a)gmail.com&gt; > >> >> wrote: > >> >> > > >> >> > > >> >> > On Mon, Mar 27, 2017 at 9:02 PM Galder Zamarreño > >> >> > <galder(a)redhat.com&gt; > >> >> > wrote: > >> >> >> > >> >> >> > >> >> >> -- > >> >> >> Galder Zamarreño > >> >> >> Infinispan, Red Hat > >> >> >> > >> >> >> > On 21 Mar 2017, at 17:16, Dan Berindei <dan.berindei(a)gmail.com&gt; > >> >> >> > wrote: > >> >> >> > > >> >> >> > I'm leaning towards option 1. > >> >> >> > > >> >> >> > Are you thinking about also allowing the consumer to modify the > >> >> >> > entry, > >> >> >> > like JCache's EntryProcessors? For a consumer that can only > >> >> >> > modify > >> >> >> > the > >> >> >> > current entry, we could even "emulate" locking in an optimistic > >> >> >> > cache > >> >> >> > by catching the WriteSkewException and running the consumer > >> >> >> > again. > >> >> >> > > >> >> >> > I wouldn't allow this to be mixed with other operations in a > >> >> >> > stream, > >> >> >> > because then you may have to run filters/mappers/sorting while > >> >> >> > holding > >> >> >> > the lock as well. > >> >> >> > >> >> >> ^ Would forEach w/ lock still run for all entries in originator? > >> >> >> If > >> >> >> so, > >> >> >> not being able to filter could be a pain. IOW, you'd be forcing > >> >> >> all > >> >> >> entries > >> >> >> to be shipped to a node and user to do its own filtering. Not > >> >> >> ideal > >> >> >> :\ > >> >> > > >> >> > > >> >> > No the primary owner would run the operation per entry. I was > >> >> > thinking > >> >> > we > >> >> > would have 2 levels of filtering in my proposal above. > >> >> > > >> >> > We would have the first one which is using filterKeys on the > >> >> > CacheStream > >> >> > method. This requires serializing keys sent to each node (only > >> >> > primary > >> >> > owned > >> >> > keys are sent). While it has the cost of serialization it makes up > >> >> > for > >> >> > by > >> >> > having constant time lookups (no iterating memory/stores) for the > >> >> > keys > >> >> > as it > >> >> > creates a stream using Cache.get to populate it. > >> >> > > >> >> > The second was to support the filter method on the Stream API > >> >> > which > >> >> > would > >> >> > allow for a Predicate so you don't have to serialize keys. In this > >> >> > case > >> >> > you > >> >> > wouldn't want to include keys in this Predicate as all keys would > >> >> > be > >> >> > serialized to all nodes and then you still have to iterate and > >> >> > check > >> >> > the > >> >> > entire data container/store. > >> >> > > >> >> > You could actually do both as well. So if you only want a subset > >> >> > of > >> >> > known > >> >> > keys where their values match a Predicate this can be done too. > >> >> > > >> >> > cache.lockedStream().filterKeys(keys).filter(predicate).forEach(); > >> >> > > >> >> >> > >> >> >> > >> >> >> > >> >> >> > > >> >> >> > Cheers > >> >> >> > Dan > >> >> >> > > >> >> >> > > >> >> >> > On Tue, Mar 21, 2017 at 5:37 PM, William Burns > >> >> >> > <mudokonman(a)gmail.com&gt; > >> >> >> > wrote: > >> >> >> >> Some users have expressed the need to have some sort of > >> >> >> >> forEach > >> >> >> >> operation > >> >> >> >> that is performed where the Consumer is called while holding > >> >> >> >> the > >> >> >> >> lock > >> >> >> >> for > >> >> >> >> the given key and subsequently released after the Consumer > >> >> >> >> operation > >> >> >> >> completes. > >> >> >> >> > >> >> >> >> Due to the nature of how streams work with retries and > >> >> >> >> performing > >> >> >> >> the > >> >> >> >> operation on the primary owner, this works out quite well with > >> >> >> >> forEach > >> >> >> >> to be > >> >> >> >> done in an efficient way. > >> >> >> >> > >> >> >> >> The problem is that this only really works well with non tx > >> >> >> >> and > >> >> >> >> pessimistic > >> >> >> >> tx. This obviously leaves out optimistic tx, which at first I > >> >> >> >> was > >> >> >> >> a > >> >> >> >> little > >> >> >> >> worried about. But after thinking about it more, this > >> >> >> >> prelocking > >> >> >> >> and > >> >> >> >> optimistic tx don't really fit that well together anyways. So > >> >> >> >> I > >> >> >> >> am > >> >> >> >> thinking > >> >> >> >> whenever this operation is performed it would throw an > >> >> >> >> exception > >> >> >> >> not > >> >> >> >> letting > >> >> >> >> the user use this feature in optimistic transactions. > >> >> >> >> > >> >> >> >> Another question is what does the API for this look like. I > >> >> >> >> was > >> >> >> >> debating > >> >> >> >> between 3 options myself: > >> >> >> >> > >> >> >> >> 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, > >> >> >> >> CacheEntry<K, > >> >> >> >> V>> > >> >> >> >> consumer) > >> >> >> >> > >> >> >> >> This require the least amount of changes, however the user > >> >> >> >> can't > >> >> >> >> customize > >> >> >> >> certain parameters that CacheStream currently provides (listed > >> >> >> >> below > >> >> >> >> - > >> >> >> >> big > >> >> >> >> one being filterKeys). > >> >> >> >> > >> >> >> >> 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, > >> >> >> >> V>> > >> >> >> >> consumer) > >> >> >> >> > >> >> >> >> This method would only be allowed to be invoked on the Stream > >> >> >> >> if > >> >> >> >> no > >> >> >> >> other > >> >> >> >> intermediate operations were invoked, otherwise an exception > >> >> >> >> would > >> >> >> >> be > >> >> >> >> thrown. This still gives us access to all of the CacheStream > >> >> >> >> methods > >> >> >> >> that > >> >> >> >> aren't on the Stream interface (ie. sequentialDistribution, > >> >> >> >> parallelDistribution, parallel, sequential, filterKeys, > >> >> >> >> filterKeySegments, > >> >> >> >> distributedBatchSize, disableRehashAware, timeout). > >> >> >> >> > >> >> >> >> 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > >> >> >> >> > >> >> >> >> This requires the most changes, however the API would be the > >> >> >> >> most > >> >> >> >> explicit. > >> >> >> >> In this case the LockedStream would only have the methods on > >> >> >> >> it > >> >> >> >> that > >> >> >> >> are > >> >> >> >> able to be invoked as noted above and forEach. > >> >> >> >> > >> >> >> >> I personally feel that #3 might be the cleanest, but obviously > >> >> >> >> requires > >> >> >> >> adding more classes. Let me know what you guys think and if > >> >> >> >> you > >> >> >> >> think > >> >> >> >> the > >> >> >> >> optimistic exclusion is acceptable. > >> >> >> >> > >> >> >> >> Thanks, > >> >> >> >> > >> >> >> >> - Will > >> >> >> >> > >> >> >> >> _______________________________________________ > >> >> >> >> infinispan-dev mailing list > >> >> >> >> infinispan-dev(a)lists.jboss.org > >> >> >> >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> >> >> > _______________________________________________ > >> >> >> > infinispan-dev mailing list > >> >> >> > infinispan-dev(a)lists.jboss.org > >> >> >> > https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> >> >> > >> >> >> > >> >> >> _______________________________________________ > >> >> >> infinispan-dev mailing list > >> >> >> infinispan-dev(a)lists.jboss.org > >> >> >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> >> > > >> >> > > >> >> > _______________________________________________ > >> >> > infinispan-dev mailing list > >> >> > infinispan-dev(a)lists.jboss.org > >> >> > https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> >> > >> >> _______________________________________________ > >> >> infinispan-dev mailing list > >> >> infinispan-dev(a)lists.jboss.org > >> >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> > > >> > > >> > _______________________________________________ > >> > infinispan-dev mailing list > >> > infinispan-dev(a)lists.jboss.org > >> > https://lists.jboss.org/mailman/listinfo/infinispan-dev > >> > >> _______________________________________________ > >> infinispan-dev mailing list > >> infinispan-dev(a)lists.jboss.org > >> https://lists.jboss.org/mailman/listinfo/infinispan-dev > > > > > > _______________________________________________ > > infinispan-dev mailing list > > infinispan-dev(a)lists.jboss.org > > https://lists.jboss.org/mailman/listinfo/infinispan-dev > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On 03/21/2017 04:37 PM, William Burns wrote: > Some users have expressed the need to have some sort of forEach > operation that is performed where the Consumer is called while holding > the lock for the given key and subsequently released after the > Consumer operation completes. Seconding Dan's question - is that intended to be able to modify the entry? In my opinion, sending a function that will work on the ReadWriteEntryView directly to the node is the only reasonable request. I wouldn't like to see blocking operations in there.

> > Due to the nature of how streams work with retries and performing the > operation on the primary owner, this works out quite well with forEach > to be done in an efficient way. > > The problem is that this only really works well with non tx and > pessimistic tx. This obviously leaves out optimistic tx, which at > first I was a little worried about. But after thinking about it more, > this prelocking and optimistic tx don't really fit that well together > anyways. So I am thinking whenever this operation is performed it > would throw an exception not letting the user use this feature in > optimistic transactions. How exactly reading streams interacts with transactions? Does it wrap read entries into context? This would be a scalability issue.

I agree that "locking" should not be exposed with optimistic transactions.

With pessimistic transactions, how do you expect to handle locking order? For regular operations, user is responsible for setting up some locking order in order to not get a deadlock. With pessimistic transaction, it's the cache itself who will order the calls. Also, if you lock anything that is read, you just end up locking everything (or, getting a deadlock). If you don't it's the same as issuing the lock and reading again (to check the locked value) - but you'd do that internally anyway. Therefore, I don't feel well about pessimistic transactions neither.

> > Another question is what does the API for this look like. I was > debating between 3 options myself: > > 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > consumer) > > This require the least amount of changes, however the user can't > customize certain parameters that CacheStream currently provides > (listed below - big one being filterKeys). > > 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > consumer) > > This method would only be allowed to be invoked on the Stream if no > other intermediate operations were invoked, otherwise an exception > would be thrown. This still gives us access to all of the CacheStream > methods that aren't on the Stream interface (ie. > sequentialDistribution, parallelDistribution, parallel, sequential, > filterKeys, filterKeySegments, distributedBatchSize, > disableRehashAware, timeout). For both options, I don't like Cache being passed around. You should modify the CacheEntry (or some kind of view) directly.

Radim > > 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > > This requires the most changes, however the API would be the most > explicit. In this case the LockedStream would only have the methods on > it that are able to be invoked as noted above and forEach. > > I personally feel that #3 might be the cleanest, but obviously > requires adding more classes. Let me know what you guys think and if > you think the optimistic exclusion is acceptable. > > Thanks, > > - Will > > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev -- Radim Vansa <rvansa(a)redhat.com&gt; JBoss Performance Team _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On Tue, Mar 21, 2017 at 1:42 PM William Burns <mudokonman(a)gmail.com <mailto:mudokonman@gmail.com>> wrote: On Tue, Mar 21, 2017 at 12:53 PM Radim Vansa <rvansa(a)redhat.com <mailto:rvansa@redhat.com>> wrote: On 03/21/2017 04:37 PM, William Burns wrote: > Some users have expressed the need to have some sort of forEach > operation that is performed where the Consumer is called while holding > the lock for the given key and subsequently released after the > Consumer operation completes. Seconding Dan's question - is that intended to be able to modify the entry? In my opinion, sending a function that will work on the ReadWriteEntryView directly to the node is the only reasonable request. I wouldn't like to see blocking operations in there. Hrmm the user can use the FunctionalMap interface for this then it seems? I wonder if this should just be the going in API. I will need to discuss with Galder the semantics of the evalAll/evalMany methods. Actually looking at evalAll it seems it doesn't scale as it keeps all entries in memory at once, so this is only for caches with a limited amount of entries.

> > Due to the nature of how streams work with retries and performing the > operation on the primary owner, this works out quite well with forEach > to be done in an efficient way. > > The problem is that this only really works well with non tx and > pessimistic tx. This obviously leaves out optimistic tx, which at > first I was a little worried about. But after thinking about it more, > this prelocking and optimistic tx don't really fit that well together > anyways. So I am thinking whenever this operation is performed it > would throw an exception not letting the user use this feature in > optimistic transactions. How exactly reading streams interacts with transactions? Does it wrap read entries into context? This would be a scalability issue. It doesn't wrap read entries into the context for that exact reason. It does however use existing entries in the context to override ones in memory/store.

I agree that "locking" should not be exposed with optimistic transactions. Yeah I can't find a good way to do this really and it seems to be opposite of what optimistic transactions are. With pessimistic transactions, how do you expect to handle locking order? For regular operations, user is responsible for setting up some locking order in order to not get a deadlock. With pessimistic transaction, it's the cache itself who will order the calls. Also, if you lock anything that is read, you just end up locking everything (or, getting a deadlock). If you don't it's the same as issuing the lock and reading again (to check the locked value) - but you'd do that internally anyway. Therefore, I don't feel well about pessimistic transactions neither. The lock is done per key only for each invocation. There is no ordering as only one is obtained at a time before it goes to the next. If the user then acquires a lock for another key while in the Consumer this could cause a deadlock if the inverse occurs on a different thread/node, but this is on the user. It is the same as it is today really, except we do the read lock for them before invoking their Consumer.

> > Another question is what does the API for this look like. I was > debating between 3 options myself: > > 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > consumer) > > This require the least amount of changes, however the user can't > customize certain parameters that CacheStream currently provides > (listed below - big one being filterKeys). > > 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> > consumer) > > This method would only be allowed to be invoked on the Stream if no > other intermediate operations were invoked, otherwise an exception > would be thrown. This still gives us access to all of the CacheStream > methods that aren't on the Stream interface (ie. > sequentialDistribution, parallelDistribution, parallel, sequential, > filterKeys, filterKeySegments, distributedBatchSize, > disableRehashAware, timeout). For both options, I don't like Cache being passed around. You should modify the CacheEntry (or some kind of view) directly. I don't know for sure if that is sufficient for the user. Sometimes they may modify another Cache given the value in this one for example, which they could access from the CacheManager of that Cache. Maybe Tristan knows more about some use cases.

Radim > > 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > > This requires the most changes, however the API would be the most > explicit. In this case the LockedStream would only have the methods on > it that are able to be invoked as noted above and forEach. > > I personally feel that #3 might be the cleanest, but obviously > requires adding more classes. Let me know what you guys think and if > you think the optimistic exclusion is acceptable. > > Thanks, > > - Will > > > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org <mailto:infinispan-dev@lists.jboss.org> > https://lists.jboss.org/mailman/listinfo/infinispan-dev -- Radim Vansa <rvansa(a)redhat.com <mailto:rvansa@redhat.com>> JBoss Performance Team _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org <mailto:infinispan-dev@lists.jboss.org> https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev

On 03/21/2017 06:50 PM, William Burns wrote: > > > On Tue, Mar 21, 2017 at 1:42 PM William Burns <mudokonman(a)gmail.com > <mailto:mudokonman@gmail.com>> wrote: > > On Tue, Mar 21, 2017 at 12:53 PM Radim Vansa <rvansa(a)redhat.com > <mailto:rvansa@redhat.com>> wrote: > > On 03/21/2017 04:37 PM, William Burns wrote: > > Some users have expressed the need to have some sort of forEach > > operation that is performed where the Consumer is called > while holding > > the lock for the given key and subsequently released after the > > Consumer operation completes. > > Seconding Dan's question - is that intended to be able to > modify the > entry? In my opinion, sending a function that will work on the > ReadWriteEntryView directly to the node is the only reasonable > request. > I wouldn't like to see blocking operations in there. > > > Hrmm the user can use the FunctionalMap interface for this then it > seems? I wonder if this should just be the going in API. I will > need to discuss with Galder the semantics of the evalAll/evalMany > methods. > > > Actually looking at evalAll it seems it doesn't scale as it keeps all > entries in memory at once, so this is only for caches with a limited > amount of entries. Don't look into the implementation; I think Galder has focused more on the API side than having optimal implementation. IMO there's no reason evalAll should load all the entries into memory in non-transactional mode.

> > > > > Due to the nature of how streams work with retries and > performing the > > operation on the primary owner, this works out quite well > with forEach > > to be done in an efficient way. > > > > The problem is that this only really works well with non tx and > > pessimistic tx. This obviously leaves out optimistic tx, > which at > > first I was a little worried about. But after thinking about > it more, > > this prelocking and optimistic tx don't really fit that well > together > > anyways. So I am thinking whenever this operation is > performed it > > would throw an exception not letting the user use this > feature in > > optimistic transactions. > > How exactly reading streams interacts with transactions? Does > it wrap > read entries into context? This would be a scalability issue. > > > It doesn't wrap read entries into the context for that exact > reason. It does however use existing entries in the context to > override ones in memory/store. > Uuh, so you end up with a copy of the cache in single invocation context, without any means to flush it. I think that we need add InvocationContext.current().forget(key) API (throwing exception if the entry was modified) or something like that, even for the regular streams. Maybe an override for filter methods, too, because you want to pass a nice predicate, but you can't just forget all filtered out entries.

> > I agree that "locking" should not be exposed with optimistic > transactions. > > > Yeah I can't find a good way to do this really and it seems to be > opposite of what optimistic transactions are. >

> > With pessimistic transactions, how do you expect to handle locking > order? For regular operations, user is responsible for setting > up some > locking order in order to not get a deadlock. With pessimistic > transaction, it's the cache itself who will order the calls. > Also, if > you lock anything that is read, you just end up locking > everything (or, > getting a deadlock). If you don't it's the same as issuing the > lock and > reading again (to check the locked value) - but you'd do that > internally > anyway. Therefore, I don't feel well about pessimistic > transactions neither. > > > The lock is done per key only for each invocation. There is no > ordering as only one is obtained at a time before it goes to the > next. If the user then acquires a lock for another key while in > the Consumer this could cause a deadlock if the inverse occurs on > a different thread/node, but this is on the user. It is the same > as it is today really, except we do the read lock for them before > invoking their Consumer. > In pessimistic mode, you should not release a lock before the end of the transaction.

> > > > > Another question is what does the API for this look like. I was > > debating between 3 options myself: > > > > 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, > CacheEntry<K, V>> > > consumer) > > > > This require the least amount of changes, however the user can't > > customize certain parameters that CacheStream currently provides > > (listed below - big one being filterKeys). > > > > 2. CacheStream.forEachWithLock(BiConsumer<Cache, > CacheEntry<K, V>> > > consumer) > > > > This method would only be allowed to be invoked on the > Stream if no > > other intermediate operations were invoked, otherwise an > exception > > would be thrown. This still gives us access to all of the > CacheStream > > methods that aren't on the Stream interface (ie. > > sequentialDistribution, parallelDistribution, parallel, > sequential, > > filterKeys, filterKeySegments, distributedBatchSize, > > disableRehashAware, timeout). > > For both options, I don't like Cache being passed around. You > should > modify the CacheEntry (or some kind of view) directly. > > > I don't know for sure if that is sufficient for the user. > Sometimes they may modify another Cache given the value in this > one for example, which they could access from the CacheManager of > that Cache. Maybe Tristan knows more about some use cases. > Rather than guessing what could the user need, the Consumer could be CDI enabled.

> > Radim > > > > > 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() > > > > This requires the most changes, however the API would be the > most > > explicit. In this case the LockedStream would only have the > methods on > > it that are able to be invoked as noted above and forEach. > > > > I personally feel that #3 might be the cleanest, but obviously > > requires adding more classes. Let me know what you guys > think and if > > you think the optimistic exclusion is acceptable. > > > > Thanks, > > > > - Will > >

Some users have expressed the need to have some sort of forEach operation that is performed where the Consumer is called while holding the lock for the given key and subsequently released after the Consumer operation completes. Due to the nature of how streams work with retries and performing the operation on the primary owner, this works out quite well with forEach 1. AdvancedCache.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> consumer) This require the least amount of changes, however the user can't customize certain parameters that CacheStream currently provides (listed below - big one being filterKeys). 2. CacheStream.forEachWithLock(BiConsumer<Cache, CacheEntry<K, V>> consumer) This method would only be allowed to be invoked on the Stream if no other intermediate operations were invoked, otherwise an exception would be thrown. This still gives us access to all of the CacheStream methods that aren't on the Stream interface (ie. sequentialDistribution, parallelDistribution, parallel, sequential, filterKeys, filterKeySegments, distributedBatchSize, disableRehashAware, timeout). 3. LockedStream<CacheEntry<K, V>> AdvancedCache.lockedStream() This requires the most changes, however the API would be the most explicit. In this case the LockedStream would only have the methods on it that are able to be invoked as noted above and forEach. I personally feel that #3 might be the cleanest, but obviously requires adding more classes. Let me know what you guys think and if you think the optimistic exclusion is acceptable.