Hi everyone,
I agree that having IsolationLevel be determined at query-time is the ideal
design, but there are a few sticking points:
1.
There needs to be some way to communicate the IsolationLevel down to the
RocksDBStore itself, so that the query can respect it. Since stores are
"layered" in functionality (i.e. ChangeLoggingStore, MeteredStore, etc.),
we need some way to deliver that information to the bottom layer. For IQv2,
we can use the existing State#query() method, but IQv1 has no way to do
this.
A simple approach, which would potentially open up other options, would be
to add something like: ReadOnlyKeyValueStore<K, V>
readOnlyView(IsolationLevel isolationLevel) to ReadOnlyKeyValueStore (and
similar to ReadOnlyWindowStore, ReadOnlySessionStore, etc.).
2.
As mentioned above, RocksDB WriteBatches are not thread-safe, which causes
a problem if we want to provide READ_UNCOMMITTED Iterators. I also had a
look at RocksDB Transactions[1], but they solve a very different problem,
and have the same thread-safety issue.
One possible approach that I mentioned is chaining WriteBatches: every time
a new Interactive Query is received (i.e. readOnlyView, see above, is
called) we "freeze" the existing WriteBatch, and start a new one for new
writes. The Interactive Query queries the "chain" of previous WriteBatches
+ the underlying database; while the StreamThread starts writing to the
*new* WriteBatch. On-commit, the StreamThread would write *all*
WriteBatches in the chain to the database (that have not yet been written).
WriteBatches would be closed/freed only when they have been both committed,
and all open Interactive Queries on them have been closed. This would
require some reference counting.
Obviously a drawback of this approach is the potential for increased memory
usage: if an Interactive Query is long-lived, for example by doing a full
scan over a large database, or even just pausing in the middle of an
iteration, then the existing chain of WriteBatches could be kept around for
a long time, potentially forever.
--
A.
Going off on a tangent, it looks like in addition to supporting
READ_COMMITTED queries, we could go further and support REPEATABLE_READ
queries (i.e. where subsequent reads to the same key in the same
Interactive Query are guaranteed to yield the same value) by making use of
RocksDB Snapshots[2]. These are fairly lightweight, so the performance
impact is likely to be negligible, but they do require that the Interactive
Query session can be explicitly closed.
This could be achieved if we made the above readOnlyView interface look
more like:
interface ReadOnlyKeyValueView<K, V> implements ReadOnlyKeyValueStore<K,
V>, AutoCloseable {}
interface ReadOnlyKeyValueStore<K, V> {
...
ReadOnlyKeyValueView<K, V> readOnlyView(IsolationLevel isolationLevel);
}
But this would be a breaking change, as existing IQv1 queries are
guaranteed to never call store.close(), and therefore these would leak
memory under REPEATABLE_READ.
B.
One thing that's notable: MyRocks states that they support READ_COMMITTED
and REPEATABLE_READ, but they make no mention of READ_UNCOMMITTED[3][4].
This could be because doing so is technically difficult/impossible using
the primitives available in RocksDB.
--
Lucas, to address your points:
U1.
It's only "SHOULD" to permit alternative (i.e. non-RocksDB) implementations
of StateStore that do not support atomic writes. Obviously in those cases,
the guarantees Kafka Streams provides/expects would be relaxed. Do you
think we should require all implementations to support atomic writes?
U2.
Stores can support multiple IsolationLevels. As we've discussed above, the
ideal scenario would be to specify the IsolationLevel at query-time.
Failing that, I think the second-best approach is to define the
IsolationLevel for *all* queries based on the processing.mode, which is
what the default StateStoreContext#isolationLevel() achieves. Would you
prefer an alternative?
While the existing implementation is equivalent to READ_UNCOMMITTED, this
can yield unexpected results/errors under EOS, if a transaction is rolled
back. While this would be a change in behaviour for users, it would look
more like a bug fix than a breaking change. That said, we *could* make it
configurable, and default to the existing behaviour (READ_UNCOMMITTED)
instead of inferring it from the processing.mode?
N1, N2.
These were only primitives to avoid boxing costs, but since this is not a
performance sensitive area, it should be fine to change if that's desirable.
N3.
It's because the store "manages its own offsets", which includes both
committing the offset, *and providing it* via getCommittedOffset().
Personally, I think "managesOffsets" conveys this best, but I don't mind
changing it if the nomenclature is unclear.
Sorry for the massive emails/essays!
--
Nick
1: https://github.com/facebook/rocksdb/wiki/Transactions
2: https://github.com/facebook/rocksdb/wiki/Snapshot
3: https://github.com/facebook/mysql-5.6/wiki/Transaction-Isolation
4: https://mariadb.com/kb/en/myrocks-transactional-isolation/
On Mon, 18 Sept 2023 at 16:19, Lucas Brutschy
<lbruts...@confluent.io.invalid> wrote:
> Hi Nick,
>
> since I last read it in April, the KIP has become much cleaner and
> easier to read. Great work!
>
> It feels to me the last big open point is whether we can implement
> isolation level as a query parameter. I understand that there are
> implementation concerns, but as Colt says, it would be a great
> addition, and would also simplify the migration path for this change.
> Is the implementation problem you mentioned caused by the WriteBatch
> not having a notion of a snapshot, as the underlying DB iterator does?
> In that case, I am not sure a chain of WriteBatches as you propose
> would fully solve the problem, but maybe I didn't dig enough into the
> details to fully understand it.
>
> If it's not possible to implement it now, would it be an option to
> make sure in this KIP that we do not fully close the door on per-query
> isolation levels in the interface, as it may be possible to implement
> the missing primitives in RocksDB or Speedb in the future.
>
> Understanding:
>
> * U1) Why is it only "SHOULD" for changelogOffsets to be persisted
> atomically with the records?
> * U2) Don't understand the default implementation of `isolationLevel`.
> The isolation level should be a property of the underlying store, and
> not be defined by the default config? Existing stores probably don't
> guarantee READ_COMMITTED, so the default should be to return
> READ_UNCOMMITTED.
>
> Nits:
> * N1) Could `getComittedOffset` use an `OptionalLong` return type, to
> avoid the `null`?
> * N2) Could `apporixmateNumUncomittedBytes` use an `OptionalLong`
> return type, to avoid the `-1`?
> * N3) I don't understand why `managesOffsets` uses the 'manage' verb,
> whereas all other methods use the "commits" verb. I'd suggest
> `commitsOffsets`.
>
> Either way, it feels this KIP is very close to the finish line, I'm
> looking forward to seeing this in production!
>
> Cheers,
> Lucas
>
> On Mon, Sep 18, 2023 at 6:57 AM Colt McNealy <c...@littlehorse.io> wrote:
> >
> > > Making IsolationLevel a query-time constraint, rather than linking it
> to
> > the processing.guarantee.
> >
> > As I understand it, would this allow even a user of EOS to control
> whether
> > reading committed or uncommitted records? If so, I am highly in favor of
> > this.
> >
> > I know that I was one of the early people to point out the current
> > shortcoming that IQ reads uncommitted records, but just this morning I
> > realized a pattern we use which means that (for certain queries) our
> system
> > needs to be able to read uncommitted records, which is the current
> behavior
> > of Kafka Streams in EOS.***
> >
> > If IsolationLevel being a query-time decision allows for this, then that
> > would be amazing. I would also vote that the default behavior should be
> for
> > reading uncommitted records, because it is totally possible for a valid
> > application to depend on that behavior, and breaking it in a minor
> release
> > might be a bit strong.
> >
> > *** (Note, for the curious reader....) Our use-case/query pattern is a
> bit
> > complex, but reading "uncommitted" records is actually safe in our case
> > because processing is deterministic. Additionally, IQ being able to read
> > uncommitted records is crucial to enable "read your own writes" on our
> API:
> > Due to the deterministic processing, we send an "ack" to the client who
> > makes the request as soon as the processor processes the result. If they
> > can't read uncommitted records, they may receive a "201 - Created"
> > response, immediately followed by a "404 - Not Found" when doing a lookup
> > for the object they just created).
> >
> > Thanks,
> > Colt McNealy
> >
> > *Founder, LittleHorse.dev*
> >
> >
> > On Wed, Sep 13, 2023 at 9:19 AM Nick Telford <nick.telf...@gmail.com>
> wrote:
> >
> > > Addendum:
> > >
> > > I think we would also face the same problem with the approach John
> outlined
> > > earlier (using the record cache as a transaction buffer and flushing it
> > > straight to SST files). This is because the record cache (the
> ThreadCache
> > > class) is not thread-safe, so every commit would invalidate open IQ
> > > Iterators in the same way that RocksDB WriteBatches do.
> > > --
> > > Nick
> > >
> > > On Wed, 13 Sept 2023 at 16:58, Nick Telford <nick.telf...@gmail.com>
> > > wrote:
> > >
> > > > Hi Bruno,
> > > >
> > > > I've updated the KIP based on our conversation. The only things I've
> not
> > > > yet done are:
> > > >
> > > > 1. Using transactions under ALOS and EOS.
> > > > 2. Making IsolationLevel a query-time constraint, rather than
> linking it
> > > > to the processing.guarantee.
> > > >
> > > > There's a wrinkle that makes this a challenge: Interactive Queries
> that
> > > > open an Iterator, when using transactions and READ_UNCOMMITTED.
> > > > The problem is that under READ_UNCOMMITTED, queries need to be able
> to
> > > > read records from the currently uncommitted transaction buffer
> > > > (WriteBatch). This includes for Iterators, which should iterate both
> the
> > > > transaction buffer and underlying database (using
> > > > WriteBatch#iteratorWithBase()).
> > > >
> > > > The issue is that when the StreamThread commits, it writes the
> current
> > > > WriteBatch to RocksDB *and then clears the WriteBatch*. Clearing the
> > > > WriteBatch while an Interactive Query holds an open Iterator on it
> will
> > > > invalidate the Iterator. Worse, it turns out that Iterators over a
> > > > WriteBatch become invalidated not just when the WriteBatch is
> cleared,
> > > but
> > > > also when the Iterators' current key receives a new write.
> > > >
> > > > Now that I'm writing this, I remember that this is the major reason
> that
> > > I
> > > > switched the original design from having a query-time IsolationLevel
> to
> > > > having the IsolationLevel linked to the transactionality of the
> stores
> > > > themselves.
> > > >
> > > > It *might* be possible to resolve this, by having a "chain" of
> > > > WriteBatches, with the StreamThread switching to a new WriteBatch
> > > whenever
> > > > a new Interactive Query attempts to read from the database, but that
> > > could
> > > > cause some performance problems/memory pressure when subjected to a
> high
> > > > Interactive Query load. It would also reduce the efficiency of
> > > WriteBatches
> > > > on-commit, as we'd have to write N WriteBatches, where N is the
> number of
> > > > Interactive Queries since the last commit.
> > > >
> > > > I realise this is getting into the weeds of the implementation, and
> you'd
> > > > rather we focus on the API for now, but I think it's important to
> > > consider
> > > > how to implement the desired API, in case we come up with an API that
> > > > cannot be implemented efficiently, or even at all!
> > > >
> > > > Thoughts?
> > > > --
> > > > Nick
> > > >
> > > > On Wed, 13 Sept 2023 at 13:03, Bruno Cadonna <cado...@apache.org>
> wrote:
> > > >
> > > >> Hi Nick,
> > > >>
> > > >> 6.
> > > >> Of course, you are right! My bad!
> > > >> Wiping out the state in the downgrading case is fine.
> > > >>
> > > >>
> > > >> 3a.
> > > >> Focus on the public facing changes for the KIP. We will manage to
> get
> > > >> the internals right. Regarding state stores that do not support
> > > >> READ_COMMITTED, they should throw an error stating that they do not
> > > >> support READ_COMMITTED. No need to adapt all state stores
> immediately.
> > > >>
> > > >> 3b.
> > > >> I am in favor of using transactions also for ALOS.
> > > >>
> > > >>
> > > >> Best,
> > > >> Bruno
> > > >>
> > > >> On 9/13/23 11:57 AM, Nick Telford wrote:
> > > >> > Hi Bruno,
> > > >> >
> > > >> > Thanks for getting back to me!
> > > >> >
> > > >> > 2.
> > > >> > The fact that implementations can always track estimated memory
> usage
> > > in
> > > >> > the wrapper is a good point. I can remove -1 as an option, and
> I'll
> > > >> clarify
> > > >> > the JavaDoc that 0 is not just for non-transactional stores,
> which is
> > > >> > currently misleading.
> > > >> >
> > > >> > 6.
> > > >> > The problem with catching the exception in the downgrade process
> is
> > > that
> > > >> > would require new code in the Kafka version being downgraded to.
> Since
> > > >> > users could conceivably downgrade to almost *any* older version of
> > > Kafka
> > > >> > Streams, I'm not sure how we could add that code?
> > > >> > The only way I can think of doing it would be to provide a
> dedicated
> > > >> > downgrade tool, that goes through every local store and removes
> the
> > > >> > offsets column families. But that seems like an unnecessary
> amount of
> > > >> extra
> > > >> > code to maintain just to handle a somewhat niche situation, when
> the
> > > >> > alternative (automatically wipe and restore stores) should be
> > > >> acceptable.
> > > >> >
> > > >> > 1, 4, 5: Agreed. I'll make the changes you've requested.
> > > >> >
> > > >> > 3a.
> > > >> > I agree that IsolationLevel makes more sense at query-time, and I
> > > >> actually
> > > >> > initially attempted to place the IsolationLevel at query-time,
> but I
> > > ran
> > > >> > into some problems:
> > > >> > - The key issue is that, under ALOS we're not staging writes in
> > > >> > transactions, so can't perform writes at the READ_COMMITTED
> isolation
> > > >> > level. However, this may be addressed if we decide to *always* use
> > > >> > transactions as discussed under 3b.
> > > >> > - IQv1 and IQv2 have quite different implementations. I remember
> > > having
> > > >> > some difficulty understanding the IQv1 internals, which made it
> > > >> difficult
> > > >> > to determine what needed to be changed. However, I *think* this
> can be
> > > >> > addressed for both implementations by wrapping the RocksDBStore
> in an
> > > >> > IsolationLevel-dependent wrapper, that overrides read methods
> (get,
> > > >> etc.)
> > > >> > to either read directly from the database or from the ongoing
> > > >> transaction.
> > > >> > But IQv1 might still be difficult.
> > > >> > - If IsolationLevel becomes a query constraint, then all other
> > > >> StateStores
> > > >> > will need to respect it, including the in-memory stores. This
> would
> > > >> require
> > > >> > us to adapt in-memory stores to stage their writes so they can be
> > > >> isolated
> > > >> > from READ_COMMITTTED queries. It would also become an important
> > > >> > consideration for third-party stores on upgrade, as without
> changes,
> > > >> they
> > > >> > would not support READ_COMMITTED queries correctly.
> > > >> >
> > > >> > Ultimately, I may need some help making the necessary change to
> IQv1
> > > to
> > > >> > support this, but I don't think it's fundamentally impossible, if
> we
> > > >> want
> > > >> > to pursue this route.
> > > >> >
> > > >> > 3b.
> > > >> > The main reason I chose to keep ALOS un-transactional was to
> minimize
> > > >> > behavioural change for most users (I believe most Streams users
> use
> > > the
> > > >> > default configuration, which is ALOS). That said, it's clear that
> if
> > > >> ALOS
> > > >> > also used transactional stores, the only change in behaviour
> would be
> > > >> that
> > > >> > it would become *more correct*, which could be considered a "bug
> fix"
> > > by
> > > >> > users, rather than a change they need to handle.
> > > >> >
> > > >> > I believe that performance using transactions (aka. RocksDB
> > > >> WriteBatches)
> > > >> > should actually be *better* than the un-batched write-path that is
> > > >> > currently used[1]. The only "performance" consideration will be
> the
> > > >> > increased memory usage that transactions require. Given the
> > > mitigations
> > > >> for
> > > >> > this memory that we have in place, I would expect that this is
> not a
> > > >> > problem for most users.
> > > >> >
> > > >> > If we're happy to do so, we can make ALOS also use transactions.
> > > >> >
> > > >> > Regards,
> > > >> > Nick
> > > >> >
> > > >> > Link 1:
> > > >> >
> > >
> https://github.com/adamretter/rocksjava-write-methods-benchmark#results
> > > >> >
> > > >> > On Wed, 13 Sept 2023 at 09:41, Bruno Cadonna <cado...@apache.org>
> > > >> wrote:
> > > >> >
> > > >> >> Hi Nick,
> > > >> >>
> > > >> >> Thanks for the updates and sorry for the delay on my side!
> > > >> >>
> > > >> >>
> > > >> >> 1.
> > > >> >> Making the default implementation for flush() a no-op sounds
> good to
> > > >> me.
> > > >> >>
> > > >> >>
> > > >> >> 2.
> > > >> >> I think what was bugging me here is that a third-party state
> store
> > > >> needs
> > > >> >> to implement the state store interface. That means they need to
> > > >> >> implement a wrapper around the actual state store as we do for
> > > RocksDB
> > > >> >> with RocksDBStore. So, a third-party state store can always
> estimate
> > > >> the
> > > >> >> uncommitted bytes, if it wants, because the wrapper can record
> the
> > > >> added
> > > >> >> bytes.
> > > >> >> One case I can think of where returning -1 makes sense is when
> > > Streams
> > > >> >> does not need to estimate the size of the write batch and trigger
> > > >> >> extraordinary commits, because the third-party state store takes
> care
> > > >> of
> > > >> >> memory. But in that case the method could also just return 0.
> Even
> > > that
> > > >> >> case would be better solved with a method that returns whether
> the
> > > >> state
> > > >> >> store manages itself the memory used for uncommitted bytes or
> not.
> > > >> >> Said that, I am fine with keeping the -1 return value, I was just
> > > >> >> wondering when and if it will be used.
> > > >> >>
> > > >> >> Regarding returning 0 for transactional state stores when the
> batch
> > > is
> > > >> >> empty, I was just wondering because you explicitly stated
> > > >> >>
> > > >> >> "or {@code 0} if this StateStore does not support transactions."
> > > >> >>
> > > >> >> So it seemed to me returning 0 could only happen for
> > > non-transactional
> > > >> >> state stores.
> > > >> >>
> > > >> >>
> > > >> >> 3.
> > > >> >>
> > > >> >> a) What do you think if we move the isolation level to IQ (v1 and
> > > v2)?
> > > >> >> In the end this is the only component that really needs to
> specify
> > > the
> > > >> >> isolation level. It is similar to the Kafka consumer that can
> choose
> > > >> >> with what isolation level to read the input topic.
> > > >> >> For IQv1 the isolation level should go into
> StoreQueryParameters. For
> > > >> >> IQv2, I would add it to the Query interface.
> > > >> >>
> > > >> >> b) Point a) raises the question what should happen during
> > > at-least-once
> > > >> >> processing when the state store does not use transactions? John
> in
> > > the
> > > >> >> past proposed to also use transactions on state stores for
> > > >> >> at-least-once. I like that idea, because it avoids aggregating
> the
> > > same
> > > >> >> records over and over again in the case of a failure. We had a
> case
> > > in
> > > >> >> the past where a Streams applications in at-least-once mode was
> > > failing
> > > >> >> continuously for some reasons I do not remember before
> committing the
> > > >> >> offsets. After each failover, the app aggregated again and again
> the
> > > >> >> same records. Of course the aggregate increased to very wrong
> values
> > > >> >> just because of the failover. With transactions on the state
> stores
> > > we
> > > >> >> could have avoided this. The app would have output the same
> aggregate
> > > >> >> multiple times (i.e., after each failover) but at least the
> value of
> > > >> the
> > > >> >> aggregate would not depend on the number of failovers.
> Outputting the
> > > >> >> same aggregate multiple times would be incorrect under
> exactly-once
> > > but
> > > >> >> it is OK for at-least-once.
> > > >> >> If it makes sense to add a config to turn on and off
> transactions on
> > > >> >> state stores under at-least-once or just use transactions in any
> case
> > > >> is
> > > >> >> a question we should also discuss in this KIP. It depends a bit
> on
> > > the
> > > >> >> performance trade-off. Maybe to be safe, I would add a config.
> > > >> >>
> > > >> >>
> > > >> >> 4.
> > > >> >> Your points are all valid. I tend to say to keep the metrics
> around
> > > >> >> flush() until we remove flush() completely from the interface.
> Calls
> > > to
> > > >> >> flush() might still exist since existing processors might still
> call
> > > >> >> flush() explicitly as you mentioned in 1). For sure, we need to
> > > >> document
> > > >> >> how the metrics change due to the transactions in the upgrade
> notes.
> > > >> >>
> > > >> >>
> > > >> >> 5.
> > > >> >> I see. Then you should describe how the .position files are
> handled
> > > in
> > > >> >> a dedicated section of the KIP or incorporate the description in
> the
> > > >> >> "Atomic Checkpointing" section instead of only mentioning it in
> the
> > > >> >> "Compatibility, Deprecation, and Migration Plan".
> > > >> >>
> > > >> >>
> > > >> >> 6.
> > > >> >> Describing upgrading and downgrading in the KIP is a good idea.
> > > >> >> Regarding downgrading, I think you could also catch the
> exception and
> > > >> do
> > > >> >> what is needed to downgrade, e.g., drop the column family. See
> here
> > > for
> > > >> >> an example:
> > > >> >>
> > > >> >>
> > > >> >>
> > > >>
> > >
> https://github.com/apache/kafka/blob/63fee01366e6ce98b9dfafd279a45d40b80e282d/streams/src/main/java/org/apache/kafka/streams/state/internals/RocksDBTimestampedStore.java#L75
> > > >> >>
> > > >> >> It is a bit brittle, but it works.
> > > >> >>
> > > >> >>
> > > >> >> Best,
> > > >> >> Bruno
> > > >> >>
> > > >> >>
> > > >> >> On 8/24/23 12:18 PM, Nick Telford wrote:
> > > >> >>> Hi Bruno,
> > > >> >>>
> > > >> >>> Thanks for taking the time to review the KIP. I'm back from
> leave
> > > now
> > > >> and
> > > >> >>> intend to move this forwards as quickly as I can.
> > > >> >>>
> > > >> >>> Addressing your points:
> > > >> >>>
> > > >> >>> 1.
> > > >> >>> Because flush() is part of the StateStore API, it's exposed to
> > > custom
> > > >> >>> Processors, which might be making calls to flush(). This was
> > > actually
> > > >> the
> > > >> >>> case in a few integration tests.
> > > >> >>> To maintain as much compatibility as possible, I'd prefer not to
> > > make
> > > >> >> this
> > > >> >>> an UnsupportedOperationException, as it will cause previously
> > > working
> > > >> >>> Processors to start throwing exceptions at runtime.
> > > >> >>> I agree that it doesn't make sense for it to proxy commit(),
> though,
> > > >> as
> > > >> >>> that would cause it to violate the "StateStores commit only
> when the
> > > >> Task
> > > >> >>> commits" rule.
> > > >> >>> Instead, I think we should make this a no-op. That way, existing
> > > user
> > > >> >>> Processors will continue to work as-before, without violation of
> > > store
> > > >> >>> consistency that would be caused by premature flush/commit of
> > > >> StateStore
> > > >> >>> data to disk.
> > > >> >>> What do you think?
> > > >> >>>
> > > >> >>> 2.
> > > >> >>> As stated in the JavaDoc, when a StateStore implementation is
> > > >> >>> transactional, but is unable to estimate the uncommitted memory
> > > usage,
> > > >> >> the
> > > >> >>> method will return -1.
> > > >> >>> The intention here is to permit third-party implementations
> that may
> > > >> not
> > > >> >> be
> > > >> >>> able to estimate memory usage.
> > > >> >>>
> > > >> >>> Yes, it will be 0 when nothing has been written to the store
> yet. I
> > > >> >> thought
> > > >> >>> that was implied by "This method will return an approximation
> of the
> > > >> >> memory
> > > >> >>> would be freed by the next call to {@link #commit(Map)}" and
> > > "@return
> > > >> The
> > > >> >>> approximate size of all records awaiting {@link #commit(Map)}",
> > > >> however,
> > > >> >> I
> > > >> >>> can add it explicitly to the JavaDoc if you think this is
> unclear?
> > > >> >>>
> > > >> >>> 3.
> > > >> >>> I realise this is probably the most contentious point in my
> design,
> > > >> and
> > > >> >> I'm
> > > >> >>> open to changing it if I'm unable to convince you of the
> benefits.
> > > >> >>> Nevertheless, here's my argument:
> > > >> >>> The Interactive Query (IQ) API(s) are directly provided
> StateStores
> > > to
> > > >> >>> query, and it may be important for users to programmatically
> know
> > > >> which
> > > >> >>> mode the StateStore is operating under. If we simply provide an
> > > >> >>> "eosEnabled" boolean (as used throughout the internal streams
> > > >> engine), or
> > > >> >>> similar, then users will need to understand the operation and
> > > >> >> consequences
> > > >> >>> of each available processing mode and how it pertains to their
> > > >> >> StateStore.
> > > >> >>>
> > > >> >>> Interactive Query users aren't the only people that care about
> the
> > > >> >>> processing.mode/IsolationLevel of a StateStore: implementers of
> > > custom
> > > >> >>> StateStores also need to understand the behaviour expected of
> their
> > > >> >>> implementation. KIP-892 introduces some assumptions into the
> Streams
> > > >> >> Engine
> > > >> >>> about how StateStores operate under each processing mode, and
> it's
> > > >> >>> important that custom implementations adhere to those
> assumptions in
> > > >> >> order
> > > >> >>> to maintain the consistency guarantees.
> > > >> >>>
> > > >> >>> IsolationLevels provide a high-level contract on the behaviour
> of
> > > the
> > > >> >>> StateStore: a user knows that under READ_COMMITTED, they will
> see
> > > >> writes
> > > >> >>> only after the Task has committed, and under READ_UNCOMMITTED
> they
> > > >> will
> > > >> >> see
> > > >> >>> writes immediately. No understanding of the details of each
> > > >> >> processing.mode
> > > >> >>> is required, either for IQ users or StateStore implementers.
> > > >> >>>
> > > >> >>> An argument can be made that these contractual guarantees can
> simply
> > > >> be
> > > >> >>> documented for the processing.mode (i.e. that exactly-once and
> > > >> >>> exactly-once-v2 behave like READ_COMMITTED and at-least-once
> behaves
> > > >> like
> > > >> >>> READ_UNCOMMITTED), but there are several small issues with this
> I'd
> > > >> >> prefer
> > > >> >>> to avoid:
> > > >> >>>
> > > >> >>> - Where would we document these contracts, in a way that is
> > > >> difficult
> > > >> >>> for users/implementers to miss/ignore?
> > > >> >>> - It's not clear to users that the processing mode is
> > > >> communicating
> > > >> >>> an expectation of read isolation, unless they read the
> > > >> >> documentation. Users
> > > >> >>> rarely consult documentation unless they feel they need
> to, so
> > > >> it's
> > > >> >> likely
> > > >> >>> this detail would get missed by many users.
> > > >> >>> - It tightly couples processing modes to read isolation.
> Adding
> > > >> new
> > > >> >>> processing modes, or changing the read isolation of
> existing
> > > >> >> processing
> > > >> >>> modes would be difficult/impossible.
> > > >> >>>
> > > >> >>> Ultimately, the cost of introducing IsolationLevels is just a
> single
> > > >> >>> method, since we re-use the existing IsolationLevel enum from
> Kafka.
> > > >> This
> > > >> >>> gives us a clear place to document the contractual guarantees
> > > expected
> > > >> >>> of/provided by StateStores, that is accessible both by the
> > > StateStore
> > > >> >>> itself, and by IQ users.
> > > >> >>>
> > > >> >>> (Writing this I've just realised that the StateStore and IQ APIs
> > > >> actually
> > > >> >>> don't provide access to StateStoreContext that IQ users would
> have
> > > >> direct
> > > >> >>> access to... Perhaps StateStore should expose isolationLevel()
> > > itself
> > > >> >> too?)
> > > >> >>>
> > > >> >>> 4.
> > > >> >>> Yeah, I'm not comfortable renaming the metrics in-place either,
> as
> > > >> it's a
> > > >> >>> backwards incompatible change. My concern is that, if we leave
> the
> > > >> >> existing
> > > >> >>> "flush" metrics in place, they will be confusing to users. Right
> > > now,
> > > >> >>> "flush" metrics record explicit flushes to disk, but under
> KIP-892,
> > > >> even
> > > >> >> a
> > > >> >>> commit() will not explicitly flush data to disk - RocksDB will
> > > decide
> > > >> on
> > > >> >>> when to flush memtables to disk itself.
> > > >> >>>
> > > >> >>> If we keep the existing "flush" metrics, we'd have two options,
> > > which
> > > >> >> both
> > > >> >>> seem pretty bad to me:
> > > >> >>>
> > > >> >>> 1. Have them record calls to commit(), which would be
> > > >> misleading, as
> > > >> >>> data is no longer explicitly "flushed" to disk by this
> call.
> > > >> >>> 2. Have them record nothing at all, which is equivalent to
> > > >> removing
> > > >> >> the
> > > >> >>> metrics, except that users will see the metric still
> exists and
> > > >> so
> > > >> >> assume
> > > >> >>> that the metric is correct, and that there's a problem with
> > > their
> > > >> >> system
> > > >> >>> when there isn't.
> > > >> >>>
> > > >> >>> I agree that removing them is also a bad solution, and I'd like
> some
> > > >> >>> guidance on the best path forward here.
> > > >> >>>
> > > >> >>> 5.
> > > >> >>> Position files are updated on every write to a StateStore.
> Since our
> > > >> >> writes
> > > >> >>> are now buffered until commit(), we can't update the Position
> file
> > > >> until
> > > >> >>> commit() has been called, otherwise it would be inconsistent
> with
> > > the
> > > >> >> data
> > > >> >>> in the event of a rollback. Consequently, we need to manage
> these
> > > >> offsets
> > > >> >>> the same way we manage the checkpoint offsets, and ensure
> they're
> > > only
> > > >> >>> written on commit().
> > > >> >>>
> > > >> >>> 6.
> > > >> >>> Agreed, although I'm not exactly sure yet what tests to write.
> How
> > > >> >> explicit
> > > >> >>> do we need to be here in the KIP?
> > > >> >>>
> > > >> >>> As for upgrade/downgrade: upgrade is designed to be seamless,
> and we
> > > >> >> should
> > > >> >>> definitely add some tests around that. Downgrade, it transpires,
> > > isn't
> > > >> >>> currently possible, as the extra column family for offset
> storage is
> > > >> >>> incompatible with the pre-KIP-892 implementation: when you open
> a
> > > >> RocksDB
> > > >> >>> database, you must open all available column families or
> receive an
> > > >> >> error.
> > > >> >>> What currently happens on downgrade is that it attempts to open
> the
> > > >> >> store,
> > > >> >>> throws an error about the offsets column family not being
> opened,
> > > >> which
> > > >> >>> triggers a wipe and rebuild of the Task. Given that downgrades
> > > should
> > > >> be
> > > >> >>> uncommon, I think this is acceptable behaviour, as the
> end-state is
> > > >> >>> consistent, even if it results in an undesirable state restore.
> > > >> >>>
> > > >> >>> Should I document the upgrade/downgrade behaviour explicitly in
> the
> > > >> KIP?
> > > >> >>>
> > > >> >>> --
> > > >> >>>
> > > >> >>> Regards,
> > > >> >>> Nick
> > > >> >>>
> > > >> >>>
> > > >> >>> On Mon, 14 Aug 2023 at 22:31, Bruno Cadonna <cado...@apache.org
> >
> > > >> wrote:
> > > >> >>>
> > > >> >>>> Hi Nick!
> > > >> >>>>
> > > >> >>>> Thanks for the updates!
> > > >> >>>>
> > > >> >>>> 1.
> > > >> >>>> Why does StateStore#flush() default to
> > > >> >>>> StateStore#commit(Collections.emptyMap())?
> > > >> >>>> Since calls to flush() will not exist anymore after this KIP is
> > > >> >>>> released, I would rather throw an unsupported operation
> exception
> > > by
> > > >> >>>> default.
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> 2.
> > > >> >>>> When would a state store return -1 from
> > > >> >>>> StateStore#approximateNumUncommittedBytes() while being
> > > >> transactional?
> > > >> >>>>
> > > >> >>>> Wouldn't StateStore#approximateNumUncommittedBytes() also
> return 0
> > > if
> > > >> >>>> the state store is transactional but nothing has been written
> to
> > > the
> > > >> >>>> state store yet?
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> 3.
> > > >> >>>> Sorry for bringing this up again. Does this KIP really need to
> > > >> introduce
> > > >> >>>> StateStoreContext#isolationLevel()? StateStoreContext has
> already
> > > >> >>>> appConfigs() which basically exposes the same information,
> i.e., if
> > > >> EOS
> > > >> >>>> is enabled or not.
> > > >> >>>> In one of your previous e-mails you wrote:
> > > >> >>>>
> > > >> >>>> "My idea was to try to keep the StateStore interface as loosely
> > > >> coupled
> > > >> >>>> from the Streams engine as possible, to give implementers more
> > > >> freedom,
> > > >> >>>> and reduce the amount of internal knowledge required."
> > > >> >>>>
> > > >> >>>> While I understand the intent, I doubt that it decreases the
> > > >> coupling of
> > > >> >>>> a StateStore interface and the Streams engine. READ_COMMITTED
> only
> > > >> >>>> applies to IQ but not to reads by processors. Thus,
> implementers
> > > >> need to
> > > >> >>>> understand how Streams accesses the state stores.
> > > >> >>>>
> > > >> >>>> I would like to hear what others think about this.
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> 4.
> > > >> >>>> Great exposing new metrics for transactional state stores!
> > > However, I
> > > >> >>>> would prefer to add new metrics and deprecate (in the docs)
> the old
> > > >> >>>> ones. You can find examples of deprecated metrics here:
> > > >> >>>> https://kafka.apache.org/documentation/#selector_monitoring
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> 5.
> > > >> >>>> Why does the KIP mention position files? I do not think they
> are
> > > >> related
> > > >> >>>> to transactions or flushes.
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> 6.
> > > >> >>>> I think we will also need to adapt/add integration tests
> besides
> > > unit
> > > >> >>>> tests. Additionally, we probably need integration or system
> tests
> > > to
> > > >> >>>> verify that upgrades and downgrades between transactional and
> > > >> >>>> non-transactional state stores work as expected.
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> Best,
> > > >> >>>> Bruno
> > > >> >>>>
> > > >> >>>>
> > > >> >>>>
> > > >> >>>>
> > > >> >>>>
> > > >> >>>> On 7/21/23 10:34 PM, Nick Telford wrote:
> > > >> >>>>> One more thing: I noted John's suggestion in the KIP, under
> > > >> "Rejected
> > > >> >>>>> Alternatives". I still think it's an idea worth pursuing, but
> I
> > > >> believe
> > > >> >>>>> that it's out of the scope of this KIP, because it solves a
> > > >> different
> > > >> >> set
> > > >> >>>>> of problems to this KIP, and the scope of this one has already
> > > grown
> > > >> >>>> quite
> > > >> >>>>> large!
> > > >> >>>>>
> > > >> >>>>> On Fri, 21 Jul 2023 at 21:33, Nick Telford <
> > > nick.telf...@gmail.com>
> > > >> >>>> wrote:
> > > >> >>>>>
> > > >> >>>>>> Hi everyone,
> > > >> >>>>>>
> > > >> >>>>>> I've updated the KIP (
> > > >> >>>>>>
> > > >> >>>>
> > > >> >>
> > > >>
> > >
> https://cwiki.apache.org/confluence/display/KAFKA/KIP-892%3A+Transactional+Semantics+for+StateStores
> > > >> >>>> )
> > > >> >>>>>> with the latest changes; mostly bringing back "Atomic
> > > >> Checkpointing"
> > > >> >>>> (for
> > > >> >>>>>> what feels like the 10th time!). I think the one thing
> missing is
> > > >> some
> > > >> >>>>>> changes to metrics (notably the store "flush" metrics will
> need
> > > to
> > > >> be
> > > >> >>>>>> renamed to "commit").
> > > >> >>>>>>
> > > >> >>>>>> The reason I brought back Atomic Checkpointing was to
> decouple
> > > >> store
> > > >> >>>> flush
> > > >> >>>>>> from store commit. This is important, because with
> Transactional
> > > >> >>>>>> StateStores, we now need to call "flush" on *every* Task
> commit,
> > > >> and
> > > >> >> not
> > > >> >>>>>> just when the StateStore is closing, otherwise our
> transaction
> > > >> buffer
> > > >> >>>> will
> > > >> >>>>>> never be written and persisted, instead growing unbounded! I
> > > >> >>>> experimented
> > > >> >>>>>> with some simple solutions, like forcing a store flush
> whenever
> > > the
> > > >> >>>>>> transaction buffer was likely to exceed its configured size,
> but
> > > >> this
> > > >> >>>> was
> > > >> >>>>>> brittle: it prevented the transaction buffer from being
> > > configured
> > > >> to
> > > >> >> be
> > > >> >>>>>> unbounded, and it still would have required explicit flushes
> of
> > > >> >> RocksDB,
> > > >> >>>>>> yielding sub-optimal performance and memory utilization.
> > > >> >>>>>>
> > > >> >>>>>> I deemed Atomic Checkpointing to be the "right" way to
> resolve
> > > this
> > > >> >>>>>> problem. By ensuring that the changelog offsets that
> correspond
> > > to
> > > >> the
> > > >> >>>> most
> > > >> >>>>>> recently written records are always atomically written to the
> > > >> >> StateStore
> > > >> >>>>>> (by writing them to the same transaction buffer), we can
> avoid
> > > >> >> forcibly
> > > >> >>>>>> flushing the RocksDB memtables to disk, letting RocksDB flush
> > > them
> > > >> >> only
> > > >> >>>>>> when necessary, without losing any of our consistency
> guarantees.
> > > >> See
> > > >> >>>> the
> > > >> >>>>>> updated KIP for more info.
> > > >> >>>>>>
> > > >> >>>>>> I have fully implemented these changes, although I'm still
> not
> > > >> >> entirely
> > > >> >>>>>> happy with the implementation for segmented StateStores, so I
> > > plan
> > > >> to
> > > >> >>>>>> refactor that. Despite that, all tests pass. If you'd like
> to try
> > > >> out
> > > >> >> or
> > > >> >>>>>> review this highly experimental and incomplete branch, it's
> > > >> available
> > > >> >>>> here:
> > > >> >>>>>> https://github.com/nicktelford/kafka/tree/KIP-892-3.5.0.
> Note:
> > > >> it's
> > > >> >>>> built
> > > >> >>>>>> against Kafka 3.5.0 so that I had a stable base to build and
> test
> > > >> it
> > > >> >> on,
> > > >> >>>>>> and to enable easy apples-to-apples comparisons in a live
> > > >> >> environment. I
> > > >> >>>>>> plan to rebase it against trunk once it's nearer completion
> and
> > > has
> > > >> >> been
> > > >> >>>>>> proven on our main application.
> > > >> >>>>>>
> > > >> >>>>>> I would really appreciate help in reviewing and testing:
> > > >> >>>>>> - Segmented (Versioned, Session and Window) stores
> > > >> >>>>>> - Global stores
> > > >> >>>>>>
> > > >> >>>>>> As I do not currently use either of these, so my primary test
> > > >> >>>> environment
> > > >> >>>>>> doesn't test these areas.
> > > >> >>>>>>
> > > >> >>>>>> I'm going on Parental Leave starting next week for a few
> weeks,
> > > so
> > > >> >> will
> > > >> >>>>>> not have time to move this forward until late August. That
> said,
> > > >> your
> > > >> >>>>>> feedback is welcome and appreciated, I just won't be able to
> > > >> respond
> > > >> >> as
> > > >> >>>>>> quickly as usual.
> > > >> >>>>>>
> > > >> >>>>>> Regards,
> > > >> >>>>>> Nick
> > > >> >>>>>>
> > > >> >>>>>> On Mon, 3 Jul 2023 at 16:23, Nick Telford <
> > > nick.telf...@gmail.com>
> > > >> >>>> wrote:
> > > >> >>>>>>
> > > >> >>>>>>> Hi Bruno
> > > >> >>>>>>>
> > > >> >>>>>>> Yes, that's correct, although the impact on IQ is not
> something
> > > I
> > > >> had
> > > >> >>>>>>> considered.
> > > >> >>>>>>>
> > > >> >>>>>>> What about atomically updating the state store from the
> > > >> transaction
> > > >> >>>>>>>> buffer every commit interval and writing the checkpoint
> (thus,
> > > >> >>>> flushing
> > > >> >>>>>>>> the memtable) every configured amount of data and/or
> number of
> > > >> >> commit
> > > >> >>>>>>>> intervals?
> > > >> >>>>>>>>
> > > >> >>>>>>>
> > > >> >>>>>>> I'm not quite sure I follow. Are you suggesting that we add
> an
> > > >> >>>> additional
> > > >> >>>>>>> config for the max number of commit intervals between
> > > checkpoints?
> > > >> >> That
> > > >> >>>>>>> way, we would checkpoint *either* when the transaction
> buffers
> > > are
> > > >> >>>> nearly
> > > >> >>>>>>> full, *OR* whenever a certain number of commit intervals
> have
> > > >> >> elapsed,
> > > >> >>>>>>> whichever comes first?
> > > >> >>>>>>>
> > > >> >>>>>>> That certainly seems reasonable, although this re-ignites an
> > > >> earlier
> > > >> >>>>>>> debate about whether a config should be measured in "number
> of
> > > >> commit
> > > >> >>>>>>> intervals", instead of just an absolute time.
> > > >> >>>>>>>
> > > >> >>>>>>> FWIW, I realised that this issue is the reason I was
> pursuing
> > > the
> > > >> >>>> Atomic
> > > >> >>>>>>> Checkpoints, as it de-couples memtable flush from
> checkpointing,
> > > >> >> which
> > > >> >>>>>>> enables us to just checkpoint on every commit without any
> > > >> performance
> > > >> >>>>>>> impact. Atomic Checkpointing is definitely the "best"
> solution,
> > > >> but
> > > >> >>>> I'm not
> > > >> >>>>>>> sure if this is enough to bring it back into this KIP.
> > > >> >>>>>>>
> > > >> >>>>>>> I'm currently working on moving all the transactional logic
> > > >> directly
> > > >> >>>> into
> > > >> >>>>>>> RocksDBStore itself, which does away with the
> > > >> >> StateStore#newTransaction
> > > >> >>>>>>> method, and reduces the number of new classes introduced,
> > > >> >> significantly
> > > >> >>>>>>> reducing the complexity. If it works, and the complexity is
> > > >> >> drastically
> > > >> >>>>>>> reduced, I may try bringing back Atomic Checkpoints into
> this
> > > KIP.
> > > >> >>>>>>>
> > > >> >>>>>>> Regards,
> > > >> >>>>>>> Nick
> > > >> >>>>>>>
> > > >> >>>>>>> On Mon, 3 Jul 2023 at 15:27, Bruno Cadonna <
> cado...@apache.org>
> > > >> >> wrote:
> > > >> >>>>>>>
> > > >> >>>>>>>> Hi Nick,
> > > >> >>>>>>>>
> > > >> >>>>>>>> Thanks for the insights! Very interesting!
> > > >> >>>>>>>>
> > > >> >>>>>>>> As far as I understand, you want to atomically update the
> state
> > > >> >> store
> > > >> >>>>>>>> from the transaction buffer, flush the memtable of a state
> > > store
> > > >> and
> > > >> >>>>>>>> write the checkpoint not after the commit time elapsed but
> > > after
> > > >> the
> > > >> >>>>>>>> transaction buffer reached a size that would lead to
> exceeding
> > > >> >>>>>>>> statestore.transaction.buffer.max.bytes before the next
> commit
> > > >> >>>> interval
> > > >> >>>>>>>> ends.
> > > >> >>>>>>>> That means, the Kafka transaction would commit every commit
> > > >> interval
> > > >> >>>> but
> > > >> >>>>>>>> the state store will only be atomically updated roughly
> every
> > > >> >>>>>>>> statestore.transaction.buffer.max.bytes of data. Also IQ
> would
> > > >> then
> > > >> >>>> only
> > > >> >>>>>>>> see new data roughly every
> > > >> statestore.transaction.buffer.max.bytes.
> > > >> >>>>>>>> After a failure the state store needs to restore up to
> > > >> >>>>>>>> statestore.transaction.buffer.max.bytes.
> > > >> >>>>>>>>
> > > >> >>>>>>>> Is this correct?
> > > >> >>>>>>>>
> > > >> >>>>>>>> What about atomically updating the state store from the
> > > >> transaction
> > > >> >>>>>>>> buffer every commit interval and writing the checkpoint
> (thus,
> > > >> >>>> flushing
> > > >> >>>>>>>> the memtable) every configured amount of data and/or
> number of
> > > >> >> commit
> > > >> >>>>>>>> intervals? In such a way, we would have the same delay for
> > > >> records
> > > >> >>>>>>>> appearing in output topics and IQ because both would appear
> > > when
> > > >> the
> > > >> >>>>>>>> Kafka transaction is committed. However, after a failure
> the
> > > >> state
> > > >> >>>> store
> > > >> >>>>>>>> still needs to restore up to
> > > >> statestore.transaction.buffer.max.bytes
> > > >> >>>> and
> > > >> >>>>>>>> it might restore data that is already in the state store
> > > because
> > > >> the
> > > >> >>>>>>>> checkpoint lags behind the last stable offset (i.e. the
> last
> > > >> >> committed
> > > >> >>>>>>>> offset) of the changelog topics. Restoring data that is
> already
> > > >> in
> > > >> >> the
> > > >> >>>>>>>> state store is idempotent, so eos should not violated.
> > > >> >>>>>>>> This solution needs at least one new config to specify
> when a
> > > >> >>>> checkpoint
> > > >> >>>>>>>> should be written.
> > > >> >>>>>>>>
> > > >> >>>>>>>>
> > > >> >>>>>>>>
> > > >> >>>>>>>> A small correction to your previous e-mail that does not
> change
> > > >> >>>> anything
> > > >> >>>>>>>> you said: Under alos the default commit interval is 30
> seconds,
> > > >> not
> > > >> >>>> five
> > > >> >>>>>>>> seconds.
> > > >> >>>>>>>>
> > > >> >>>>>>>>
> > > >> >>>>>>>> Best,
> > > >> >>>>>>>> Bruno
> > > >> >>>>>>>>
> > > >> >>>>>>>>
> > > >> >>>>>>>> On 01.07.23 12:37, Nick Telford wrote:
> > > >> >>>>>>>>> Hi everyone,
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> I've begun performance testing my branch on our staging
> > > >> >> environment,
> > > >> >>>>>>>>> putting it through its paces in our non-trivial
> application.
> > > I'm
> > > >> >>>>>>>> already
> > > >> >>>>>>>>> observing the same increased flush rate that we saw the
> last
> > > >> time
> > > >> >> we
> > > >> >>>>>>>>> attempted to use a version of this KIP, but this time, I
> > > think I
> > > >> >> know
> > > >> >>>>>>>> why.
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> Pre-KIP-892, StreamTask#postCommit, which is called at
> the end
> > > >> of
> > > >> >> the
> > > >> >>>>>>>> Task
> > > >> >>>>>>>>> commit process, has the following behaviour:
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> - Under ALOS: checkpoint the state stores. This
> > > includes
> > > >> >>>>>>>>> flushing memtables in RocksDB. This is acceptable
> > > >> because the
> > > >> >>>>>>>> default
> > > >> >>>>>>>>> commit.interval.ms is 5 seconds, so forcibly
> flushing
> > > >> >> memtables
> > > >> >>>>>>>> every 5
> > > >> >>>>>>>>> seconds is acceptable for most applications.
> > > >> >>>>>>>>> - Under EOS: checkpointing is not done, *unless*
> it's
> > > >> being
> > > >> >>>>>>>> forced, due
> > > >> >>>>>>>>> to e.g. the Task closing or being revoked. This
> means
> > > >> that
> > > >> >> under
> > > >> >>>>>>>> normal
> > > >> >>>>>>>>> processing conditions, the state stores will not be
> > > >> >>>> checkpointed,
> > > >> >>>>>>>> and will
> > > >> >>>>>>>>> not have memtables flushed at all , unless RocksDB
> > > >> decides to
> > > >> >>>>>>>> flush them on
> > > >> >>>>>>>>> its own. Checkpointing stores and force-flushing
> their
> > > >> >> memtables
> > > >> >>>>>>>> is only
> > > >> >>>>>>>>> done when a Task is being closed.
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> Under EOS, KIP-892 needs to checkpoint stores on at least
> > > *some*
> > > >> >>>> normal
> > > >> >>>>>>>>> Task commits, in order to write the RocksDB transaction
> > > buffers
> > > >> to
> > > >> >>>> the
> > > >> >>>>>>>>> state stores, and to ensure the offsets are synced to
> disk to
> > > >> >> prevent
> > > >> >>>>>>>>> restores from getting out of hand. Consequently, my
> current
> > > >> >>>>>>>> implementation
> > > >> >>>>>>>>> calls maybeCheckpoint on *every* Task commit, which is
> far too
> > > >> >>>>>>>> frequent.
> > > >> >>>>>>>>> This causes checkpoints every 10,000 records, which is a
> > > change
> > > >> in
> > > >> >>>>>>>> flush
> > > >> >>>>>>>>> behaviour, potentially causing performance problems for
> some
> > > >> >>>>>>>> applications.
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> I'm looking into possible solutions, and I'm currently
> leaning
> > > >> >>>> towards
> > > >> >>>>>>>>> using the statestore.transaction.buffer.max.bytes
> > > configuration
> > > >> to
> > > >> >>>>>>>>> checkpoint Tasks once we are likely to exceed it. This
> would
> > > >> >>>>>>>> complement the
> > > >> >>>>>>>>> existing "early Task commit" functionality that this
> > > >> configuration
> > > >> >>>>>>>>> provides, in the following way:
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> - Currently, we use
> > > >> statestore.transaction.buffer.max.bytes
> > > >> >> to
> > > >> >>>>>>>> force an
> > > >> >>>>>>>>> early Task commit if processing more records would
> > > cause
> > > >> our
> > > >> >>>> state
> > > >> >>>>>>>> store
> > > >> >>>>>>>>> transactions to exceed the memory assigned to them.
> > > >> >>>>>>>>> - New functionality: when a Task *does* commit, we
> will
> > > >> not
> > > >> >>>>>>>> checkpoint
> > > >> >>>>>>>>> the stores (and hence flush the transaction
> buffers)
> > > >> unless
> > > >> >> we
> > > >> >>>>>>>> expect to
> > > >> >>>>>>>>> cross the statestore.transaction.buffer.max.bytes
> > > >> threshold
> > > >> >>>> before
> > > >> >>>>>>>> the next
> > > >> >>>>>>>>> commit
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> I'm also open to suggestions.
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> Regards,
> > > >> >>>>>>>>> Nick
> > > >> >>>>>>>>>
> > > >> >>>>>>>>> On Thu, 22 Jun 2023 at 14:06, Nick Telford <
> > > >> nick.telf...@gmail.com
> > > >> >>>
> > > >> >>>>>>>> wrote:
> > > >> >>>>>>>>>
> > > >> >>>>>>>>>> Hi Bruno!
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>> 3.
> > > >> >>>>>>>>>> By "less predictable for users", I meant in terms of
> > > >> understanding
> > > >> >>>> the
> > > >> >>>>>>>>>> performance profile under various circumstances. The more
> > > >> complex
> > > >> >>>> the
> > > >> >>>>>>>>>> solution, the more difficult it would be for users to
> > > >> understand
> > > >> >> the
> > > >> >>>>>>>>>> performance they see. For example, spilling records to
> disk
> > > >> when
> > > >> >> the
> > > >> >>>>>>>>>> transaction buffer reaches a threshold would, I expect,
> > > reduce
> > > >> >> write
> > > >> >>>>>>>>>> throughput. This reduction in write throughput could be
> > > >> >> unexpected,
> > > >> >>>>>>>> and
> > > >> >>>>>>>>>> potentially difficult to diagnose/understand for users.
> > > >> >>>>>>>>>> At the moment, I think the "early commit" concept is
> > > relatively
> > > >> >>>>>>>>>> straightforward; it's easy to document, and conceptually
> > > fairly
> > > >> >>>>>>>> obvious to
> > > >> >>>>>>>>>> users. We could probably add a metric to make it easier
> to
> > > >> >>>> understand
> > > >> >>>>>>>> when
> > > >> >>>>>>>>>> it happens though.
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>> 3. (the second one)
> > > >> >>>>>>>>>> The IsolationLevel is *essentially* an indirect way of
> > > telling
> > > >> >>>>>>>> StateStores
> > > >> >>>>>>>>>> whether they should be transactional. READ_COMMITTED
> > > >> essentially
> > > >> >>>>>>>> requires
> > > >> >>>>>>>>>> transactions, because it dictates that two threads
> calling
> > > >> >>>>>>>>>> `newTransaction()` should not see writes from the other
> > > >> >> transaction
> > > >> >>>>>>>> until
> > > >> >>>>>>>>>> they have been committed. With READ_UNCOMMITTED, all
> bets are
> > > >> off,
> > > >> >>>> and
> > > >> >>>>>>>>>> stores can allow threads to observe written records at
> any
> > > >> time,
> > > >> >>>>>>>> which is
> > > >> >>>>>>>>>> essentially "no transactions". That said, StateStores are
> > > free
> > > >> to
> > > >> >>>>>>>> implement
> > > >> >>>>>>>>>> these guarantees however they can, which is a bit more
> > > relaxed
> > > >> >> than
> > > >> >>>>>>>>>> dictating "you must use transactions". For example, with
> > > >> RocksDB
> > > >> >> we
> > > >> >>>>>>>> would
> > > >> >>>>>>>>>> implement these as READ_COMMITTED == WBWI-based
> > > "transactions",
> > > >> >>>>>>>>>> READ_UNCOMMITTED == direct writes to the database. But
> with
> > > >> other
> > > >> >>>>>>>> storage
> > > >> >>>>>>>>>> engines, it might be preferable to *always* use
> transactions,
> > > >> even
> > > >> >>>>>>>> when
> > > >> >>>>>>>>>> unnecessary; or there may be storage engines that don't
> > > provide
> > > >> >>>>>>>>>> transactions, but the isolation guarantees can be met
> using a
> > > >> >>>>>>>> different
> > > >> >>>>>>>>>> technique.
> > > >> >>>>>>>>>> My idea was to try to keep the StateStore interface as
> > > loosely
> > > >> >>>> coupled
> > > >> >>>>>>>>>> from the Streams engine as possible, to give implementers
> > > more
> > > >> >>>>>>>> freedom, and
> > > >> >>>>>>>>>> reduce the amount of internal knowledge required.
> > > >> >>>>>>>>>> That said, I understand that "IsolationLevel" might not
> be
> > > the
> > > >> >> right
> > > >> >>>>>>>>>> abstraction, and we can always make it much more
> explicit if
> > > >> >>>>>>>> required, e.g.
> > > >> >>>>>>>>>> boolean transactional()
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>> 7-8.
> > > >> >>>>>>>>>> I can make these changes either later today or tomorrow.
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>> Small update:
> > > >> >>>>>>>>>> I've rebased my branch on trunk and fixed a bunch of
> issues
> > > >> that
> > > >> >>>>>>>> needed
> > > >> >>>>>>>>>> addressing. Currently, all the tests pass, which is
> > > promising,
> > > >> but
> > > >> >>>> it
> > > >> >>>>>>>> will
> > > >> >>>>>>>>>> need to undergo some performance testing. I haven't (yet)
> > > >> worked
> > > >> >> on
> > > >> >>>>>>>>>> removing the `newTransaction()` stuff, but I would expect
> > > that,
> > > >> >>>>>>>>>> behaviourally, it should make no difference. The branch
> is
> > > >> >> available
> > > >> >>>>>>>> at
> > > >> >>>>>>>>>> https://github.com/nicktelford/kafka/tree/KIP-892-c if
> > > anyone
> > > >> is
> > > >> >>>>>>>>>> interested in taking an early look.
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>> Regards,
> > > >> >>>>>>>>>> Nick
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>> On Thu, 22 Jun 2023 at 11:59, Bruno Cadonna <
> > > >> cado...@apache.org>
> > > >> >>>>>>>> wrote:
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>>> Hi Nick,
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> 1.
> > > >> >>>>>>>>>>> Yeah, I agree with you. That was actually also my
> point. I
> > > >> >>>> understood
> > > >> >>>>>>>>>>> that John was proposing the ingestion path as a way to
> avoid
> > > >> the
> > > >> >>>>>>>> early
> > > >> >>>>>>>>>>> commits. Probably, I misinterpreted the intent.
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> 2.
> > > >> >>>>>>>>>>> I agree with John here, that actually it is public API.
> My
> > > >> >> question
> > > >> >>>>>>>> is
> > > >> >>>>>>>>>>> how this usage pattern affects normal processing.
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> 3.
> > > >> >>>>>>>>>>> My concern is that checking for the size of the
> transaction
> > > >> >> buffer
> > > >> >>>>>>>> and
> > > >> >>>>>>>>>>> maybe triggering an early commit affects the whole
> > > processing
> > > >> of
> > > >> >>>>>>>> Kafka
> > > >> >>>>>>>>>>> Streams. The transactionality of a state store is not
> > > >> confined to
> > > >> >>>> the
> > > >> >>>>>>>>>>> state store itself, but spills over and changes the
> behavior
> > > >> of
> > > >> >>>> other
> > > >> >>>>>>>>>>> parts of the system. I agree with you that it is a
> decent
> > > >> >>>>>>>> compromise. I
> > > >> >>>>>>>>>>> just wanted to analyse the downsides and list the
> options to
> > > >> >>>> overcome
> > > >> >>>>>>>>>>> them. I also agree with you that all options seem quite
> > > heavy
> > > >> >>>>>>>> compared
> > > >> >>>>>>>>>>> with your KIP. I do not understand what you mean with
> "less
> > > >> >>>>>>>> predictable
> > > >> >>>>>>>>>>> for users", though.
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> I found the discussions about the alternatives really
> > > >> >> interesting.
> > > >> >>>>>>>> But I
> > > >> >>>>>>>>>>> also think that your plan sounds good and we should
> continue
> > > >> with
> > > >> >>>> it!
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> Some comments on your reply to my e-mail on June 20th:
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> 3.
> > > >> >>>>>>>>>>> Ah, now, I understand the reasoning behind putting
> isolation
> > > >> >> level
> > > >> >>>> in
> > > >> >>>>>>>>>>> the state store context. Thanks! Should that also be a
> way
> > > to
> > > >> >> give
> > > >> >>>>>>>> the
> > > >> >>>>>>>>>>> the state store the opportunity to decide whether to
> turn on
> > > >> >>>>>>>>>>> transactions or not?
> > > >> >>>>>>>>>>> With my comment, I was more concerned about how do you
> know
> > > >> if a
> > > >> >>>>>>>>>>> checkpoint file needs to be written under EOS, if you
> do not
> > > >> >> have a
> > > >> >>>>>>>> way
> > > >> >>>>>>>>>>> to know if the state store is transactional or not. If a
> > > state
> > > >> >>>> store
> > > >> >>>>>>>> is
> > > >> >>>>>>>>>>> transactional, the checkpoint file can be written during
> > > >> normal
> > > >> >>>>>>>>>>> processing under EOS. If the state store is not
> > > transactional,
> > > >> >> the
> > > >> >>>>>>>>>>> checkpoint file must not be written under EOS.
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> 7.
> > > >> >>>>>>>>>>> My point was about not only considering the bytes in
> memory
> > > in
> > > >> >>>> config
> > > >> >>>>>>>>>>> statestore.uncommitted.max.bytes, but also bytes that
> might
> > > be
> > > >> >>>>>>>> spilled
> > > >> >>>>>>>>>>> on disk. Basically, I was wondering whether you should
> > > remove
> > > >> the
> > > >> >>>>>>>>>>> "memory" in "Maximum number of memory bytes to be used
> to
> > > >> >>>>>>>>>>> buffer uncommitted state-store records." My thinking was
> > > that
> > > >> >> even
> > > >> >>>>>>>> if a
> > > >> >>>>>>>>>>> state store spills uncommitted bytes to disk, limiting
> the
> > > >> >> overall
> > > >> >>>>>>>> bytes
> > > >> >>>>>>>>>>> might make sense. Thinking about it again and
> considering
> > > the
> > > >> >>>> recent
> > > >> >>>>>>>>>>> discussions, it does not make too much sense anymore.
> > > >> >>>>>>>>>>> I like the name statestore.transaction.buffer.max.bytes
> that
> > > >> you
> > > >> >>>>>>>> proposed.
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> 8.
> > > >> >>>>>>>>>>> A high-level description (without implementation
> details) of
> > > >> how
> > > >> >>>>>>>> Kafka
> > > >> >>>>>>>>>>> Streams will manage the commit of changelog
> transactions,
> > > >> state
> > > >> >>>> store
> > > >> >>>>>>>>>>> transactions and checkpointing would be great. Would be
> > > great
> > > >> if
> > > >> >>>> you
> > > >> >>>>>>>>>>> could also add some sentences about the behavior in
> case of
> > > a
> > > >> >>>>>>>> failure.
> > > >> >>>>>>>>>>> For instance how does a transactional state store
> recover
> > > >> after a
> > > >> >>>>>>>>>>> failure or what happens with the transaction buffer,
> etc.
> > > >> (that
> > > >> >> is
> > > >> >>>>>>>> what
> > > >> >>>>>>>>>>> I meant by "fail-over" in point 9.)
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> Best,
> > > >> >>>>>>>>>>> Bruno
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>> On 21.06.23 18:50, Nick Telford wrote:
> > > >> >>>>>>>>>>>> Hi Bruno,
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> 1.
> > > >> >>>>>>>>>>>> Isn't this exactly the same issue that
> WriteBatchWithIndex
> > > >> >>>>>>>> transactions
> > > >> >>>>>>>>>>>> have, whereby exceeding (or likely to exceed)
> configured
> > > >> memory
> > > >> >>>>>>>> needs to
> > > >> >>>>>>>>>>>> trigger an early commit?
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> 2.
> > > >> >>>>>>>>>>>> This is one of my big concerns. Ultimately, any
> approach
> > > >> based
> > > >> >> on
> > > >> >>>>>>>>>>> cracking
> > > >> >>>>>>>>>>>> open RocksDB internals and using it in ways it's not
> really
> > > >> >>>> designed
> > > >> >>>>>>>>>>> for is
> > > >> >>>>>>>>>>>> likely to have some unforseen performance or
> consistency
> > > >> issues.
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> 3.
> > > >> >>>>>>>>>>>> What's your motivation for removing these early
> commits?
> > > >> While
> > > >> >> not
> > > >> >>>>>>>>>>> ideal, I
> > > >> >>>>>>>>>>>> think they're a decent compromise to ensure consistency
> > > >> whilst
> > > >> >>>>>>>>>>> maintaining
> > > >> >>>>>>>>>>>> good and predictable performance.
> > > >> >>>>>>>>>>>> All 3 of your suggested ideas seem *very* complicated,
> and
> > > >> might
> > > >> >>>>>>>>>>> actually
> > > >> >>>>>>>>>>>> make behaviour less predictable for users as a
> consequence.
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> I'm a bit concerned that the scope of this KIP is
> growing a
> > > >> bit
> > > >> >>>> out
> > > >> >>>>>>>> of
> > > >> >>>>>>>>>>>> control. While it's good to discuss ideas for future
> > > >> >>>> improvements, I
> > > >> >>>>>>>>>>> think
> > > >> >>>>>>>>>>>> it's important to narrow the scope down to a design
> that
> > > >> >> achieves
> > > >> >>>>>>>> the
> > > >> >>>>>>>>>>> most
> > > >> >>>>>>>>>>>> pressing objectives (constant sized restorations during
> > > dirty
> > > >> >>>>>>>>>>>> close/unexpected errors). Any design that this KIP
> produces
> > > >> can
> > > >> >>>>>>>>>>> ultimately
> > > >> >>>>>>>>>>>> be changed in the future, especially if the bulk of it
> is
> > > >> >> internal
> > > >> >>>>>>>>>>>> behaviour.
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> I'm going to spend some time next week trying to
> re-work
> > > the
> > > >> >>>>>>>> original
> > > >> >>>>>>>>>>>> WriteBatchWithIndex design to remove the
> newTransaction()
> > > >> >> method,
> > > >> >>>>>>>> such
> > > >> >>>>>>>>>>> that
> > > >> >>>>>>>>>>>> it's just an implementation detail of RocksDBStore.
> That
> > > >> way, if
> > > >> >>>> we
> > > >> >>>>>>>>>>> want to
> > > >> >>>>>>>>>>>> replace WBWI with something in the future, like the SST
> > > file
> > > >> >>>>>>>> management
> > > >> >>>>>>>>>>>> outlined by John, then we can do so with little/no API
> > > >> changes.
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> Regards,
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>> Nick
> > > >> >>>>>>>>>>>>
> > > >> >>>>>>>>>>>
> > > >> >>>>>>>>>>
> > > >> >>>>>>>>>
> > > >> >>>>>>>>
> > > >> >>>>>>>
> > > >> >>>>>
> > > >> >>>>
> > > >> >>>
> > > >> >>
> > > >> >
> > > >>
> > > >
> > >
>
