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
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>>
> >>>>
> >>>
> >
>
