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From Xi Liu <xi.liu....@gmail.com>
Subject Re: Proxy Client - Batch Ordering / Commit
Date Wed, 09 Nov 2016 10:34:41 GMT
Cameron,

Have you started any work for this? I just updated the proposal page -
https://cwiki.apache.org/confluence/display/DL/DP-2+-+Epoch+Write+Support
Maybe we can work together with this.

Sijie, Leigh,

can you guys help review this to make sure our proposal is in the right
direction?

- Xi

On Tue, Nov 1, 2016 at 3:05 AM, Sijie Guo <sijie@apache.org> wrote:

> I created https://issues.apache.org/jira/browse/DL-63 for tracking the
> proposed idea here.
>
>
>
> On Wed, Oct 26, 2016 at 4:53 PM, Sijie Guo <sijieg@twitter.com.invalid>
> wrote:
>
> > On Tue, Oct 25, 2016 at 11:30 AM, Cameron Hatfield <kinguy@gmail.com>
> > wrote:
> >
> > > Yes, we are reading the HBase WAL (from their replication plugin
> > support),
> > > and writing that into DL.
> > >
> >
> > Gotcha.
> >
> >
> > >
> > > From the sounds of it, yes, it would. Only thing I would say is make
> the
> > > epoch requirement optional, so that if I client doesn't care about
> dupes
> > > they don't have to deal with the process of getting a new epoch.
> > >
> >
> > Yup. This should be optional. I can start a wiki page on how we want to
> > implement this. Are you interested in contributing to this?
> >
> >
> > >
> > > -Cameron
> > >
> > > On Wed, Oct 19, 2016 at 7:43 PM, Sijie Guo <sijieg@twitter.com.invalid
> >
> > > wrote:
> > >
> > > > On Wed, Oct 19, 2016 at 7:17 PM, Sijie Guo <sijieg@twitter.com>
> wrote:
> > > >
> > > > >
> > > > >
> > > > > On Monday, October 17, 2016, Cameron Hatfield <kinguy@gmail.com>
> > > wrote:
> > > > >
> > > > >> Answer inline:
> > > > >>
> > > > >> On Mon, Oct 17, 2016 at 11:46 AM, Sijie Guo <sijie@apache.org>
> > wrote:
> > > > >>
> > > > >> > Cameron,
> > > > >> >
> > > > >> > Thank you for your summary. I liked the discussion here.
I also
> > > liked
> > > > >> the
> > > > >> > summary of your requirement - 'single-writer-per-key,
> > > > >> > multiple-writers-per-log'. If I understand correctly, the
core
> > > concern
> > > > >> here
> > > > >> > is almost 'exact-once' write (or a way to explicit tell
if a
> write
> > > can
> > > > >> be
> > > > >> > retried or not).
> > > > >> >
> > > > >> > Comments inline.
> > > > >> >
> > > > >> > On Fri, Oct 14, 2016 at 11:17 AM, Cameron Hatfield <
> > > kinguy@gmail.com>
> > > > >> > wrote:
> > > > >> >
> > > > >> > > > Ah- yes good point (to be clear we're not using
the proxy
> this
> > > way
> > > > >> > > today).
> > > > >> > >
> > > > >> > > > > Due to the source of the
> > > > >> > > > > data (HBase Replication), we cannot guarantee
that a
> single
> > > > >> partition
> > > > >> > > will
> > > > >> > > > > be owned for writes by the same client.
> > > > >> > >
> > > > >> > > > Do you mean you *need* to support multiple writers
issuing
> > > > >> interleaved
> > > > >> > > > writes or is it just that they might sometimes
interleave
> > writes
> > > > and
> > > > >> > you
> > > > >> > > >don't care?
> > > > >> > > How HBase partitions the keys being written wouldn't
have a
> > > one->one
> > > > >> > > mapping with the partitions we would have in HBase.
Even if we
> > did
> > > > >> have
> > > > >> > > that alignment when the cluster first started, HBase
will
> > > rebalance
> > > > >> what
> > > > >> > > servers own what partitions, as well as split and merge
> > partitions
> > > > >> that
> > > > >> > > already exist, causing eventual drift from one log
per
> > partition.
> > > > >> > > Because we want ordering guarantees per key (row in
hbase), we
> > > > >> partition
> > > > >> > > the logs by the key. Since multiple writers are possible
per
> > range
> > > > of
> > > > >> > keys
> > > > >> > > (due to the aforementioned rebalancing / splitting
/ etc of
> > > hbase),
> > > > we
> > > > >> > > cannot use the core library due to requiring a single
writer
> for
> > > > >> > ordering.
> > > > >> > >
> > > > >> > > But, for a single log, we don't really care about ordering
> aside
> > > > from
> > > > >> at
> > > > >> > > the per-key level. So all we really need to be able
to handle
> is
> > > > >> > preventing
> > > > >> > > duplicates when a failure occurs, and ordering consistency
> > across
> > > > >> > requests
> > > > >> > > from a single client.
> > > > >> > >
> > > > >> > > So our general requirements are:
> > > > >> > > Write A, Write B
> > > > >> > > Timeline: A -> B
> > > > >> > > Request B is only made after A has successfully returned
> > (possibly
> > > > >> after
> > > > >> > > retries)
> > > > >> > >
> > > > >> > > 1) If the write succeeds, it will be durably exposed
to
> clients
> > > > within
> > > > >> > some
> > > > >> > > bounded time frame
> > > > >> > >
> > > > >> >
> > > > >> > Guaranteed.
> > > > >> >
> > > > >>
> > > > >> > > 2) If A succeeds and B succeeds, the ordering for the
log will
> > be
> > > A
> > > > >> and
> > > > >> > > then B
> > > > >> > >
> > > > >> >
> > > > >> > If I understand correctly here, B is only sent after A is
> > returned,
> > > > >> right?
> > > > >> > If that's the case, It is guaranteed.
> > > > >>
> > > > >>
> > > > >>
> > > > >> >
> > > > >> >
> > > > >> >
> > > > >> > > 3) If A fails due to an error that can be relied on
to *not*
> be
> > a
> > > > lost
> > > > >> > ack
> > > > >> > > problem, it will never be exposed to the client, so
it may
> > > > (depending
> > > > >> on
> > > > >> > > the error) be retried immediately
> > > > >> > >
> > > > >> >
> > > > >> > If it is not a lost-ack problem, the entry will be exposed.
it
> is
> > > > >> > guaranteed.
> > > > >>
> > > > >> Let me try rephrasing the questions, to make sure I'm
> understanding
> > > > >> correctly:
> > > > >> If A fails, with an error such as "Unable to create connection
to
> > > > >> bookkeeper server", that would be the type of error we would
> expect
> > to
> > > > be
> > > > >> able to retry immediately, as that result means no action was
> taken
> > on
> > > > any
> > > > >> log / etc, so no entry could have been created. This is different
> > > then a
> > > > >> "Connection Timeout" exception, as we just might not have gotten
a
> > > > >> response
> > > > >> in time.
> > > > >>
> > > > >>
> > > > > Gotcha.
> > > > >
> > > > > The response code returned from proxy can tell if a failure can be
> > > > retried
> > > > > safely or not. (We might need to make them well documented)
> > > > >
> > > > >
> > > > >
> > > > >>
> > > > >> >
> > > > >> >
> > > > >> > > 4) If A fails due to an error that could be a lost
ack problem
> > > > >> (network
> > > > >> > > connectivity / etc), within a bounded time frame it
should be
> > > > >> possible to
> > > > >> > > find out if the write succeed or failed. Either by
reading
> from
> > > some
> > > > >> > > checkpoint of the log for the changes that should have
been
> made
> > > or
> > > > >> some
> > > > >> > > other possible server-side support.
> > > > >> > >
> > > > >> >
> > > > >> > If I understand this correctly, it is a duplication issue,
> right?
> > > > >> >
> > > > >> > Can a de-duplication solution work here? Either DL or your
> client
> > > does
> > > > >> the
> > > > >> > de-duplication?
> > > > >> >
> > > > >>
> > > > >> The requirements I'm mentioning are the ones needed for
> client-side
> > > > >> dedupping. Since if I can guarantee writes being exposed within
> some
> > > > time
> > > > >> frame, and I can never get into an inconsistently ordered state
> when
> > > > >> successes happen, when an error occurs, I can always wait for
max
> > time
> > > > >> frame, read the latest writes, and then dedup locally against
the
> > > > request
> > > > >> I
> > > > >> just made.
> > > > >>
> > > > >> The main thing about that timeframe is that its basically the
> > addition
> > > > of
> > > > >> every timeout, all the way down in the system, combined with
> > whatever
> > > > >> flushing / caching / etc times are at the bookkeeper / client
> level
> > > for
> > > > >> when values are exposed
> > > > >
> > > > >
> > > > > Gotcha.
> > > > >
> > > > >>
> > > > >>
> > > > >> >
> > > > >> > Is there any ways to identify your write?
> > > > >> >
> > > > >> > I can think of a case as follow - I want to know what is
your
> > > expected
> > > > >> > behavior from the log.
> > > > >> >
> > > > >> > a)
> > > > >> >
> > > > >> > If a hbase region server A writes a change of key K to the
log,
> > the
> > > > >> change
> > > > >> > is successfully made to the log;
> > > > >> > but server A is down before receiving the change.
> > > > >> > region server B took over the region that contains K, what
will
> B
> > > do?
> > > > >> >
> > > > >>
> > > > >> HBase writes in large chunks (WAL Logs), which its replication
> > system
> > > > then
> > > > >> handles by replaying in the case of failure. If I'm in a middle
> of a
> > > > log,
> > > > >> and the whole region goes down and gets rescheduled elsewhere,
I
> > will
> > > > >> start
> > > > >> back up from the beginning of the log I was in the middle of.
> Using
> > > > >> checkpointing + deduping, we should be able to find out where
we
> > left
> > > > off
> > > > >> in the log.
> > > > >
> > > > >
> > > > >> >
> > > > >> >
> > > > >> > b) same as a). but server A was just network partitioned.
will
> > both
> > > A
> > > > >> and B
> > > > >> > write the change of key K?
> > > > >> >
> > > > >>
> > > > >> HBase gives us some guarantees around network partitions
> > (Consistency
> > > > over
> > > > >> availability for HBase). HBase is a single-master failover
> recovery
> > > type
> > > > >> of
> > > > >> system, with zookeeper-based guarantees for single owners
> (writers)
> > > of a
> > > > >> range of data.
> > > > >>
> > > > >> >
> > > > >> >
> > > > >> >
> > > > >> > > 5) If A is turned into multiple batches (one large
request
> gets
> > > > split
> > > > >> > into
> > > > >> > > multiple smaller ones to the bookkeeper backend, due
to log
> > > rolling
> > > > /
> > > > >> > size
> > > > >> > > / etc):
> > > > >> > >   a) The ordering of entries within batches have ordering
> > > > consistence
> > > > >> > with
> > > > >> > > the original request, when exposed in the log (though
they may
> > be
> > > > >> > > interleaved with other requests)
> > > > >> > >   b) The ordering across batches have ordering consistence
> with
> > > the
> > > > >> > > original request, when exposed in the log (though they
may be
> > > > >> interleaved
> > > > >> > > with other requests)
> > > > >> > >   c) If a batch fails, and cannot be retried / is
> unsuccessfully
> > > > >> retried,
> > > > >> > > all batches after the failed batch should not be exposed
in
> the
> > > log.
> > > > >> > Note:
> > > > >> > > The batches before and including the failed batch,
that ended
> up
> > > > >> > > succeeding, can show up in the log, again within some
bounded
> > time
> > > > >> range
> > > > >> > > for reads by a client.
> > > > >> > >
> > > > >> >
> > > > >> > There is a method 'writeBulk' in DistributedLogClient can
> achieve
> > > this
> > > > >> > guarantee.
> > > > >> >
> > > > >> > However, I am not very sure about how will you turn A into
> > batches.
> > > If
> > > > >> you
> > > > >> > are dividing A into batches,
> > > > >> > you can simply control the application write sequence to
achieve
> > the
> > > > >> > guarantee here.
> > > > >> >
> > > > >> > Can you explain more about this?
> > > > >> >
> > > > >>
> > > > >> In this case, by batches I mean what the proxy does with the
> single
> > > > >> request
> > > > >> that I send it. If the proxy decides it needs to turn my single
> > > request
> > > > >> into multiple batches of requests, due to log rolling, size
> > > limitations,
> > > > >> etc, those would be the guarantees I need to be able to
> reduplicate
> > on
> > > > the
> > > > >> client side.
> > > > >
> > > > >
> > > > > A single record written by #write and A record set (set of records)
> > > > > written by #writeRecordSet are atomic - they will not be broken
> down
> > > into
> > > > > entries (batches). With the correct response code, you would be
> able
> > to
> > > > > tell if it is a lost-ack failure or not. However there is a size
> > > > limitation
> > > > > for this - it can't not go beyond 1MB for current implementation.
> > > > >
> > > > > What is your expected record size?
> > > > >
> > > > >
> > > > >>
> > > > >> >
> > > > >> >
> > > > >> > >
> > > > >> > > Since we can guarantee per-key ordering on the client
side, we
> > > > >> guarantee
> > > > >> > > that there is a single writer per-key, just not per
log.
> > > > >> >
> > > > >> >
> > > > >> > Do you need fencing guarantee in the case of network partition
> > > causing
> > > > >> > two-writers?
> > > > >> >
> > > > >> >
> > > > >> > > So if there was a
> > > > >> > > way to guarantee a single write request as being written
or
> not,
> > > > >> within a
> > > > >> > > certain time frame (since failures should be rare anyways,
> this
> > is
> > > > >> fine
> > > > >> > if
> > > > >> > > it is expensive), we can then have the client guarantee
the
> > > ordering
> > > > >> it
> > > > >> > > needs.
> > > > >> > >
> > > > >> >
> > > > >> > This sounds an 'exact-once' write (regarding retries)
> requirement
> > to
> > > > me,
> > > > >> > right?
> > > > >> >
> > > > >> Yes. I'm curious of how this issue is handled by Manhattan, since
> > you
> > > > can
> > > > >> imagine a data store that ends up getting multiple writes for
the
> > same
> > > > put
> > > > >> / get / etc, would be harder to use, and we are basically trying
> to
> > > > create
> > > > >> a log like that for HBase.
> > > > >
> > > > >
> > > > > Are you guys replacing HBase WAL?
> > > > >
> > > > > In Manhattan case, the request will be first written to DL streams
> by
> > > > > Manhattan coordinator. The Manhattan replica then will read from
> the
> > DL
> > > > > streams and apply the change. In the lost-ack case, the MH
> > coordinator
> > > > will
> > > > > just fail the request to client.
> > > > >
> > > > > My feeling here is your usage for HBase is a bit different from how
> > we
> > > > use
> > > > > DL in Manhattan. It sounds like you read from a source (HBase WAL)
> > and
> > > > > write to DL. But I might be wrong.
> > > > >
> > > > >
> > > > >>
> > > > >> >
> > > > >> >
> > > > >> > >
> > > > >> > >
> > > > >> > > > Cameron:
> > > > >> > > > Another thing we've discussed but haven't really
thought
> > > through -
> > > > >> > > > We might be able to support some kind of epoch
write
> request,
> > > > where
> > > > >> the
> > > > >> > > > epoch is guaranteed to have changed if the writer
has
> changed
> > or
> > > > the
> > > > >> > > ledger
> > > > >> > > > was ever fenced off. Writes include an epoch and
are
> rejected
> > if
> > > > the
> > > > >> > > epoch
> > > > >> > > > has changed.
> > > > >> > > > With a mechanism like this, fencing the ledger
off after a
> > > failure
> > > > >> > would
> > > > >> > > > ensure any pending writes had either been written
or would
> be
> > > > >> rejected.
> > > > >> > >
> > > > >> > > The issue would be how I guarantee the write I wrote
to the
> > server
> > > > was
> > > > >> > > written. Since a network issue could happen on the
send of the
> > > > >> request,
> > > > >> > or
> > > > >> > > on the receive of the success response, an epoch wouldn't
tell
> > me
> > > > if I
> > > > >> > can
> > > > >> > > successfully retry, as it could be successfully written
but
> AWS
> > > > >> dropped
> > > > >> > the
> > > > >> > > connection for the success response. Since the epoch
would be
> > the
> > > > same
> > > > >> > > (same ledger), I could write duplicates.
> > > > >> > >
> > > > >> > >
> > > > >> > > > We are currently proposing adding a transaction
semantic to
> dl
> > > to
> > > > >> get
> > > > >> > rid
> > > > >> > > > of the size limitation and the unaware-ness in
the proxy
> > client.
> > > > >> Here
> > > > >> > is
> > > > >> > > > our idea -
> > > > >> > > > http://mail-archives.apache.org/mod_mbox/incubator-
> > > distributedlog
> > > > >> > > -dev/201609.mbox/%3cCAAC6BxP5YyEHwG0ZCF5soh42X=xuYwYm
> > > > >> > > <http://mail-archives.apache.org/mod_mbox/incubator-
> > > > >> > distributedlog%0A-dev/201609.mbox/%3cCAAC6BxP5YyEHwG0ZCF5soh
> > > > 42X=xuYwYm>
> > > > >> > > L4nXsYBYiofzxpVk6g@mail.gmail.com%3e
> > > > >> > >
> > > > >> > > > I am not sure if your idea is similar as ours.
but we'd like
> > to
> > > > >> > > collaborate
> > > > >> > > > with the community if anyone has the similar idea.
> > > > >> > >
> > > > >> > > Our use case would be covered by transaction support,
but I'm
> > > unsure
> > > > >> if
> > > > >> > we
> > > > >> > > would need something that heavy weight for the guarantees
we
> > need.
> > > > >> > >
> > > > >> >
> > > > >> > >
> > > > >> > > Basically, the high level requirement here is "Support
> > consistent
> > > > >> write
> > > > >> > > ordering for single-writer-per-key, multi-writer-per-log".
My
> > > hunch
> > > > is
> > > > >> > > that, with some added guarantees to the proxy (if it
isn't
> > already
> > > > >> > > supported), and some custom client code on our side
for
> removing
> > > the
> > > > >> > > entries that actually succeed to write to DistributedLog
from
> > the
> > > > >> request
> > > > >> > > that failed, it should be a relatively easy thing to
support.
> > > > >> > >
> > > > >> >
> > > > >> > Yup. I think it should not be very difficult to support.
There
> > might
> > > > be
> > > > >> > some changes in the server side.
> > > > >> > Let's figure out what will the changes be. Are you guys
> interested
> > > in
> > > > >> > contributing?
> > > > >> >
> > > > >> > Yes, we would be.
> > > > >>
> > > > >> As a note, the one thing that we see as an issue with the client
> > side
> > > > >> dedupping is how to bound the range of data that needs to be
> looked
> > at
> > > > for
> > > > >> deduplication. As you can imagine, it is pretty easy to bound
the
> > > bottom
> > > > >> of
> > > > >> the range, as that it just regular checkpointing of the DSLN
that
> is
> > > > >> returned. I'm still not sure if there is any nice way to time
> bound
> > > the
> > > > >> top
> > > > >> end of the range, especially since the proxy owns sequence numbers
> > > > (which
> > > > >> makes sense). I am curious if there is more that can be done
if
> > > > >> deduplication is on the server side. However the main minus I
see
> of
> > > > >> server
> > > > >> side deduplication is that instead of running contingent on there
> > > being
> > > > a
> > > > >> failed client request, instead it would have to run every time
a
> > write
> > > > >> happens.
> > > > >
> > > > >
> > > > > For a reliable dedup, we probably need fence-then-getLastDLSN
> > > operation -
> > > > > so it would guarantee that any non-completed requests issued
> > (lost-ack
> > > > > requests) before this fence-then-getLastDLSN operation will be
> failed
> > > and
> > > > > they will never land at the log.
> > > > >
> > > > > the pseudo code would look like below -
> > > > >
> > > > > write(request) onFailure { t =>
> > > > >
> > > > > if (t is timeout exception) {
> > > > >
> > > > > DLSN lastDLSN = fenceThenGetLastDLSN()
> > > > > DLSN lastCheckpointedDLSN = ...;
> > > > > // find if the request lands between [lastDLSN,
> > lastCheckpointedDLSN].
> > > > > // if it exists, the write succeed; otherwise retry.
> > > > >
> > > > > }
> > > > >
> > > > >
> > > > > }
> > > > >
> > > >
> > > >
> > > > Just realized the idea is same as what Leigh raised in the previous
> > email
> > > > about 'epoch write'. Let me explain more about this idea (Leigh, feel
> > > free
> > > > to jump in to fill up your idea).
> > > >
> > > > - when a log stream is owned,  the proxy use the last transaction id
> as
> > > the
> > > > epoch
> > > > - when a client connects (handshake with the proxy), it will get the
> > > epoch
> > > > for the stream.
> > > > - the writes issued by this client will carry the epoch to the proxy.
> > > > - add a new rpc - fenceThenGetLastDLSN - it would force the proxy to
> > bump
> > > > the epoch.
> > > > - if fenceThenGetLastDLSN happened, all the outstanding writes with
> old
> > > > epoch will be rejected with exceptions (e.g. EpochFenced).
> > > > - The DLSN returned from fenceThenGetLastDLSN can be used as the
> bound
> > > for
> > > > deduplications on failures.
> > > >
> > > > Cameron, does this sound a solution to your use case?
> > > >
> > > >
> > > >
> > > > >
> > > > >
> > > > >>
> > > > >> Maybe something that could fit a similar need that Kafka does
(the
> > > last
> > > > >> store value for a particular key in a log), such that on a per
key
> > > basis
> > > > >> there could be a sequence number that support deduplication?
Cost
> > > seems
> > > > >> like it would be high however, and I'm not even sure if bookkeeper
> > > > >> supports
> > > > >> it.
> > > > >
> > > > >
> > > > >> Cheers,
> > > > >> Cameron
> > > > >>
> > > > >> >
> > > > >> > >
> > > > >> > > Thanks,
> > > > >> > > Cameron
> > > > >> > >
> > > > >> > >
> > > > >> > > On Sat, Oct 8, 2016 at 7:35 AM, Leigh Stewart
> > > > >> > <lstewart@twitter.com.invalid
> > > > >> > > >
> > > > >> > > wrote:
> > > > >> > >
> > > > >> > > > Cameron:
> > > > >> > > > Another thing we've discussed but haven't really
thought
> > > through -
> > > > >> > > > We might be able to support some kind of epoch
write
> request,
> > > > where
> > > > >> the
> > > > >> > > > epoch is guaranteed to have changed if the writer
has
> changed
> > or
> > > > the
> > > > >> > > ledger
> > > > >> > > > was ever fenced off. Writes include an epoch and
are
> rejected
> > if
> > > > the
> > > > >> > > epoch
> > > > >> > > > has changed.
> > > > >> > > > With a mechanism like this, fencing the ledger
off after a
> > > failure
> > > > >> > would
> > > > >> > > > ensure any pending writes had either been written
or would
> be
> > > > >> rejected.
> > > > >> > > >
> > > > >> > > >
> > > > >> > > > On Sat, Oct 8, 2016 at 7:10 AM, Sijie Guo <sijie@apache.org
> >
> > > > wrote:
> > > > >> > > >
> > > > >> > > > > Cameron,
> > > > >> > > > >
> > > > >> > > > > I think both Leigh and Xi had made a few
good points about
> > > your
> > > > >> > > question.
> > > > >> > > > >
> > > > >> > > > > To add one more point to your question -
"but I am not
> > > > >> > > > > 100% of how all of the futures in the code
handle
> failures.
> > > > >> > > > > If not, where in the code would be the relevant
places to
> > add
> > > > the
> > > > >> > > ability
> > > > >> > > > > to do this, and would the project be interested
in a pull
> > > > >> request?"
> > > > >> > > > >
> > > > >> > > > > The current proxy and client logic doesn't
do perfectly on
> > > > >> handling
> > > > >> > > > > failures (duplicates) - the strategy now
is the client
> will
> > > > retry
> > > > >> as
> > > > >> > > best
> > > > >> > > > > at it can before throwing exceptions to users.
The code
> you
> > > are
> > > > >> > looking
> > > > >> > > > for
> > > > >> > > > > - it is on BKLogSegmentWriter for the proxy
handling
> writes
> > > and
> > > > >> it is
> > > > >> > > on
> > > > >> > > > > DistributedLogClientImpl for the proxy client
handling
> > > responses
> > > > >> from
> > > > >> > > > > proxies. Does this help you?
> > > > >> > > > >
> > > > >> > > > > And also, you are welcome to contribute the
pull requests.
> > > > >> > > > >
> > > > >> > > > > - Sijie
> > > > >> > > > >
> > > > >> > > > >
> > > > >> > > > >
> > > > >> > > > > On Tue, Oct 4, 2016 at 3:39 PM, Cameron Hatfield
<
> > > > >> kinguy@gmail.com>
> > > > >> > > > wrote:
> > > > >> > > > >
> > > > >> > > > > > I have a question about the Proxy Client.
Basically, for
> > our
> > > > use
> > > > >> > > cases,
> > > > >> > > > > we
> > > > >> > > > > > want to guarantee ordering at the key
level,
> irrespective
> > of
> > > > the
> > > > >> > > > ordering
> > > > >> > > > > > of the partition it may be assigned
to as a whole. Due
> to
> > > the
> > > > >> > source
> > > > >> > > of
> > > > >> > > > > the
> > > > >> > > > > > data (HBase Replication), we cannot
guarantee that a
> > single
> > > > >> > partition
> > > > >> > > > > will
> > > > >> > > > > > be owned for writes by the same client.
This means the
> > proxy
> > > > >> client
> > > > >> > > > works
> > > > >> > > > > > well (since we don't care which proxy
owns the partition
> > we
> > > > are
> > > > >> > > writing
> > > > >> > > > > > to).
> > > > >> > > > > >
> > > > >> > > > > >
> > > > >> > > > > > However, the guarantees we need when
writing a batch
> > > consists
> > > > >> of:
> > > > >> > > > > > Definition of a Batch: The set of records
sent to the
> > > > writeBatch
> > > > >> > > > endpoint
> > > > >> > > > > > on the proxy
> > > > >> > > > > >
> > > > >> > > > > > 1. Batch success: If the client receives
a success from
> > the
> > > > >> proxy,
> > > > >> > > then
> > > > >> > > > > > that batch is successfully written
> > > > >> > > > > >
> > > > >> > > > > > 2. Inter-Batch ordering : Once a batch
has been written
> > > > >> > successfully
> > > > >> > > by
> > > > >> > > > > the
> > > > >> > > > > > client, when another batch is written,
it will be
> > guaranteed
> > > > to
> > > > >> be
> > > > >> > > > > ordered
> > > > >> > > > > > after the last batch (if it is the same
stream).
> > > > >> > > > > >
> > > > >> > > > > > 3. Intra-Batch ordering: Within a batch
of writes, the
> > > records
> > > > >> will
> > > > >> > > be
> > > > >> > > > > > committed in order
> > > > >> > > > > >
> > > > >> > > > > > 4. Intra-Batch failure ordering: If
an individual record
> > > fails
> > > > >> to
> > > > >> > > write
> > > > >> > > > > > within a batch, all records after that
record will not
> be
> > > > >> written.
> > > > >> > > > > >
> > > > >> > > > > > 5. Batch Commit: Guarantee that if a
batch returns a
> > > success,
> > > > it
> > > > >> > will
> > > > >> > > > be
> > > > >> > > > > > written
> > > > >> > > > > >
> > > > >> > > > > > 6. Read-after-write: Once a batch is
committed, within a
> > > > limited
> > > > >> > > > > time-frame
> > > > >> > > > > > it will be able to be read. This is
required in the case
> > of
> > > > >> > failure,
> > > > >> > > so
> > > > >> > > > > > that the client can see what actually
got committed. I
> > > believe
> > > > >> the
> > > > >> > > > > > time-frame part could be removed if
the client can send
> in
> > > the
> > > > >> same
> > > > >> > > > > > sequence number that was written previously,
since it
> > would
> > > > then
> > > > >> > fail
> > > > >> > > > and
> > > > >> > > > > > we would know that a read needs to occur.
> > > > >> > > > > >
> > > > >> > > > > >
> > > > >> > > > > > So, my basic question is if this is
currently possible
> in
> > > the
> > > > >> > proxy?
> > > > >> > > I
> > > > >> > > > > > don't believe it gives these guarantees
as it stands
> > today,
> > > > but
> > > > >> I
> > > > >> > am
> > > > >> > > > not
> > > > >> > > > > > 100% of how all of the futures in the
code handle
> > failures.
> > > > >> > > > > > If not, where in the code would be the
relevant places
> to
> > > add
> > > > >> the
> > > > >> > > > ability
> > > > >> > > > > > to do this, and would the project be
interested in a
> pull
> > > > >> request?
> > > > >> > > > > >
> > > > >> > > > > >
> > > > >> > > > > > Thanks,
> > > > >> > > > > > Cameron
> > > > >> > > > > >
> > > > >> > > > >
> > > > >> > > >
> > > > >> > >
> > > > >> >
> > > > >>
> > > > >
> > > >
> > >
> >
>

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