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From "Parthasarathy, Mohan" <mpart...@hpe.com>
Subject Re: Can kafka internal state be purged ?
Date Wed, 26 Jun 2019 17:56:52 GMT
Initially it started in the testing. QA reported problems where "events" were not detected
after they finished their testing. After this discussion, my proposal was to send a few more
records to cause the windows to flush so that the suppressed event would show up. Now it looks
to me, these few dummy records have to match the "key" of the pending windows. Then it would
be flushed. 

In practice, it may not be a problem always. But then the real time nature of the problem
might require us that there is not a huge delay between the processing of the event and the
flush. How does one solve this issue in production ? I am wondering why the design did not
accommodate a timer to flush the windows ? 

Thanks
Mohan


´╗┐On 6/26/19, 8:18 AM, "John Roesler" <john@confluent.io> wrote:

    Hi Mohan,
    
    I see where you're going with this, and it might indeed be a
    challenge. Even if you send a "dummy" message on all input topics, you
    won't have a guarantee that after the repartition, the dummy message
    is propagated to all partitions of the repartition topics. So it might
    be difficult to force the suppression buffer to flush if it's after a
    repartition.
    
    Can we take a step back and discuss the motivation for forcing the
    records to flush out? Is this for testing your app, or is it to drive
    some production logic?
    
    Thanks,
    -John
    
    
    On Mon, Jun 24, 2019 at 7:26 PM Parthasarathy, Mohan <mparthas@hpe.com> wrote:
    >
    > John,
    >
    > Thanks for the nice explanation. When the repartitioning happens, does the window
get associated with the new partition i.e., now does a message with new timestamp has to appear
on the repartition topic for the window to expire ? It is possible that there is new stream
of messages coming in but post-map operation, the partitions in the repartitioned topic does
not see the same thing.
    >
    > Thanks
    > Mohan
    >
    > On 6/24/19, 7:49 AM, "John Roesler" <john@confluent.io> wrote:
    >
    >     Hey, this is a very apt question.
    >
    >     GroupByKey isn't a great example because it doesn't actually change
    >     the key, so all the aggregation results are actually on records from
    >     the same partition. But let's say you do a groupBy or a map (or any
    >     operation that can change the key), followed by an aggregation. Now
    >     it's possible that the aggregation would need to process records from
    >     two different partitions. In such a case (key-changing operation
    >     followed by a stateful operation), Streams actually round-trips the
    >     data through an intermediate topic, called a repartition topic, before
    >     the aggregation. This has the effect, similar to the "shuffle" phase
    >     of map-reduce, of putting all the data into its *new* right partition,
    >     so then the aggregation can still process each of its partitions
    >     independently.
    >
    >     Regarding the latter statement, even though you only have one
    >     instance, Streams _still_ processes each partition independently. The
    >     "unit of work" responsible for processing a partition is called a
    >     "task". So if you have 4 partitions, then your one instance actually
    >     has 4 state stores, one for each task, where each task only gets
    >     records from a single partition. The tasks can't see anything about
    >     each other, not their state nor other metadata like their current
    >     stream time. Otherwise, the results would depend on which tasks happen
    >     to be co-located with which other tasks. So, having to send your
    >     "purge" event to all partitions is a pain, but in the end, it buys you
    >     a lot, as you can add another instance to your cluster at any time,
    >     and Streams will scale up, and you'll know that the program is
    >     executing exactly the same way the whole time.
    >
    >     -John
    >
    >     On Sat, Jun 22, 2019 at 4:37 PM Parthasarathy, Mohan <mparthas@hpe.com>
wrote:
    >     >
    >     > I can see the issue. But it raised other questions. Pardon my ignorance.
Even though partitions are processed independently, windows can be aggregating state from
records read from many partitions. Let us say there is a groupByKey followed by aggregate.
In this case how is the state reconciled across all the application instances ? Is there a
designated instance for a particular key ?
    >     >
    >     > In my case, there was only one instance processing records from all partitions
and it is kind of odd that windows did not expire even though I understand why now.
    >     >
    >     > Thanks
    >     > Mohan
    >     >
    >     >
    >     > On 6/21/19, 2:25 PM, "John Roesler" <john@confluent.io> wrote:
    >     >
    >     >     No problem. It's definitely a subtlety. It occurs because each
    >     >     partition is processed completely independently of the others, so
    >     >     "stream time" is tracked per partition, and there's no way to look
    >     >     across at the other partitions to find out what stream time they have.
    >     >
    >     >     In general, it's not a problem because you'd expect all partitions to
    >     >     receive updates over time, but if you're specifically trying to send
    >     >     events that cause stuff to get flushed from the buffers, it can mess
    >     >     with you. It's especially notable in tests. So, for most tests, I just
    >     >     configure the topics to have one partition.
    >     >
    >     >     -John
    >     >
    >     >     On Fri, Jun 21, 2019 at 3:56 PM Parthasarathy, Mohan <mparthas@hpe.com>
wrote:
    >     >     >
    >     >     > That change "In the same partition" must explain what we are seeing.
Unless you see one message per partition, all windows will not expire. That is an interesting
twist. Thanks for the correction ( I will go back and confirm this.
    >     >     >
    >     >     > -mohan
    >     >     >
    >     >     >
    >     >     > On 6/21/19, 12:40 PM, "John Roesler" <john@confluent.io>
wrote:
    >     >     >
    >     >     >     Sure, the record cache attempts to save downstream operators
from
    >     >     >     unnecessary updates by also buffering for a short amount of
time
    >     >     >     before forwarding. It forwards results whenever the cache fills
up or
    >     >     >     whenever there is a commit. If you're happy to wait at least
"commit
    >     >     >     interval" amount of time for updates, then you don't need to
do
    >     >     >     anything, but if you're on the edge of your seat, waiting for
these
    >     >     >     results, you can set cache.max.bytes.buffering to 0 to disable
the
    >     >     >     record cache entirely. Note that this would hurt throughput
in
    >     >     >     general, though.
    >     >     >
    >     >     >     Just a slight modification:
    >     >     >     * a new record with new timestamp > (all the previous timestamps
+
    >     >     >     grace period) will cause all the old windows *in the same partition*
    >     >     >     to close
    >     >     >     * yes, expiry of the window depends only on the event time
    >     >     >
    >     >     >     Hope this helps!
    >     >     >     -John
    >     >     >
    >     >     >     On Thu, Jun 20, 2019 at 11:42 AM Parthasarathy, Mohan <mparthas@hpe.com>
wrote:
    >     >     >     >
    >     >     >     > Could you tell me a little more about the delays about
the record caches and how I can disable it ?
    >     >     >     >
    >     >     >     >  If I could summarize my problem:
    >     >     >     >
    >     >     >     > -A new record with a new timestamp > all records sent
before, I expect *all* of the old windows to close
    >     >     >     > -Expiry of the windows depends only on the event time
and not on the key
    >     >     >     >
    >     >     >     > Are these two statements correct ?
    >     >     >     >
    >     >     >     > Thanks
    >     >     >     > Mohan
    >     >     >     >
    >     >     >     > On 6/20/19, 9:17 AM, "John Roesler" <john@confluent.io>
wrote:
    >     >     >     >
    >     >     >     >     Hi!
    >     >     >     >
    >     >     >     >     In addition to setting the grace period to zero (or
some small
    >     >     >     >     number), you should also consider the delays introduced
by record
    >     >     >     >     caches upstream of the suppression. If you're closely
watching the
    >     >     >     >     timing of records going into and coming out of the
topology, this
    >     >     >     >     might also spoil your expectations. You could always
disable the
    >     >     >     >     record cache to make the system more predictable (although
this would
    >     >     >     >     hurt throughput in production).
    >     >     >     >
    >     >     >     >     Thanks,
    >     >     >     >     -John
    >     >     >     >
    >     >     >     >     On Wed, Jun 19, 2019 at 3:01 PM Parthasarathy, Mohan
<mparthas@hpe.com> wrote:
    >     >     >     >     >
    >     >     >     >     > We do explicitly set the grace period to zero.
I am going to try the new version
    >     >     >     >     >
    >     >     >     >     > -mohan
    >     >     >     >     >
    >     >     >     >     >
    >     >     >     >     > On 6/19/19, 12:50 PM, "Parthasarathy, Mohan"
<mparthas@hpe.com> wrote:
    >     >     >     >     >
    >     >     >     >     >     Thanks. We will give it a shot.
    >     >     >     >     >
    >     >     >     >     >     On 6/19/19, 12:42 PM, "Bruno Cadonna" <bruno@confluent.io>
wrote:
    >     >     >     >     >
    >     >     >     >     >         Hi Mohan,
    >     >     >     >     >
    >     >     >     >     >         I realized that my previous statement
was not clear. With a grace
    >     >     >     >     >         period of 12 hour, suppress would wait
for late events until stream
    >     >     >     >     >         time has advanced 12 hours before a result
would be emitted.
    >     >     >     >     >
    >     >     >     >     >         Best,
    >     >     >     >     >         Bruno
    >     >     >     >     >
    >     >     >     >     >         On Wed, Jun 19, 2019 at 9:21 PM Bruno
Cadonna <bruno@confluent.io> wrote:
    >     >     >     >     >         >
    >     >     >     >     >         > Hi Mohan,
    >     >     >     >     >         >
    >     >     >     >     >         > if you do not set a grace period,
the grace period defaults to 12
    >     >     >     >     >         > hours. Hence, suppress would wait
for an event that occurs 12 hour
    >     >     >     >     >         > later before it outputs a result.
Try to explicitly set the grace
    >     >     >     >     >         > period to 0 and let us know if it
worked.
    >     >     >     >     >         >
    >     >     >     >     >         > If it still does not work, upgrade
to version 2.2.1 if it is possible
    >     >     >     >     >         > for you. We had a couple of bugs
in suppress recently that are fixed
    >     >     >     >     >         > in that version.
    >     >     >     >     >         >
    >     >     >     >     >         > Best,
    >     >     >     >     >         > Bruno
    >     >     >     >     >         >
    >     >     >     >     >         > On Wed, Jun 19, 2019 at 8:37 PM
Parthasarathy, Mohan <mparthas@hpe.com> wrote:
    >     >     >     >     >         > >
    >     >     >     >     >         > > No, I have not set any grace
period. Is that mandatory ? Have you seen problems with suppress and windows expiring ?
    >     >     >     >     >         > >
    >     >     >     >     >         > > Thanks
    >     >     >     >     >         > > Mohan
    >     >     >     >     >         > >
    >     >     >     >     >         > > On 6/19/19, 12:41 AM, "Bruno
Cadonna" <bruno@confluent.io> wrote:
    >     >     >     >     >         > >
    >     >     >     >     >         > >     Hi Mohan,
    >     >     >     >     >         > >
    >     >     >     >     >         > >     Did you set a grace period
on the window?
    >     >     >     >     >         > >
    >     >     >     >     >         > >     Best,
    >     >     >     >     >         > >     Bruno
    >     >     >     >     >         > >
    >     >     >     >     >         > >     On Tue, Jun 18, 2019 at
2:04 AM Parthasarathy, Mohan <mparthas@hpe.com> wrote:
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     > On further debugging,
what we are seeing is that windows are expiring rather randomly as new messages are being
processed. . We tested with new key for every new message. We waited for the window time before
replaying new messages. Sometimes a new message would come in and create state. It takes several
messages to make some of the old windows to be closed (go past suppress to the next stage).
We have also seen where one of them never closed even but several other older ones expired.
 Then we explicitly sent a message with the same old key and then it showed up. Also, for
every new message, only one of the previous window expires even though there are several pending.
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     > If we don't use suppress,
then there is never an issue. With suppress, the behavior we are seeing is weird. We are using
2.1.0 version in DSL mode. Any clues on what we could be missing ? Why isn't there an order
in the way windows are closed ? As event time progresses by the new messages arriving, the
older ones should expire. Is that right understanding or not ?
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     > Thanks
    >     >     >     >     >         > >     > Mohan
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     > On 6/17/19, 3:43 PM,
"Parthasarathy, Mohan" <mparthas@hpe.com> wrote:
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     >     Hi,
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     >     We are using suppress
in the application. We see some state being created at some point in time. Now there is no
new data for a day or two. We send new data but the old window of data (where we see the state
being created) is not closing i.e not seeing it go through suppress and on to the next stage.
It is as though the state created earlier was purged. Is this possible ?
    >     >     >     >     >         > >     >
    >     >     >     >     >         > >     >     Thanks
    >     >     >     >     >         > >     >     Mohan
    >     >     >     >     >         > >     >
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