On Fri, 21 Jun 2019 at 18:02, Jan Lukavský <[email protected]
<mailto:[email protected]>> wrote:
Hi Reza,
great prezentation on the Beam Summit. I have had a few posts
here in the list during last few weeks, some of which might
actually be related to both looping timers and validity
windows. But maybe you will be able to see a different
approach, than I do, so questions:
a) because of [1] timers might not be exactly ordered (the
JIRA talks about DirectRunner, but I suppose the issue is
present on all runners that use immutable bundles of size >
1, so might be related to Dataflow as well). This might cause
issues when you try to introduce TTL for looping timers,
because the TTL timer might get fired before regular looping
timer, which might cause incorrect results (state cleared
before have been flushed).
The TTL check would be in the same Timer rather than a separate
Timer. The max value processed in each OnTimer call would be
stored in valuestate and used as base to know how long it has
been seen the pipeline has seen an external value for that key.
b) because stateful pardo doesn't sort by timestamp, that
implies, that you have to store last values in BagState (as
opposed to the blog, where you just emit identity value of
sum operation), right?
You can store it in ValueState rather than BagState, but yes you
store that value in State ready for the next OnTimer() fire.
c) because of how stateful pardo currently works on batch,
does that imply that all values (per key) would have to be
stored in memory? would that scale?
This is one of the sharp edges and the answer is ... it depends
:-) I would recommend always using a FixedWindow+Combiner before
this step, this will compress the values into something much
smaller. For example in case of building 'candles' this will
compress down to low/hi/first/last values per FixedWindow length.
If the window length is very small there maybe no compression,
but in most cases I have seen this is a ok compromise.
There is a discussion about problem a) in [2], but maybe
there is some different approach possible. For problem b) and
c) there is a proposal [3]. When the input is sorted, it
starts to work both in batch and with ValueState, because the
last value is the *valid* value.
There was also a discussion on dev@ around a sorted Map state,
which would be very cool for this usecase.
This has even connection with the mentioned validity windows,
as if you sort by timestamp, the _last_ value is the _valid_
value, so is essentially boils down to keep single value per
key (and again, starts to work in both batch and stream).
one for Tyler :-)
I even have a suspicion, that sorting by timestamp has close
relation to retractions, because when you are using sorted
streams, retractions actually became only diff between last
emitted pane, and current pane. That might even help
implement that in general, but I might be missing something.
This just popped in my head today, as I was thinking why
there was actually no (or little) need for retractions in
Euphoria model (very similar to Beam, actually differs by the
sorting thing :)), and why it the need pops out so often in Beam.
Retractions will be possible with this, but it does mean that we
would need to keep old versions around, something built in would
be very cool rather than building it with this pattern.
I'd be very happy to hear what you think about all of this.
Cheers,
Jan
[1] https://issues.apache.org/jira/browse/BEAM-7520
[2]
https://lists.apache.org/thread.html/1a3a0dd9da682e159f78f131d335782fd92b047895001455ff659613@%3Cdev.beam.apache.org%3E
[3]
https://docs.google.com/document/d/1ObLVUFsf1NcG8ZuIZE4aVy2RYKx2FfyMhkZYWPnI9-c/edit?usp=sharing
On 6/21/19 8:12 AM, Reza Rokni wrote:
Great question, one thing that we did not cover in the blog
and I think we should have is the use case where you would
want to bootstrap the pipeline.
One option would be on startup to have an extra bounded
source that is read and flattened into the main pipeline,
the source will need to contain values in Timestamped<V>
format which would correspond to the first window that you
would like to kickstart the process from. Will see if I can
try and find some time to code up an example and add that
and the looping timer code into the Beam patterns.
https://beam.apache.org/documentation/patterns/overview/
Cheers
Reza
On Fri, 21 Jun 2019 at 07:59, Manu Zhang
<[email protected] <mailto:[email protected]>>
wrote:
Indeed interesting pattern.
One minor question. It seems the timer is triggered by
the first element so what if there is no data in the
"first interval" ?
Thanks for the write-up.
Manu
On Wed, Jun 19, 2019 at 12:15 PM Reza Rokni
<[email protected] <mailto:[email protected]>> wrote:
Hi folks,
Just wanted to drop a note here on a new pattern
that folks may find interesting, called Looping
Timers. It allows for default values to be created
in interval windows in the absence of any external
data coming into the pipeline. The details are in
this blog below:
https://beam.apache.org/blog/2019/06/11/looping-timers.html
Its main utility is when dealing with time series
data. There are still rough edges, like dealing with
TTL and it would be great to hear feedback on ways
it can be improved.
The next pattern to publish in this domain will
assist will hold and propagation of values from one
interval window to the next, which coupled to
looping timers starts to solve some interesting
problems.
Cheers
Reza
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