+Mikhail Gryzykhin <mailto:[email protected]> +Rui Wang
<mailto:[email protected]> +Reza Rokni <mailto:[email protected]> who
have all done some investigations here.
On Fri, Nov 22, 2019 at 11:48 AM Jan Lukavský <[email protected]
<mailto:[email protected]>> wrote:
On 11/22/19 7:54 PM, Reuven Lax wrote:
On Fri, Nov 22, 2019 at 10:19 AM Jan Lukavský <[email protected]
<mailto:[email protected]>> wrote:
Hi Reuven,
I didn't investigate that particular one, but looking into
that now, it looks that is (same as the "classic" join
library) builds around CoGBK. Is that correct? If yes, then
it essentially means that it:
- works only for cases where both sides have the same
windowfn (that is limitation of Flatten that precedes CoGBK)
Correct. Did you want to join different windows? If so what are
the semantics? If the lhs has FixedWindows and the rhs has
SessionWindows, what do you want the join semantics to be? The
only thing I could imagine would be for the user to provide some
function telling the join how to map the windows together, but
that could be pretty complicated.
I don't want to go too far into details, but generally both lhs
and rhs can be put onto time line and then full join can be
defined as each pair of (lhs, first preceding rhs) and (rhs, first
preceding lhs). Then the end of window is semantically just
clearing the joined value (setting it to null, thus at the end of
window there will be pair (lhs, null) or (null, rhs) in case of
full outer join). This way any combination of windows is possible,
because all window does is that it "scopes" validity of respective
values (lhs, rhs).
I think it is very valid to hope to do a join in the sense of a
relational join where it is row-to-row. In this case, Beam's concept
of windowing may or may not make sense. It is just a tool for the job.
It is just a grouping key that provides a time when state can be
deleted. So I would say your use case is more global window to global
window join. That is what I think of as a true stream-to-stream join
anyhow. You probably don't want to wait forever for output. So you'll
need to use some knob other than Beam windows or triggers.
Reza has prototyped a join like you describe here:
https://github.com/apache/beam/pull/9032
If your join condition explicitly includes the event time distance
between elements, then it could "just work". If that isn't really part
of your join condition, then you will have to see this restriction as
a "knob" that you tweak on your results.
- when using global window, there has to be trigger and
(afaik) there is no trigger that would guarantee firing after
each data element (for early panes) (because triggers are
there to express cost-latency tradeoff, not semantics)
Can you explain the use case where this matters? If you do
trigger elementCountAtLeast(1) on the join, then the consumer
will simply see a continuous stream of outputs. I'm not sure I
understand why the consumer cares that some of those outputs were
in a pane that really held 3 outputs instead of 1.
What I'm trying to solve is basically this:
- lhs is event stream
- rhs is stream of a "state updates"
purpose of the join is "take each event, pair it with currently
valid state and produce output and possibly modified state". I
cannot process two events at a time, because first event can
modify the state and the subsequent event should see this. It is
not a "simple" stateful pardo either, because the state can be
modified externally (not going into too much detail here, but e.g.
by writing into kafka topic).
Reuven's explanation is missing some detail. If the CoGBK is in
discarding mode, then it will miss join results. If the CoGBK is in
accumulating mode, it will duplicate join results. This is a known
problem and the general solution is retractions.
Basically, CoGBK-based joins just don't work with triggers until we
have retractions.
Moreover, I'd like to define the join semantics so that when
there are available elements from both sides, the fired pane
should be ON_TIME, not EARLY. That essentially means that the
fully general case would not be built around (Co)GBK, but
stateful ParDo. There are specific options where this fully
general case "degrades" into forms that can be efficiently
expressed using (Co)GBK, that is true.
BTW building this around stateful DoFn might be a better fit. The
main reason I didn't is because we would need a good distributed
MapState (something discussed fairly recently on the list), and
that is not yet built. Once we had that, I might be inclined to
rewrite this join on stateful DoFn.
Yes, the sorted state helps for streaming case. But I'd be careful
about that for batch case, where this might lead to high pressure
on the state (and InMemoryStateInternals might OOME for instance).
However can you explain what you are expecting from the pane? An
EARLY pane simply means that we are producing output before the
end of the window. If you are in the global window triggering
every element, then every output is EARLY. It might seem weird if
you are interpreting EARLY as "outputting data that isn't ready,"
however that's not what EARLY is defined to be. Any change to the
pane semantics would be a major breaking change to very
fundamental semantics.
I wonder if you are really objecting to the name EARLY and
ON_TIME? Maybe we would've been better off tagging it
BEFORE_WINDOW_END instead of EARLY, to make it clear what is meant?
Essentially I don't object anything here. I'm missing solution to
the "event vs. state" join described above. I was thinking about
how to make these types of problems more user friendly and it
essentially leads to creating a somewhat more generic semantics of
join, where end-of-window is converted into "'value-delete events"
and then just joining by the "previous" or "valid" value (yes,
this relates to validity windows mentioned on Beam Summit Europe).
It actually turns out that with some work we could define quite
"naturally" a join on two streams with global window and no
trigger. It would even function with lowest latency possible (but
yes, with the highest expenses, it is actually the introduction of
(same!) windows that enable certain optimizations). It the
correctly defines semantics for different windows, although the
result would be (probably unexpectedly) windowed using global
window. But that doesn't seem to be any breaking change, because
it is currently not possible (any such pipeline will not be
validated).
Maybe for reference, the unwindowed join would be what is
described here [1]
[1]
https://cwiki.apache.org/confluence/display/KAFKA/Kafka+Streams+Join+Semantics#KafkaStreamsJoinSemantics-KStream-KTableJoin
Jan
On 11/22/19 6:47 PM, Reuven Lax wrote:
Have you seen the Join library that is part of schemas? I'm
curious whether this fits your needs, or there's something
lacking there.
On Fri, Nov 22, 2019 at 12:31 AM Jan Lukavský
<[email protected] <mailto:[email protected]>> wrote:
Hi,
based on roadmap [1], we would like to define and
implement a full set
of (unified) stream-stream joins. That would include:
- joins (left, right, full outer) on global window
with "immediate
trigger"
- joins with different windowing functions on left and
right side
The approach would be to define these operations in a
natural way, so
that the definition is aligned with how current joins
work (same
windows, cartesian product of values with same keys,
output timestamp
projected to the end of window, etc.). Because this
should be a generic
approach, this effort should probably be part of join
library, that can
the be reused by other components, too (e.g. SQL).
The question is - is (or was) there any effort that we
can build upon?
Or should this be designed from scratch?
Jan
[1] https://beam.apache.org/roadmap/euphoria/
