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From Aljoscha Krettek <aljos...@apache.org>
Subject Re: Semantics of PCollection.isBounded
Date Thu, 16 May 2019 08:53:23 GMT
Please take this with a grain of salt, because I might be a bit rusty on this.

I think the Beam model does not prescribe any ordering (by time or otherwise) on inputs. Mostly
because always requiring it would be prohibitively expensive on most Runners, especially global
sorting.

If you want to have sorting by key, you could do a GroupByKey and then sort the groups in
memory. This only works, of course, if your groups are not too large.

> On 15. May 2019, at 21:01, Jan Lukavský <je.ik@seznam.cz> wrote:
> 
> Hmmm, looking into the code of FlinkRunner (and also by observing results from the stateful
ParDo), it seems, that I got it wrong from the beginning. The data is not sorted before the
stateful ParDo, but that a little surprises me. How the operator should work in this case?
It would mean, that in the batch case I have to hold arbitrarily long allowedLateness inside
the BagState, which seems to be kind of suboptimal. Or am I missing something obvious here?
I'll describe the use case in more detail, let's suppose I have a series of ones and zeros
and I want emit at each time point value of 1 if value changes from 0 to 1, value of -1 if
changes from 1 to 0 and 0 otherwise. So:
> 
>  0, 1, 1, 0, 0, 1 -> 0, 1, 0, -1, 0, 1
> 
> Does anyone have a better idea how to solve it? And if not, how to make it running on
batch, without possibly infinite buffer? Should the input to stateful ParDo be sorted in batch
case? My intuition would be that it should be, because in my understanding of "batch as a
special case of streaming" in batch case, there is (by default) single window, time advances
from -inf to +inf at the end, and the data contains no out of order data, in places where
this might matter (which therefore enables some optimizations). The order would be relevant
only in the stateful ParDo, I'd say.
> 
> Jan
> 
> On 5/15/19 8:34 PM, Jan Lukavský wrote:
>> Just to clarify, I understand, that changing semantics of the PCollection.isBounded,
 is probably impossible now, because would probably introduce chicken egg problem. Maybe I
will state it more clearly - would it be better to be able to run bounded pipelines using
batch semantics on DirectRunner (including sorting before stateful ParDos), or would it be
better to come up with some way to notify the pipeline that it will be running in a streaming
way although it consists only of bounded inputs? And I'm not saying how to do it, just trying
to find out if anyone else ever had such a need.
>> 
>> Jan
>> 
>> On 5/15/19 5:20 PM, Jan Lukavský wrote:
>>> Hi,
>>> 
>>> I have come across unexpected (at least for me) behavior of some apparent inconsistency
of how a PCollection is processed in DirectRunner and what PCollection.isBounded signals.
Let me explain:
>>> 
>>>  - I have a stateful ParDo, which needs to make sure that elements arrive in
order - it accomplishes this by defining BagState for buffering input elements and sorting
them inside this buffer, it also keeps track of element with highest timestamp to somehow
estimate local watermark (minus some allowed lateness), to know when to remove elements from
the buffer, sort them by time and pass them to some (time ordered) processing
>>> 
>>>  - this seems to work well for streaming (unbounded) data
>>> 
>>>  - for batch (bounded) data the semantics of stateful ParDo should be (please
correct me if I'm wrong) that elements always arrive in order, because the runner can sort
them by timestamp
>>> 
>>>  - this implies that for batch processed input (bounded) the allowedLateness
can be set to zero, so that the processing is little more effective, because it doesn't have
to use the BagState at all
>>> 
>>>  - now, the trouble seems to be, that DirectRunner always uses streaming processing,
even if the input is bounded (that is by definition possible), but there is no way now to
know when it is possible to change allowed lateness to zero (because input will arrive ordered)
>>> 
>>>  - so - it seems to me, that either DirectRunner should apply sorting to stateful
ParDo, when it processes bounded data (the same way that other runners do), or it can apply
streaming processing, but then it should change PCollection.isBounded to UNBOUNDED, even if
the input is originally bounded
>>> 
>>>  - that way, the semantics of PCollection.isBounded, would be not if the data
are known in advance to be finite, but *how* the data are going to be processed, which is
much more valuable (IMO)
>>> 
>>> Any thoughts?
>>> 
>>>  Jan
>>> 


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