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https://issues.apache.org/jira/browse/BEAM-696?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15566498#comment-15566498
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Amit Sela edited comment on BEAM-696 at 10/11/16 8:42 PM:
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Does Dataflow "buffer until trigger..." if there are no sideInputs assigned ?
Combiners are a very important optimization (Spark for sure, but I guess other
runners too), and Sessions (or any other merging windows) can be used without
sideInput, so I guess a runner should defer *only* for merging windows and
*only* if they are used with sideInputs..
I think my question is: where do we draw the line ?
I could argue that in order to use sideInputs for merging windows a pipeline
author should use explicit {{GroupByKey}} followed by {{Combine.GroupedValues}}
or risk a non-deterministic result.
There are analytical cases where you actually want to do that such as
identifying a sequence of events in a time frame. It's clear you can't use
combiners here and are willing to pay the price of shuffling and grouping the
events (+maintaining non-compactable state).
I don't know if you have/can access such statistics, but I wonder what % of
pipelines with sessions also use sideInputs (and would be affected from
non-deterministic behaviour of combiners) ?
was (Author: amitsela):
Does Dataflow "buffer until trigger..." if there are no sideInputs assigned ?
Combiners are a very important optimization (Spark for sure, but I guess other
runners too), and Sessions (or any other merging windows) can be used without
sideInput, so I guess a runner should defer *only* for merging windows and
*only* if they are used with sideInputs..
I think my question is: where do we draw the line ?
I could argue that in order to use sideInputs for merging windows a pipeline
author should use explicit {{GroupByKey}} followed by {{Combine.GroupedValues}}
or risk a non-deterministic result.
There are analytical cases where you actually want to do that such as
identifying a sequence of events in a time frame. It's clear you can't use
combiners here and are willing to pay the price of shuffling and grouping the
events (+maintaining non-compactable state).
I don't know if you have/can access such statistics, but I wonder what % of
pipelines with sessions also use sideInputs ?
> Side-Inputs non-deterministic with merging main-input windows
> -------------------------------------------------------------
>
> Key: BEAM-696
> URL: https://issues.apache.org/jira/browse/BEAM-696
> Project: Beam
> Issue Type: Bug
> Components: beam-model
> Reporter: Ben Chambers
> Assignee: Pei He
>
> Side-Inputs are non-deterministic for several reasons:
> 1. Because they depend on triggering of the side-input (this is acceptable
> because triggers are by their nature non-deterministic).
> 2. They depend on the current state of the main-input window in order to
> lookup the side-input. This means that with merging
> 3. Any runner optimizations that affect when the side-input is looked up may
> cause problems with either or both of these.
> This issue focuses on #2 -- the non-determinism of side-inputs that execute
> within a Merging WindowFn.
> Possible solution would be to defer running anything that looks up the
> side-input until we need to extract an output, and using the main-window at
> that point. Specifically, if the main-window is a MergingWindowFn, don't
> execute any kind of pre-combine, instead buffer all the inputs and combine
> later.
> This could still run into some non-determinism if there are triggers
> controlling when we extract output.
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