Thanks for filing those. As for how not doing a copy is "safe," it's not really. Beam simply asserts that you MUST NOT mutate your inputs (and direct runners, which are used during testing, do perform extra copies and checks to catch violations of this requirement).
On Thu, May 2, 2019 at 1:02 PM Jozef Vilcek <[email protected]> wrote: > > I have created > https://issues.apache.org/jira/browse/BEAM-7204 > https://issues.apache.org/jira/browse/BEAM-7206 > > to track these topics further > > On Wed, May 1, 2019 at 1:24 PM Jozef Vilcek <[email protected]> wrote: >> >> >> >> On Tue, Apr 30, 2019 at 5:42 PM Kenneth Knowles <[email protected]> wrote: >>> >>> >>> >>> On Tue, Apr 30, 2019, 07:05 Reuven Lax <[email protected]> wrote: >>>> >>>> In that case, Robert's point is quite valid. The old Flink runner I >>>> believe had no knowledge of fusion, which was known to make it extremely >>>> slow. A lot of work went into making the portable runner fusion aware, so >>>> we don't need to round trip through coders on every ParDo. >>> >>> >>> The old Flink runner got fusion for free, since Flink does it. The new >>> fusion in portability is because fusing the runner side of portability >>> steps does not achieve real fusion >> >> >> Aha, I see. So the feature in Flink is operator chaining and Flink per >> default initiate copy of input elements. In case of Beam coders copy seems >> to be more noticable than native Flink. >> So do I get it right that in portable runner scenario, you do similar >> chaining via this "fusion of stages"? Curious here... how is it different >> from chaining so runner can be sure that not doing copy is "safe" with >> respect to user defined functions and their behaviour over inputs? >> >>>> >>>> >>>> Reuven >>>> >>>> On Tue, Apr 30, 2019 at 6:58 AM Jozef Vilcek <[email protected]> wrote: >>>>> >>>>> It was not a portable Flink runner. >>>>> >>>>> Thanks all for the thoughts, I will create JIRAs, as suggested, with my >>>>> findings and send them out >>>>> >>>>> On Tue, Apr 30, 2019 at 11:34 AM Reuven Lax <[email protected]> wrote: >>>>>> >>>>>> Jozef did you use the portable Flink runner or the old one? >>>>>> >>>>>> Reuven >>>>>> >>>>>> On Tue, Apr 30, 2019 at 1:03 AM Robert Bradshaw <[email protected]> >>>>>> wrote: >>>>>>> >>>>>>> Thanks for starting this investigation. As mentioned, most of the work >>>>>>> to date has been on feature parity, not performance parity, but we're >>>>>>> at the point that the latter should be tackled as well. Even if there >>>>>>> is a slight overhead (and there's talk about integrating more deeply >>>>>>> with the Flume DAG that could elide even that) I'd expect it should be >>>>>>> nowhere near the 3x that you're seeing. Aside from the timer issue, >>>>>>> sounds like the cloning via coders is is a huge drag that needs to be >>>>>>> addressed. I wonder if this is one of those cases where using the >>>>>>> portability framework could be a performance win (specifically, no >>>>>>> cloning would happen between operators of fused stages, and the >>>>>>> cloning between operators could be on the raw bytes[] (if needed at >>>>>>> all, because we know they wouldn't be mutated). >>>>>>> >>>>>>> On Tue, Apr 30, 2019 at 12:31 AM Kenneth Knowles <[email protected]> >>>>>>> wrote: >>>>>>> > >>>>>>> > Specifically, a lot of shared code assumes that repeatedly setting a >>>>>>> > timer is nearly free / the same cost as determining whether or not to >>>>>>> > set the timer. ReduceFnRunner has been refactored in a way so it >>>>>>> > would be very easy to set the GC timer once per window that occurs in >>>>>>> > a bundle, but there's probably some underlying inefficiency around >>>>>>> > why this isn't cheap that would be a bigger win. >>>>>>> > >>>>>>> > Kenn >>>>>>> > >>>>>>> > On Mon, Apr 29, 2019 at 10:05 AM Reuven Lax <[email protected]> wrote: >>>>>>> >> >>>>>>> >> I think the short answer is that folks working on the BeamFlink >>>>>>> >> runner have mostly been focused on getting everything working, and >>>>>>> >> so have not dug into this performance too deeply. I suspect that >>>>>>> >> there is low-hanging fruit to optimize as a result. >>>>>>> >> >>>>>>> >> You're right that ReduceFnRunner schedules a timer for each element. >>>>>>> >> I think this code dates back to before Beam; on Dataflow timers are >>>>>>> >> identified by tag, so this simply overwrites the existing timer >>>>>>> >> which is very cheap in Dataflow. If it is not cheap on Flink, this >>>>>>> >> might be something to optimize. >>>>>>> >> >>>>>>> >> Reuven >>>>>>> >> >>>>>>> >> On Mon, Apr 29, 2019 at 3:48 AM Jozef Vilcek <[email protected]> >>>>>>> >> wrote: >>>>>>> >>> >>>>>>> >>> Hello, >>>>>>> >>> >>>>>>> >>> I am interested in any knowledge or thoughts on what should be / is >>>>>>> >>> an overhead of running Beam pipelines instead of pipelines written >>>>>>> >>> on "bare runner". Is this something which is being tested or >>>>>>> >>> investigated by community? Is there a consensus in what bounds >>>>>>> >>> should the overhead typically be? I realise this is very runner >>>>>>> >>> specific, but certain things are imposed also by SDK model itself. >>>>>>> >>> >>>>>>> >>> I tested simple streaming pipeline on Flink vs Beam-Flink and found >>>>>>> >>> very noticeable differences. I want to stress out, it was not a >>>>>>> >>> performance test. Job does following: >>>>>>> >>> >>>>>>> >>> Read Kafka -> Deserialize to Proto -> Filter deserialisation errors >>>>>>> >>> -> Reshuffle -> Report counter.inc() to metrics for throughput >>>>>>> >>> >>>>>>> >>> Both jobs had same configuration and same state backed with same >>>>>>> >>> checkpointing strategy. What I noticed from few simple test runs: >>>>>>> >>> >>>>>>> >>> * first run on Flink 1.5.0 from CPU profiles on one worker I have >>>>>>> >>> found out that ~50% time was spend either on removing timers from >>>>>>> >>> HeapInternalTimerService or in java.io.ByteArrayOutputStream from >>>>>>> >>> CoderUtils.clone() >>>>>>> >>> >>>>>>> >>> * problem with timer delete was addressed by FLINK-9423. I have >>>>>>> >>> retested on Flink 1.7.2 and there was not much time is spend in >>>>>>> >>> timer delete now, but root cause was not removed. It still remains >>>>>>> >>> that timers are frequently registered and removed ( I believe from >>>>>>> >>> ReduceFnRunner.scheduleGarbageCollectionTimer() in which case it is >>>>>>> >>> called per processed element? ) which is noticeable in GC >>>>>>> >>> activity, Heap and State ... >>>>>>> >>> >>>>>>> >>> * in Flink I use FileSystem state backed which keeps state in >>>>>>> >>> memory CopyOnWriteStateTable which after some time is full of >>>>>>> >>> PaneInfo objects. Maybe they come from PaneInfoTracker activity >>>>>>> >>> >>>>>>> >>> * Coder clone is painfull. Pure Flink job does copy between >>>>>>> >>> operators too, in my case it is via Kryo.copy() but this is not >>>>>>> >>> noticeable in CPU profile. Kryo.copy() does copy on object level >>>>>>> >>> not boject -> bytes -> object which is cheaper >>>>>>> >>> >>>>>>> >>> Overall, my observation is that pure Flink can be roughly 3x faster. >>>>>>> >>> >>>>>>> >>> I do not know what I am trying to achieve here :) Probably just >>>>>>> >>> start a discussion and collect thoughts and other experiences on >>>>>>> >>> the cost of running some data processing on Beam and particular >>>>>>> >>> runner. >>>>>>> >>>
