I downgraded spark to akka 2.1.0, and everything seems to work now. I'm going to run my tests a few more times , but I'd really have expected to see a failure by now w/ the 2.2.3 version.
I'll submit a patch shortly (need to fix some compile errors in streaming still). Matei -- I think I realize now that when you were talking about the expectation of a tcp connection staying alive, you were explaining why this is *not* a bug in the current release. You wouldn't end up in a situation where the executor thinks it finished the task, but the driver doesn't know about it, b/c if the connection dies, the executor wil get restarted. That makes sense. But, it seems like if we upgrade to akka 2.2.x, a lot of things change. I was probably wrong about seeing that problem in previous releases -- it was just a vague recollection, which fit my current theories, so I jumped to conclusions. thanks everyone On Fri, Nov 1, 2013 at 9:27 AM, Imran Rashid <[email protected]> wrote: > thanks everyone for all of the input. > > Matei: makes a lot more sense with your explanation of spark's expected > behavior of tcp, I can see why this makes sense now. But, to show my total > ignorance here, I'm wondering that when the connection does break, are you > sure all of your messages that you thought you sent before the break were > received? I'm guessing that you don't. Which is fine, if the response to > that is to have the executor just die completely, and restart. that was > the behavior I was initially observing with the code on the 2.10 branch, > where the executor handles a DisassociatedEvent explicitly, and dies. > > But -- is that the behavior we want? do we want it to be robust to tcp > connections breaking, without having to completely restart the executor? > you might say that dying & restarting will lead to correct behavior, even > if its inefficient. But sometimes, I've seen restarts so frequently that > no progress is made. > > I don't see why this changed w/ the different versions of akka -- I don't > see any relevant configuration settings that would change how "strongly" > tcp tries to keep the connection alive, but I may be missing something. > But it does seem like the netty configuration options have changed > completely between the two versions: > http://doc.akka.io/docs/akka/2.2.3/scala/remoting.html#Remote_Configuration > vs > http://doc.akka.io/docs/akka/2.0.5/scala/remoting.html > > btw, akka 2.1.0 also has been built for scala 2.10: > > http://search.maven.org/#artifactdetails|com.typesafe.akka|akka-remote_2.10|2.1.0|bundle > and its netty configuration is closer to 2.0.5: > http://doc.akka.io/docs/akka/2.1.0/scala/remoting.html > > perhaps someone more knowledge then me about netty & tcp can look through > the changes and decide what the right changes are. > > Prashant said: > >Before we conclude something about reliable messaging, I want you to for > once consider other possibilities like >actual network reconnection and may > be a GC pause ? Try connecting something like jconsole (or alike ) and >see > what happens on the driver and executor. > > > >My doubt are since we are using standalone mode where even master and > worker are also actors then if we see >a weird behaviour on the executor > and driver then Why not on master and worker too ? They should also break > >away from each other. For this reason, I am doubting our conclusions and > may be if we narrow down the >problem first before we conclude something. > It is a regression in akka 2.2.3 it uses more memory than it used to >be in > 2.1.x. > >See https://github.com/akka/akka/issues/1810 > > > Well, there could easily be the same problem with dropped connections > between master & worker -- they just communicate so little, it doesn't > really matter. The odds that a message gets dropped between them is very > low, only because there are barely any messages. > > I completely agree that the problem could be because of a contention, or > gc pause, etc. In fact, I'm only giving spark 24 out of 32 cores available > on each box, and 90g out of 125g memory. I've looked at gc a little with > jstat, and I did see some gc pauses but nothing ridiculous. > > But, I think the question remains. Suppose it is gc pauses, etc. that > cause the disassociation events; what do we do to fix it? How can we > diagnose the problem, and figure out which of the configuration variables > to tune? clearly, there *will be* long gc pauses, and the networking layer > needs to be able to deal with them. > > still I understand your desire to see if that might be the cause of the > problem in this particular case, so I will dig a little more. > > > (btw, should I move this thread to the dev list now? it is getting into > the nitty-gritty of implementation ...) > > On Fri, Nov 1, 2013 at 1:15 AM, Matei Zaharia <[email protected]>wrote: > >> Yes, so far they’ve been built on that assumption — not that Akka would >> *guarantee* delivery in that as soon as the send() call returns you know >> it’s delivered, but that Akka would act the same way as a TCP socket, >> allowing you to send a stream of messages in order and hear when the >> connection breaks. Maybe that isn’t what they want to provide, but I'd find >> it weird, because it’s very easy to write a server with this property. >> >> Matei >> >> On Oct 31, 2013, at 9:58 PM, Sriram Ramachandrasekaran < >> [email protected]> wrote: >> >> Sorry if I my understanding is wrong. May be, for this particular case it >> might be something to do with the load/network, but, in general, are you >> saying that, we build these communication channels(block manager >> communication, task events communication, etc) assuming akka would take >> care of it? I somehow feel that, it's being overly optimistic. Correct me >> if I am wrong. >> >> >> >> On Fri, Nov 1, 2013 at 10:08 AM, Matei Zaharia >> <[email protected]>wrote: >> >>> It’s true that Akka’s delivery guarantees are in general at-most-once, >>> but if you look at the text there it says that they differ by transport. In >>> the previous version, I’m quite sure that except maybe in very rare >>> circumstances or cases where we had a bug, Akka’s remote layer always kept >>> connections up between each pair of hosts. So the guarantee was that as >>> long as you haven’t received a “disconnected” event, your messages are >>> being delivered, though of course when you do receive that event you don’t >>> know which messages have really made it through unless you acked them. But >>> that didn’t matter for our use case — from our point of view an executor >>> was either up or down. >>> >>> For this reason I still think it should be possible to configure Akka to >>> do the same on 2.2. Most likely some timeouts just got lower. With large >>> heaps you can easily get a GC pause of 60 seconds, so these timeouts should >>> be in the minutes. >>> >>> If for some reason this isn’t the case, then we have a bigger problem — >>> there are *lots* of messages beyond task-finished that need to be sent >>> reliably, including things like block manager events (a block was added / >>> removed on this node) and commands to tell the block manager to drop data. >>> It would be silly to implement acks at the application level for all these. >>> But I doubt this is the case. Prashant’s observation that the standalone >>> cluster manager stayed up is a further sign that this might be due to GC. >>> >>> Matei >>> >>> On Oct 31, 2013, at 9:11 PM, Sriram Ramachandrasekaran < >>> [email protected]> wrote: >>> >>> Hi Imran, >>> Just to add, we've noticed dis-associations in a couple projects that we >>> built(using akka 2.2.x not spark). We went to some details to find out what >>> was happening. As Matei, suggested, Akka keeps the TCP connection open and >>> uses that to talk to peers. We noticed that in our case, initially, we were >>> seeing dis-associations generally at the end of keep-alive duration. So, >>> when the keep-alive duration ends, at the TCP layer, a keep-alive probe >>> gets sent to inform the peer on the other side that the connection is still >>> alive/valid. For some reason, the probe dint renew the keep-alive >>> connection and we saw a lot of dis-associations during that time. Later, we >>> realized this was not a pattern either. This >>> thread<https://groups.google.com/forum/#!msg/akka-user/RYxaPl_nby4/1USHDFIRgOkJ>contains >>> the full history of our discussions with the Akka team. It's still >>> open and unclear as to what was causing it for our case. >>> We tried tweaking various settings of akka(wrt heartbeats, failure >>> detector, even plugged-in our own failure detector with no effect). >>> >>> Imran - Just to clarify your point on message delivery - akka's message >>> delivery policy is at-most-once. However, there's no guarantee for a >>> message to be delivered to a peer. The documentation clearly explains that. >>> http://doc.akka.io/docs/akka/2.0.2/general/message-send-semantics.html. It's >>> the responsibility of the application developer to handle cases where >>> message is suspected to be not have been delivered. >>> >>> I hope this helps. >>> >>> >>> >>> >>> On Fri, Nov 1, 2013 at 8:35 AM, Imran Rashid <[email protected]>wrote: >>> >>>> >>>> unfortunately that change wasn't the silver bullet I was hoping for. >>>> Even with >>>> 1) ignoring DisassociatedEvent >>>> 2) executor uses ReliableProxy to send messages back to driver >>>> 3) turn up akka.remote.watch-failure-detector.threshold=12 >>>> >>>> >>>> there is a lot of weird behavior. First, there are a few >>>> DisassociatedEvents, but some that are followed by AssociatedEvents, so >>>> that seems ok. But sometimes the re-associations are immediately followed >>>> by this: >>>> >>>> 13/10/31 18:51:10 INFO executor.StandaloneExecutorBackend: got >>>> lifecycleevent: AssociationError >>>> [akka.tcp://sparkExecutor@<executor>:41441] >>>> -> [akka.tcp://spark@<driver>:41321]: Error [Invalid address: >>>> akka.tcp://spark@<driver>:41321] [ >>>> akka.remote.InvalidAssociation: Invalid address: >>>> akka.tcp://spark@<driver>:41321 >>>> Caused by: akka.remote.transport.Transport$InvalidAssociationException: >>>> The remote system has quarantined this system. No further associations to >>>> the remote system are possible until this system is restarted. >>>> ] >>>> >>>> On the driver, there are messages like: >>>> >>>> [INFO] [10/31/2013 18:51:07.838] >>>> [spark-akka.actor.default-dispatcher-3] [Remoting] Address [ >>>> akka.tcp://sparkExecutor@<executor>:46123] is now quarantined, all >>>> messages to this address will be delivered to dead letters. >>>> [WARN] [10/31/2013 18:51:10.845] >>>> [spark-akka.actor.default-dispatcher-20] >>>> [akka://spark/system/remote-watcher] >>>> Detected unreachable: [akka.tcp://sparkExecutor@<executor>:41441] >>>> >>>> >>>> and when the driver does decide that the executor has been terminated, >>>> it removes the executor, but doesn't start another one. >>>> >>>> there are a ton of messages also about messages to the block manager >>>> master ... I'm wondering if there are other parts of the system that need >>>> to use a reliable proxy (or some sort of acknowledgement). >>>> >>>> I really don't think this was working properly even w/ previous >>>> versions of spark / akka. I'm still learning about akka, but I think you >>>> always need an ack to be confident w/ remote communicate. Perhaps the old >>>> version of akka just had more robust defaults or something, but I bet it >>>> could still have the same problems. Even before, I have seen the driver >>>> thinking there were running tasks, but nothing happening on any executor -- >>>> it was just rare enough (and hard to reproduce) that I never bothered >>>> looking into it more. >>>> >>>> I will keep digging ... >>>> >>>> On Thu, Oct 31, 2013 at 4:36 PM, Matei Zaharia <[email protected] >>>> > wrote: >>>> >>>>> BTW the problem might be the Akka failure detector settings that seem >>>>> new in 2.2: http://doc.akka.io/docs/akka/2.2.3/scala/remoting.html >>>>> >>>>> Their timeouts seem pretty aggressive by default — around 10 seconds. >>>>> This can easily be too little if you have large garbage collections. We >>>>> should make sure they are higher than our own node failure detection >>>>> timeouts. >>>>> >>>>> Matei >>>>> >>>>> On Oct 31, 2013, at 1:33 PM, Imran Rashid <[email protected]> >>>>> wrote: >>>>> >>>>> pretty sure I found the problem -- two problems actually. And I think >>>>> one of them has been a general lurking problem w/ spark for a while. >>>>> >>>>> 1) we should ignore disassociation events, as you suggested earlier. >>>>> They seem to just indicate a temporary problem, and can generally be >>>>> ignored. I've found that they're regularly followed by AssociatedEvents, >>>>> and it seems communication really works fine at that point. >>>>> >>>>> 2) Task finished messages get lost. When this message gets sent, we >>>>> dont' know it actually gets there: >>>>> >>>>> >>>>> https://github.com/apache/incubator-spark/blob/scala-2.10/core/src/main/scala/org/apache/spark/executor/StandaloneExecutorBackend.scala#L90 >>>>> >>>>> (this is so incredible, I feel I must be overlooking something -- but >>>>> there is no ack somewhere else that I'm overlooking, is there??) So, >>>>> after >>>>> the patch, spark wasn't hanging b/c of the unhandled DisassociatedEvent. >>>>> It hangs b/c the executor has sent some taskFinished messages that never >>>>> get received by the driver. So the driver is waiting for some tasks to >>>>> finish, but the executors think they are all done. >>>>> >>>>> I'm gonna add the reliable proxy pattern for this particular >>>>> interaction and see if its fixes the problem >>>>> >>>>> http://doc.akka.io/docs/akka/2.2.3/contrib/reliable-proxy.html#introducing-the-reliable-proxy >>>>> >>>>> imran >>>>> >>>>> >>> >>> >>> -- >>> It's just about how deep your longing is! >>> >>> >>> >> >> >> -- >> It's just about how deep your longing is! >> >>
