Great. It all makes sense now. With the SSD fix, we also upgrade to 0.10.1. So we should see pretty consistent process-ns (which we do).
Based on what you have described, the following should be true in 0.10.1: event-loop-ns = choose-ns + process-ns + window-ns (if necessary) + commit-ns (if necessary) Is this correct? Thanks, David On Wed, Aug 24, 2016 at 11:27 AM Jacob Maes <jacob.m...@gmail.com> wrote: > A couple other notes. > > Prior to Samza 10.1, the choose-ns was part of process-ns. So when > choose-ns and process-ns are both high (around 10,000,000 == 10ms, which is > the default poll timeout), that usually means the task is caught up. In > Samza 10.1 the same is true if ONLY choose-ns is high. process-ns is always > the time spent in the process() method. > > Based on the above, the metric numbers you provided after the SSD fix all > look reasonable. They're all sub-millisecond and since choose-ns and > process-ns are low, it seems that the container is chewing through messages > at a good rate. > > So I would conclude that the SSD fix was probably the right one and it just > took the job a while to catch up to the backlog of messages. Once it caught > up, the choose-ns and process-ns increased, which is normal when the > processor is waiting for new messages. > > -Jake > > On Wed, Aug 24, 2016 at 9:05 AM, Jacob Maes <jacob.m...@gmail.com> wrote: > > > Hey David, > > > > Answering the most recent question first, since it's also the easiest. > :-) > > > > Is choose-ns the total number of ms used to choose a message from the > input > >> stream? What are some gating factors (e.g. serialization?) for this > >> metric? > > > > It's the amount of time the event loop spent getting new messsages for > > process(). It includes deserialization time and poll time which we added > > new metrics for, in Samza 10.1. Typically deserialization time is pretty > > consistent, so when you see a spike in choose-ns, it's usually because > the > > event loop is waiting for new messages. The two most common cases when > it's > > waiting are: > > 1. There are no new messages in the topic partition. This is good because > > it means the processor is caught up. > > 2. The consumer is slow and/or the buffer isn't large enough so the > > BrokerProxy isn't able to keep enough messages buffered to keep the event > > loop busy. This is uncommon because the buffer is defaulted to 50,000 > > messages, which should be plenty. But if it happens, it's bad. To control > > this behavior, see the following properties in the config table ( > > http://samza.apache.org/learn/documentation/0.10/jobs/ > > configuration-table.html) > > systems.system-name.samza.fetch.threshold > > task.poll.interval.ms > > > > > > > > On Wed, Aug 24, 2016 at 8:52 AM, David Yu <david...@optimizely.com> > wrote: > > > >> More updates: > >> 1. process-envelopes rate finally stabilized and converged. Consumer lag > >> is > >> down to zero. > >> 2. avg choose-ns across containers dropped overtime > >> <https://www.dropbox.com/s/z4iiilvd7c1wrjc/Screenshot%202016 > >> -08-24%2010.46.22.png?dl=0>, > >> which I assume is a good thing. > >> > >> My question: > >> Is choose-ns the total number of ms used to choose a message from the > >> input > >> stream? What are some gating factors (e.g. serialization?) for this > >> metric? > >> > >> Thanks, > >> David > >> > >> On Wed, Aug 24, 2016 at 12:34 AM David Yu <david...@optimizely.com> > >> wrote: > >> > >> > Some metric updates: > >> > 1. We started seeing some containers with a higher choose-ns > >> > <https://www.dropbox.com/s/06n3awdwn8ntfxd/Screenshot%202016 > >> -08-24%2000.26.07.png?dl=0>. > >> > Not sure what would be the cause of this. > >> > 2. We are seeing very different process-envelopes values across > >> containers > >> > <https://www.dropbox.com/s/n1wxtngquv607nb/Screenshot%202016 > >> -08-24%2000.21.05.png?dl=0> > >> > . > >> > > >> > > >> > > >> > On Tue, Aug 23, 2016 at 5:56 PM David Yu <david...@optimizely.com> > >> wrote: > >> > > >> >> Hi, Jake, > >> >> > >> >> Thanks for your suggestions. Some of my answers inline: > >> >> > >> >> 1. > >> >> On Tue, Aug 23, 2016 at 11:53 AM Jacob Maes <jacob.m...@gmail.com> > >> wrote: > >> >> > >> >>> Hey David, > >> >>> > >> >>> A few initial thoughts/questions: > >> >>> > >> >>> > >> >>> 1. Is this job using RocksDB to store the aggregations? If so, is > >> it > >> >>> running on a machine with SSDs? We've seen a few performance > issues > >> >>> related > >> >>> to RocksDB. > >> >>> 1. Not running on SSD causes slowness on disk > >> >> > >> >> - [David] This definitely pointed me to the right direction in my > >> >> investigation. We do use RocksDB and just realized that our YARN > >> cluster is > >> >> using c3.xlarge EC2 instances and is using a mixture of EBS and local > >> SSD > >> >> storage. After digging around, we noticed that some containers were > >> >> persisting their KV stores in SSD while others were using EBS. We > just > >> >> updated our YARN config to use SSD only before redeployed our jobs. > So > >> far > >> >> everything looks good. Will report back on the performance update. > >> >> > >> >>> 2. Prior to Samza 10.1, samza would excessively flush the > store > >> to > >> >>> disk, causing RocksDB compaction issues (stalls) - SAMZA-957 > >> >>> > >> >> - [David] We did notice that the log cleaner thread died on one of > our > >> >> brokers. Not sure if this was the same problem you pointed out. > >> Following > >> >> errors are logged: > >> >> > >> >> 2016-08-15 10:00:56,475 ERROR kafka.log.LogCleaner: > >> >> [kafka-log-cleaner-thread-0], Error due to > >> >> > >> >> java.lang.IllegalArgumentException: requirement failed: 5865800 > >> messages > >> >> in segment > session-store-2.0-tickets-changelog-9/00000000000009548937. > >> log > >> >> but offset map can fit only 5033164. You can increase > >> >> log.cleaner.dedupe.buffer.size or decrease log.cleaner.threads > >> >> > >> >> at scala.Predef$.require(Predef.scala:219) > >> >> > >> >> We had to cleanup the changelog topic and restart the broker to bring > >> >> back the cleaner thread. > >> >> > >> >>> 3. When the RocksDB store is used as a queue, the iterator can > >> >>> suffer > >> >>> performance issues due to RocksDBs tombstoning. ( > >> >>> > >> >>> https://github.com/facebook/rocksdb/wiki/Implement-Queue-Ser > >> vice-Using-RocksDB > >> >>> ) > >> >>> > >> >> - [David] We use RocksDB to keep track of opening sessions and use > >> >> sessionId (a random hash) as the key. In that sense, this does not > >> sound > >> >> like a queue. But we do iterate and delete closed sessions during > >> windowing > >> >> on a minute by minute basis. > >> >> > >> >> 2. Is the "messages-behind-high-watermark" metric non-zero? > >> >>> > >> >> -[David] Yes. > >> >> > >> >>> 3. The SamzaContainerMetrics might be useful too. Particularly > >> >>> "choose-ns" and "commit-ns" > >> >>> > >> >> -[David] We are seeing the following from one of the containers > (after > >> >> the SSD fix mentioned above): > >> >> choose-ns=61353 > >> >> commit-ns=306328 (what does this metric indicate? Is this in ms?) > >> >> process-ns=248260 > >> >> window-ns=150717 > >> >> > >> >>> 4. The only time I've personally seen slowness on the producer is > >> if > >> >>> it's configured for acks="all". What is the producer config from > >> the > >> >>> log? > >> >>> > >> >> - [David] We did not override this. So should be the default value > >> (1?). > >> >> > >> >> 5. The window time is high, but since it's only called once per > >> minute, > >> >>> it looks like it only represents 1% of the event loop > utilization. > >> So > >> >>> I > >> >>> don't think that's a smoking gun. > >> >>> > >> >>> -Jake > >> >>> > >> >>> On Tue, Aug 23, 2016 at 9:18 AM, David Yu <david...@optimizely.com> > >> >>> wrote: > >> >>> > >> >>> > Dear Samza guys, > >> >>> > > >> >>> > We are here for some debugging suggestions on our Samza job > >> (0.10.0), > >> >>> which > >> >>> > lags behind on consumption after running for a couple of hours, > >> >>> regardless > >> >>> > of the number of containers allocated (currently 5). > >> >>> > > >> >>> > Briefly, the job aggregates events into sessions (in Avro) during > >> >>> process() > >> >>> > and emits snapshots of the open sessions using window() every > >> minute. > >> >>> This > >> >>> > graph > >> >>> > <https://www.dropbox.com/s/utywr1j5eku0ec0/Screenshot% > >> >>> > 202016-08-23%2010.33.16.png?dl=0> > >> >>> > shows > >> >>> > you where processing started to lag (red is the number of events > >> >>> received > >> >>> > and green is the number of event processed). The end result is a > >> steady > >> >>> > increase of the consumer lag > >> >>> > <https://www.dropbox.com/s/fppsv91c339xmdb/Screenshot% > >> >>> > 202016-08-23%2010.19.27.png?dl=0>. > >> >>> > What we are trying to track down is where the performance > bottleneck > >> >>> is. > >> >>> > But it's unclear at the moment if that's in Samza or in Kafka. > >> >>> > > >> >>> > What we know so far: > >> >>> > > >> >>> > - Kafka producer seems to take a while writing to the > downstream > >> >>> topic > >> >>> > (changelog and session snapshots) shown by various timers. Not > >> sure > >> >>> > which > >> >>> > numbers are critical but here are the producer metrics > >> >>> > <https://www.dropbox.com/s/pzi9304gw5vmae2/Screenshot% > >> >>> > 202016-08-23%2010.57.33.png?dl=0> > >> >>> > from > >> >>> > one container. > >> >>> > - avg windowing duration peaks at one point during the day (due > >> to > >> >>> the > >> >>> > number of open sessions) but everything is still sub-seconds > >> >>> > <https://www.dropbox.com/s/y2ps6pbs1tf257e/Screenshot% > >> >>> > 202016-08-23%2010.44.19.png?dl=0> > >> >>> > . > >> >>> > - our Kafka cluster doesn't seem to be overloaded > >> >>> > <https://www.dropbox.com/s/q01b4p4rg43spua/Screenshot% > >> >>> > 202016-08-23%2010.48.25.png?dl=0> > >> >>> > with writes < 60MB/s across all three brokers > >> >>> > > >> >>> > From all we know, we suspected that the bottleneck happens at > >> >>> producing to > >> >>> > Kafka. But we need some help confirming that. > >> >>> > > >> >>> > Any suggestion is appreciated. > >> >>> > > >> >>> > David > >> >>> > > >> >>> > >> >> > >> > > > > >
