For the 3rd point, yes, what I'm proposing is an edge case. For example, when we have 4 tasks [0_0, 0_1, 1_0, 1_1], and a bug in rebalancing logic causing no one gets 1_1 assigned. Then the health check service will only see 3 tasks [0_0, 0_1, 1_0] reporting progress normally while not paying attention to 1_1. What I want to expose is a "logical global" view of all the tasks through the stream instance, since each instance gets the assigned topology and should be able to infer all the exact tasks to be up and running when the service is healthy.
On Thu, Feb 25, 2021 at 11:25 AM Walker Carlson <wcarl...@confluent.io> wrote: > Thanks for the follow up Boyang and Guozhang, > > I have updated the kip to include these ideas. > > Guozhang, that is a good idea about using the TaskMetadata. We can get it > through the ThreadMetadata with a minor change to `localThreadMetadata` in > kafkaStreams. This means that we will only need to update TaskMetadata and > add no other APIs > > Boyang, since each TaskMetadata contains the TaskId and TopicPartitions I > don't believe mapping either way will be a problem. Also I think we can do > something like record the time the task started idling and when it stops > idling we can override it to -1. I think that should clear up the first two > points. > > As for your third point I am not sure I 100% understand. The ThreadMetadata > will contain a set of all task assigned to that thread. Any health check > service will just need to query all clients and aggregate their responses > to get a complete picture of all tasks correct? > > walker > > On Thu, Feb 25, 2021 at 9:57 AM Guozhang Wang <wangg...@gmail.com> wrote: > > > Regarding the second API and the `TaskStatus` class: I'd suggest we > > consolidate on the existing `TaskMetadata` since we have already > > accumulated a bunch of such classes, and its better to keep them small as > > public APIs. You can see > https://issues.apache.org/jira/browse/KAFKA-12370 > > for a reference and a proposal. > > > > On Thu, Feb 25, 2021 at 9:40 AM Boyang Chen <reluctanthero...@gmail.com> > > wrote: > > > > > Thanks for the updates Walker. Some replies and follow-up questions: > > > > > > 1. I agree one task could have multiple partitions, but when we hit a > > delay > > > in terms of offset progress, do we have a convenient way to reverse > > mapping > > > TopicPartition to the problematic task? In production, I believe it > would > > > be much quicker to identify the problem using task.id instead of topic > > > partition, especially when it points to an internal topic. I think > having > > > the task id as part of the entry value seems useful, which means > getting > > > something like Map<TopicPartition, TaskProgress> where TaskProgress > > > contains both committed offsets & task id. > > > > > > 2. The task idling API was still confusing. I don't think we care about > > the > > > exact state when making tasksIdling()query, instead we care more about > > how > > > long one task has been in idle state since when you called, which > > reflects > > > whether it is a normal idling period. So I feel it might be helpful to > > > track that time difference and report it in the TaskStatus struct. > > > > > > 3. What I want to achieve to have some global mapping of either > > > TopicPartition or TaskId was that it is not possible for a health check > > > service to report a task failure that doesn't emit any metrics. So as > > long > > > as we have a global topic partition API, health check could always be > > aware > > > of any task/partition not reporting its progress, does that make sense? > > If > > > you feel we have a better way to achieve this, such as querying all the > > > input/intermediate topic metadata directly from Kafka for the > baseline, I > > > think that should be good as well and worth mentioning it in the KIP. > > > > > > Also it seems that the KIP hasn't reflected what you proposed for the > > task > > > idling status. > > > > > > Best, > > > Boyang > > > > > > > > > On Wed, Feb 24, 2021 at 9:11 AM Walker Carlson <wcarl...@confluent.io> > > > wrote: > > > > > > > Thank you for the comments everyone! > > > > > > > > I think there are a few things I can clear up in general then I will > > > > specifically respond to each question. > > > > > > > > First, when I say "idling" I refer to task idling. Where the stream > is > > > > intentionally not making progress. ( > > > > https://issues.apache.org/jira/browse/KAFKA-10091 is an example). > This > > > > becomes relevant if a task is waiting on one partition with no data > but > > > > that is holding up a partition with data. That would cause one just > > > looking > > > > at the committed offset changes to believe the task has a problem > when > > it > > > > is working as intended. > > > > > > > > In light of this confusion. I plan to change tasksIdling() to > > > `Map<TaskId, > > > > TaskStatus> getTasksStatus()` this should hopefully make it more > clear > > > what > > > > is being exposed. > > > > > > > > TaskStatus would include: TopicPartions, TaskId, ProcessorTopology, > > > Idling, > > > > and State. > > > > > > > > Boyang: > > > > > > > > 2) I think that each task should report on whatever TopicPartitions > > they > > > > hold, this means a Topic Partition might get reported twice but the > > user > > > > can roll those up and use the larger one when looking at the whole > app. > > > > > > > > 4) If the user collects the committed offsets across all the running > > > > clients there shouldn't be any tasks missing correct? > > > > > > > > 6) Because there is not a 1:1 mapping between Tasks and > > TopicPartitions I > > > > think it is cleaner to report them separately. > > > > > > > > Guozhang: > > > > > > > > 1) Yes, that was my original plan but it made more sense to mirror > how > > > the > > > > consumer exposes the committed offset. > > > > > > > > 3) That is a good point. I think that we should include internal > topics > > > as > > > > well. I think that if the topology were to evolve there should be > fair > > > > warning anyways. Maybe you can clarify what would be limited by > > exposing > > > > the interior topics here? I thought a user could find them in other > > ways. > > > > If it is the name we could aynomise them before exposing them. > > > > > > > > Thank you all for your comments. If I did not respond directly to one > > of > > > > your questions I updated the kip to include the details it was > > > requesting. > > > > I didn't not include my proposed changes mentioned earlier as I would > > > like > > > > to get some feedback about what to include in TaskStatus and in > > general. > > > > > > > > best, > > > > Walker > > > > > > > > On Mon, Feb 22, 2021 at 10:20 PM Guozhang Wang <wangg...@gmail.com> > > > wrote: > > > > > > > > > Hello Walker, thanks for the KIP. A few thoughts: > > > > > > > > > > 1) Have you considered just relying on the `KafkaStreams#metrics()` > > > that > > > > > includes embedded consumer metrics that have the committed offsets > > > > > instead of adding a new API? Not advocating that this is a better > > > > approach > > > > > but want to make sure we considered all options before we come to > the > > > > "last > > > > > resort" of adding new public interfaces. > > > > > > > > > > 2) The javadoc mentions "tasks assigned to this client", but the > > > returned > > > > > map is on partitions. I think we should make the javadoc and the > > return > > > > > types consistent, either tasks or topic partitions. > > > > > > > > > > 3) In addition, if for 2) above we ended up with topic partitions, > > then > > > > > would they include only external source topics, or also including > > > > internal > > > > > repartition / changelog topics? I think including only external > > source > > > > > topic partitions are not sufficient for your goal of tracking > > progress, > > > > but > > > > > exposing internal topic names are also a big commitment here for > > future > > > > > topology evolution. > > > > > > > > > > 4) For "tasksIdling", I'm wondering if we can make it more > general, > > > that > > > > > the returned value is not just a boolean, but a TaskState that can > be > > > an > > > > > enum of "created, restoring, running, idle, closing". This could > help > > > us > > > > in > > > > > the future to track other things like restoration efficiency and > > > > rebalance > > > > > efficiency etc. > > > > > > > > > > 5) We need to clarify how is "idling" being defined here: e.g. we > can > > > > > clearly state that a task is considered idle only if 1) lag is > > > > > increasing, indicating that there are indeed new records arrived at > > > > source, > > > > > while committed offset is not advancing, AND 2) produced offset > > > (imagine > > > > we > > > > > may have punctuations that generate new data to the output topic > even > > > if > > > > > there's no input for a while) is not advancing either. > > > > > > > > > > > > > > > Guozhang > > > > > > > > > > > > > > > > > > > > On Mon, Feb 22, 2021 at 3:11 PM Boyang Chen < > > > reluctanthero...@gmail.com> > > > > > wrote: > > > > > > > > > > > Thanks Walker for the proposed KIP! This should definitely > empower > > > > > KStream > > > > > > users with better visibility. > > > > > > > > > > > > Meanwhile I got a couple of questions/suggestions: > > > > > > > > > > > > > > > > > > 1. typo "repost/report" in the motivation section. > > > > > > > > > > > > 2. What offsets do we report when the task is under restoration > or > > > > > > rebalancing? > > > > > > > > > > > > 3. IIUC, we should clearly state that our reported metrics are > > based > > > > off > > > > > > locally assigned tasks for each instance. > > > > > > > > > > > > 4. In the meantime, what’s our strategy to report tasks that are > > not > > > > > local > > > > > > to the instance? Users would normally try to monitor all the > > possible > > > > > > tasks, and it’s unfortunate we couldn’t determine whether we have > > > lost > > > > > > tasks. My brainstorming was whether it makes sense for the leader > > > > > instance > > > > > > to report the task progress as -1 for all “supposed to be > running” > > > > tasks, > > > > > > so that on the metrics collector side it could catch any missing > > > tasks. > > > > > > > > > > > > 5. It seems not clear how users should use `isTaskIdling`. Why > not > > > > > report a > > > > > > map/set for idling tasks just as what we did for committed > offsets? > > > > > > > > > > > > 6. Why do we use TopicPartition instead of TaskId as the key in > the > > > > > > returned map? > > > > > > 7. Could we include some details in where we got the commit > offsets > > > for > > > > > > each task? Is it through consumer offset fetch, or the stream > > > > processing > > > > > > progress based on the records fetched? > > > > > > > > > > > > > > > > > > On Mon, Feb 22, 2021 at 3:00 PM Walker Carlson < > > > wcarl...@confluent.io> > > > > > > wrote: > > > > > > > > > > > > > Hello all, > > > > > > > > > > > > > > I would like to start discussion on KIP-715. This kip aims to > > make > > > it > > > > > > > easier to monitor Kafka Streams progress by exposing the > > committed > > > > > offset > > > > > > > in a similar way as the consumer client does. > > > > > > > > > > > > > > Here is the KIP: https://cwiki.apache.org/confluence/x/aRRRCg > > > > > > > > > > > > > > Best, > > > > > > > Walker > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > -- Guozhang > > > > > > > > > > > > > > > > > > -- > > -- Guozhang > > >
