Good discussion about where we should do batching. I think if there is a clear great way to batch, then it makes a lot of sense to just do it once. However, if we think there is scope for experimenting with different approaches, then an API that tools can use makes a lot of sense. They can experiment and innovate. Eventually, we can integrate something into Kafka if it makes sense.
Ismael On Sun, Apr 7, 2019, 11:03 PM Colin McCabe <cmcc...@apache.org> wrote: > Hi George, > > As Jason was saying, it seems like there are two directions we could go > here: an external system handling batching, and the controller handling > batching. I think the controller handling batching would be better, since > the controller has more information about the state of the system. If the > controller handles batching, then the controller could also handle things > like setting up replication quotas for individual partitions. The > controller could do things like throttle replication down if the cluster > was having problems. > > We kind of need to figure out which way we're going to go on this one > before we set up big new APIs, I think. If we want an external system to > handle batching, then we can keep the idea that there is only one > reassignment in progress at once. If we want the controller to handle > batching, we will need to get away from that idea. Instead, we should just > have a bunch of "ideal assignments" that we tell the controller about, and > let it decide how to do the batching. These ideal assignments could change > continuously over time, so from the admin's point of view, there would be > no start/stop/cancel, but just individual partition reassignments that we > submit, perhaps over a long period of time. And then cancellation might > just mean cancelling just that individual partition reassignment, not all > partition reassignments. > > best, > Colin > > On Fri, Apr 5, 2019, at 19:34, George Li wrote: > > Hi Jason / Viktor, > > > > For the URP during a reassignment, if the "original_replicas" is kept > > for the current pending reassignment. I think it will be very easy to > > compare that with the topic/partition's ISR. If all > > "original_replicas" are in ISR, then URP should be 0 for that > > topic/partition. > > > > It would be also nice to separate the metrics MaxLag/TotalLag for > > Reassignments. I think that will also require "original_replicas" (the > > topic/partition's replicas just before reassignment when the AR > > (Assigned Replicas) is set to Set(original_replicas) + > > Set(new_replicas_in_reassign_partitions) ). > > > > Thanks, > > George > > > > On Friday, April 5, 2019, 6:29:55 PM PDT, Jason Gustafson > > <ja...@confluent.io> wrote: > > > > Hi Viktor, > > > > Thanks for writing this up. As far as questions about overlap with > KIP-236, > > I agree it seems mostly orthogonal. I think KIP-236 may have had a larger > > initial scope, but now it focuses on cancellation and batching is left > for > > future work. > > > > With that said, I think we may not actually need a KIP for the current > > proposal since it doesn't change any APIs. To make it more generally > > useful, however, it would be nice to handle batching at the partition > level > > as well as Jun suggests. The basic question is at what level should the > > batching be determined. You could rely on external processes (e.g. cruise > > control) or it could be built into the controller. There are tradeoffs > > either way, but I think it simplifies such tools if it is handled > > internally. Then it would be much safer to submit a larger reassignment > > even just using the simple tools that come with Kafka. > > > > By the way, since you are looking into some of the reassignment logic, > > another problem that we might want to address is the misleading way we > > report URPs during a reassignment. I had a naive proposal for this > > previously, but it didn't really work > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-352%3A+Distinguish+URPs+caused+by+reassignment > . > > Potentially fixing that could fall under this work as well if you think > > it > > makes sense. > > > > Best, > > Jason > > > > On Thu, Apr 4, 2019 at 4:49 PM Jun Rao <j...@confluent.io> wrote: > > > > > Hi, Viktor, > > > > > > Thanks for the KIP. A couple of comments below. > > > > > > 1. Another potential thing to do reassignment incrementally is to move > a > > > batch of partitions at a time, instead of all partitions. This may > lead to > > > less data replication since by the time the first batch of partitions > have > > > been completely moved, some data of the next batch may have been > deleted > > > due to retention and doesn't need to be replicated. > > > > > > 2. "Update CR in Zookeeper with TR for the given partition". Which ZK > path > > > is this for? > > > > > > Jun > > > > > > On Sat, Feb 23, 2019 at 2:12 AM Viktor Somogyi-Vass < > > > viktorsomo...@gmail.com> > > > wrote: > > > > > > > Hi Harsha, > > > > > > > > As far as I understand KIP-236 it's about enabling reassignment > > > > cancellation and as a future plan providing a queue of replica > > > reassignment > > > > steps to allow manual reassignment chains. While I agree that the > > > > reassignment chain has a specific use case that allows fine grain > control > > > > over reassignment process, My proposal on the other hand doesn't talk > > > about > > > > cancellation but it only provides an automatic way to incrementalize > an > > > > arbitrary reassignment which I think fits the general use case where > > > users > > > > don't want that level of control but still would like a balanced way > of > > > > reassignments. Therefore I think it's still relevant as an > improvement of > > > > the current algorithm. > > > > Nevertheless I'm happy to add my ideas to KIP-236 as I think it > would be > > > a > > > > great improvement to Kafka. > > > > > > > > Cheers, > > > > Viktor > > > > > > > > On Fri, Feb 22, 2019 at 5:05 PM Harsha <ka...@harsha.io> wrote: > > > > > > > > > Hi Viktor, > > > > > There is already KIP-236 for the same feature and George > > > made > > > > > a PR for this as well. > > > > > Lets consolidate these two discussions. If you have any cases that > are > > > > not > > > > > being solved by KIP-236 can you please mention them in that > thread. We > > > > can > > > > > address as part of KIP-236. > > > > > > > > > > Thanks, > > > > > Harsha > > > > > > > > > > On Fri, Feb 22, 2019, at 5:44 AM, Viktor Somogyi-Vass wrote: > > > > > > Hi Folks, > > > > > > > > > > > > I've created a KIP about an improvement of the reassignment > algorithm > > > > we > > > > > > have. It aims to enable partition-wise incremental reassignment. > The > > > > > > motivation for this is to avoid excess load that the current > > > > replication > > > > > > algorithm implicitly carries as in that case there are points in > the > > > > > > algorithm where both the new and old replica set could be online > and > > > > > > replicating which puts double (or almost double) pressure on the > > > > brokers > > > > > > which could cause problems. > > > > > > Instead my proposal would slice this up into several steps where > each > > > > > step > > > > > > is calculated based on the final target replicas and the current > > > > replica > > > > > > assignment taking into account scenarios where brokers could be > > > offline > > > > > and > > > > > > when there are not enough replicas to fulfil the > min.insync.replica > > > > > > requirement. > > > > > > > > > > > > The link to the KIP: > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-435%3A+Incremental+Partition+Reassignment > > > > > > > > > > > > I'd be happy to receive any feedback. > > > > > > > > > > > > An important note is that this KIP and another one, KIP-236 that > is > > > > > > about > > > > > > interruptible reassignment ( > > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-236%3A+Interruptible+Partition+Reassignment > > > > > ) > > > > > > should be compatible. > > > > > > > > > > > > Thanks, > > > > > > Viktor > > > > > > > > > > > > > > > > > > > > >
