Cool :) Thanks for those insights :) ! I changed the subject of the thread, in order not to derail the original thread's subject...! I just want to recap to make sure I (and others) understand all of this correctly :)
So, if I understand correctly, with acks == [0,1] Kafka should provide a latency that is similar to what we have now, but with the possibility of losing a small window of unreplicated events in the case of an unrecoverable hardware failure, and with acks > 1 (or acks == -1) there will probably be a latency penalty but we will be completely protected from (non-correlated) hardware failures, right? Also, I guess the above assumptions are correct for a batch size of 1, and that bigger batch sizes could also lead to small windows of unwritten data in cases of failures, just like now...? Although, now that I think of it, I guess the vulnerability of bigger batch sizes would, again, only come into play in scenarios of unrecoverable correlated failures, since even if a machine fails with some partially committed batch, there would be other machines who received the same data (through replication) and would have enough time to commit those batches... Finally, I guess that replication (whatever the ack parameter is) will affect the overall throughput capacity of the Kafka cluster, since every node will now be writing its own data as well as the replicated data from +/- 2 other nodes, right? -- Felix On Wed, Apr 25, 2012 at 6:32 PM, Jay Kreps <jay.kr...@gmail.com> wrote: > Short answer is yes, both async (acks=0 or 1) and sync replication > (acks > 1) will be both be supported. > > -Jay > > On Wed, Apr 25, 2012 at 11:22 AM, Jun Rao <jun...@gmail.com> wrote: > > Felix, > > > > Initially, we thought we could keep the option of not sending acks from > the > > broker to the producer. However, this seems hard since in the new wire > > protocol, we need to send at least the error code to the producer (e.g., > a > > request is sent to the wrong broker or wrong partition). > > > > So, what we allow in the current design is the following. The producer > can > > specify the # of acks in the request. By default (acks = -1), the broker > > will wait for the message to be written to all replicas that are still > > synced up with the leader before acking the producer. Otherwise (acks > >=0), > > the broker will ack the producer after the message is written to acks > > replicas. Currently, acks=0 is treated the same as acks=1. > > > > Thanks, > > > > Jun > > > > On Wed, Apr 25, 2012 at 10:39 AM, Felix GV <fe...@mate1inc.com> wrote: > > > >> Just curious, but if I remember correctly from the time I read KAFKA-50 > and > >> the related JIRA issues, you guys plan to implement sync AND async > >> replication, right? > >> > >> -- > >> Felix > >> > >> > >> > >> On Tue, Apr 24, 2012 at 4:42 PM, Jay Kreps <jay.kr...@gmail.com> wrote: > >> > >> > Right now we do sloppy failover. That is when a broker goes down > >> > traffic is redirected to the remaining machines, but any unconsumed > >> > messages are stuck on that server until it comes back, if it is > >> > permanently gone the messages are lost. This is acceptable for us in > >> > the near-term since our pipeline is pretty real-time so this window > >> > between production and consumption is pretty small. The complete > >> > solution is the intra-cluster replication in KAFA-50 which is coming > >> > along fairly nicely now that we are working on it. > >> > > >> > -Jay > >> > > >> > On Tue, Apr 24, 2012 at 12:21 PM, Oliver Krohne > >> > <oliver.kro...@googlemail.com> wrote: > >> > > Hi, > >> > > > >> > > indeed I thought could be used as failover approach. > >> > > > >> > > We use raid for local redundancy but it does not protect us in case > of > >> a > >> > machine failure, so I am looking for a way to achieve a master/slave > >> setup > >> > until KAFKA-50 has been implemented. > >> > > > >> > > I think we can solve it for now by having multiple broker so that > the > >> > application can continue sending messages if one broker goes down. My > >> main > >> > concern is to not introduce a new single point of failure which can > stop > >> > the application. However as some consumer are not developed by us and > it > >> is > >> > not clear how they store the offset in zookeeper we need to find out > how > >> we > >> > can manage the consumer in case a broker will never return after a > >> failure. > >> > It will be acceptable to lose a couple of messages if a broker dies > and > >> the > >> > consumers have not consumed all messages at the point of failure. > >> > > > >> > > Thanks, > >> > > Oliver > >> > > > >> > > > >> > > > >> > > > >> > > Am 23.04.2012 um 19:58 schrieb Jay Kreps: > >> > > > >> > >> I think the confusion comes from the fact that we are using > mirroring > >> to > >> > >> handle geographic distribution not failover. If I understand > correctly > >> > what > >> > >> Oliver is asking for is something to give fault tolerance not > >> something > >> > for > >> > >> distribution. I don't think that is really what the mirroring does > out > >> > of > >> > >> the box, though technically i suppose you could just reset the > offsets > >> > and > >> > >> point the consumer at the new cluster and have it start from "now". > >> > >> > >> > >> I think it would be helpful to document our use case in the > mirroring > >> > docs > >> > >> since this is not the first time someone has asked about this. > >> > >> > >> > >> -Jay > >> > >> > >> > >> On Mon, Apr 23, 2012 at 10:38 AM, Joel Koshy <jjkosh...@gmail.com> > >> > wrote: > >> > >> > >> > >>> Hi Oliver, > >> > >>> > >> > >>> I was reading the mirroring guide and I wonder if it is required > that > >> > the > >> > >>>> mirror runs it's own zookeeper? > >> > >>>> > >> > >>>> We have a zookeeper cluster running which is used by different > >> > >>>> applications, so can we use that zookeeper cluster for the kafka > >> > source > >> > >>> and > >> > >>>> kafka mirror? > >> > >>>> > >> > >>> > >> > >>> You could have a single zookeeper cluster and use different > >> namespaces > >> > for > >> > >>> the source/target mirror. However, I don't think it is > recommended to > >> > use a > >> > >>> remote zookeeper (if you have a cross-DC set up) since that would > >> > >>> potentially mean very high ZK latencies on one of your clusters. > >> > >>> > >> > >>> > >> > >>>> What is the procedure if the kafka source server fails to switch > the > >> > >>>> applications to use the mirrored instance? > >> > >>>> > >> > >>> > >> > >>> I don't quite follow this question - can you clarify? The mirror > >> > cluster is > >> > >>> pretty much a separate instance. There is no built-in automatic > >> > fail-over > >> > >>> if your source cluster goes down. > >> > >>> > >> > >>> > >> > >>>> Are there any backup best practices if we would not use > mirroring? > >> > >>>> > >> > >>> > >> > >>> You can use RAID arrays for (local) data redundancy. You may also > be > >> > >>> interested in the (intra-DC) replication feature (KAFKA-50) that > is > >> > >>> currently being developed. I believe some folks on this list have > >> also > >> > used > >> > >>> plain rsync's as an alternative to mirroring. > >> > >>> > >> > >>> Thanks, > >> > >>> > >> > >>> Joel > >> > >>> > >> > > > >> > > >> >
