Jan, Thanks a lot for the feedback. Now I understood your concern better. The following are my comments.
The first odd thing that you pointed out could be a real concern. Basically, if a producer publishes messages with really old timestamp, our default log.roll.hours (7 days) will indeed cause the broker to roll a log on ever message, which would be bad. Time-based rolling is actually used infrequently. The only use case that I am aware of is that for compacted topics, rolling logs based on time could allow the compaction to happen sooner (since the active segment is never cleaned). One option is to change the default log.roll.hours to infinite and also document the impact on changing log.roll.hours. Jiangjie, what do you think? For the second odd thing, the OffsetRequest is a legacy request. It's awkward to use and we plan to deprecate it over time. That's why we haven't change the logic in serving OffsetRequest after KIP-33. The plan is to introduce a new OffsetRequest that will be exploiting the time based index. It's possible to have log segments with non-increasing largest timestamp. As you can see in Log.fetchOffsetsByTimestamp(), we simply iterate the segments in offset order and stop when we see the target timestamp. For the third odd thing, one of the original reasons why the time-based index points to an offset instead of the file position is that it makes truncating the time index to an offset easier since the offset is in the index. Looking at the code, we could also store the file position in the time index and do truncation based on position, instead of offset. It probably has a slight advantage of consistency between the two indexes and avoiding another level of indirection when looking up the time index. Jiangjie, have we ever considered that? The idea of log.message.timestamp.difference.max.ms is to prevent the timestamp in the published messages to drift too far away from the current timestamp. The default value is infinite though. Lastly, for the usefulness of time-based index, it's actually a feature that the community wanted and voted for, not just for Confluent customers. For example, being able to seek to an offset based on timestamp has been a frequently asked feature. This can be useful for at least the following scenarios: (1) If there is a bug in a consumer application, the user will want to rewind the consumption after fixing the logic. In this case, it's more convenient to rewind the consumption based on a timestamp. (2) In a multi data center setup, it's common for people to mirror the data from one Kafka cluster in one data center to another cluster in a different data center. If one data center fails, people want to be able to resume the consumption in the other data center. Since the offsets are not preserving between the two clusters through mirroring, being able to find a starting offset based on timestamp will allow the consumer to resume the consumption without missing any messages and also not replaying too many messages. Thanks, Jun On Wed, Aug 24, 2016 at 5:05 PM, Jan Filipiak <jan.filip...@trivago.com> wrote: > Hey Jun, > > I go and try again :), wrote the first one in quite a stressful > environment. The bottom line is that I, for our use cases, see a to small > use/effort ratio in this time index. > We do not bootstrap new consumers for key-less logs so frequently and when > we do it, they usually want everything (prod deployment) or just start at > the end ( during development). > That caused quite some frustration. Would be better if I could just have > turned it off and don't bother any more. Anyhow in the meantime I had to > dig deeper into the inner workings > and the impacts are not as dramatic as I initially assumed. But it still > carries along some oddities I want to list here. > > first odd thing: > Quote > --- > Enforce time based log rolling > > Currently time based log rolling is based on the creating time of the log > segment. With this KIP, the time based rolling would be changed to based on > the largest timestamp ever seen in a log segment. A new log segment will be > rolled out if current time is greater than largest timestamp ever seen in > the log segment + log.roll.ms. When message.timestamp.type=CreateTime, > user should set max.message.time.difference.ms appropriately together > with log.roll.ms to avoid frequent log segment roll out. > --- > imagine a Mirrormaker falls behind and the Mirrormaker has a delay of some > time > log.roll.ms. > From my understanding, when noone else is producing to this partition > except the mirror maker, the broker will start rolling on every append? > Just because you maybe under DOS-attack and your application only works in > the remote location. (also a good occasion for MM to fall behind) > But checking the default values indicates that it should indeed not become > a problem as log.roll.ms defaults to ~>7 days. > > > second odd thing: > Quote > --- > A time index entry (*T*, *offset*) means that in this segment any message > whose timestamp is greater than *T* come after *offset.* > > The OffsetRequest behaves almost the same as before. If timestamp *T* is > set in the OffsetRequest, the first offset in the returned offset sequence > means that if user want to consume from *T*, that is the offset to start > with. The guarantee is that any message whose timestamp is greater than T > has a bigger offset. i.e. Any message before this offset has a timestamp < > *T*. > --- > > Given how the index is maintained, with a little bit of bad luck (rolling > upgrade/config change of mirrormakers for different colocations) one ends > with segmentN.timeindex.maxtimestamp > segmentN+1.timeindex.maxtimestamp. > If I do not overlook something here, then the fetch code does not seem to > take that into account. > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/Log.scala#L604 > In this case the Goal listed number 1, not loose any messages, is not > achieved. easy fix seems to be to sort the segsArray by maxtimestamp but > can't wrap my head around it just now. > > > third odd thing: > Regarding the worry of increasing complexity. Looking at the code > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/LogSegment.scala#L193 -196 > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/LogSegment.scala#L227 & 230 > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/LogSegment.scala#L265 -266 > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/LogSegment.scala#L305 -307 > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/LogSegment.scala#L408 - 410 > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/LogSegment.scala#L432 - 435 > https://github.com/apache/kafka/blob/05d00b5aca2e1e59ad685a3f051d2a > b022f75acc/core/src/main/scala/kafka/log/LogSegment.scala#L104 -108 > and especially > https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a2988c40388 > 2ae8a9852e/core/src/main/scala/kafka/log/Log.scala#L717 > it feels like the Log & Log segment having a detailed knowledge about the > maintained indexes is not the ideal way to model the problem. > Having the Server maintian a Set of Indexes could reduce the code > complexity, while also allowing an easy switch to turn it off. I think both > indexes could point to the physical position, a client would do > fetch(timestamp), and the continue with the offsets as usual. Is there any > specific reason the timestamp index points into the offset index? > For reading one would need to branch earlier, maybe already in ApiHandler > and decide what indexes to query, but this branching logic is there now > anyhow. > > Further I also can't think of a situation where one wants to have this > log.message.timestamp.difference.max.ms take effect. I think this defeats > goal 1 again. > > ITE having this index in the brokers now feels wired to me. Gives me a > feeling of complexity that I don't need and have a hard time figuring out > how much other people can benefit from it. I hope that this feedback is > useful and helps to understand my scepticism regarding this thing. There > were some other oddities that I have a hard time recalling now. So i guess > the index was build for a specific confluent customer, will there be any > blogpost about their usecase? or can you share it? > > Best Jan > > > On 24.08.2016 16:47, Jun Rao wrote: > > Jan, > > Thanks for the reply. I actually wasn't sure what your main concern on > time-based rolling is. Just a couple of clarifications. (1) Time-based > rolling doesn't control how long a segment will be retained for. For > retention, if you use time-based, it will now be based on the timestamp in > the message. If you use size-based, it works the same as before. Is your > concern on time-based retention? If so, you can always configure the > timestamp in all topics to be log append time, which will give you the same > behavior as before. (2) The creation time of the segment is never exposed > to the consumer and therefore is never preserved in MirrorMaker. In > contrast, the timestamp in the message will be preserved in MirrorMaker. > So, not sure what your concern on MirrorMaker is. > > Jun > > On Wed, Aug 24, 2016 at 5:03 AM, Jan Filipiak <jan.filip...@trivago.com> > wrote: > >> Hi Jun, >> >> I copy pasted this mail from the archive, as I somehow didn't receive it >> per mail. I will sill make some comments in line, >> hopefully you can find them quick enough, my apologies. >> >> To make things more clear, you should also know, that all messages in our >> kafka setup have a common way to access their timestamp already (its >> encoded in the value the same way always) >> Sometimes this is a logical time (eg same timestamp accross many >> different topics / partitions), say PHP request start time or the like. So >> kafkas internal timestamps are not really attractive >> for us anyways currently. >> >> I hope I can make a point and not waste your time. >> >> Best Jan, >> >> hopefully everything makes sense >> >> -------- >> >> Jan, >> >> Currently, there is no switch to disable the time based index. >> >> There are quite a few use cases of time based index. >> >> 1. From KIP-33's wiki, it allows us to do time-based retention accurately. >> Before KIP-33, the time-based retention is based on the last modified time >> of each log segment. The main issue is that last modified time can change >> over time. For example, if a broker loses storage and has to re-replicate >> all data, those re-replicated segments will be retained much longer since >> their last modified time is more recent. Having a time-based index allows >> us to retain segments based on the message time, not the last modified >> time. This can also benefit KIP-71, where we want to combine time-based >> retention and compaction. >> >> /If your sparse on discspace, one could try to get by that with >> retention.bytes/ >> or, as we did, ssh into the box and rm it, which worked quite good when >> no one reads it. >> Chuckles a little when its read but readers usually do an >> auto.offset.reset >> (they are to slow any ways if they reading the last segments hrhr). >> >> 2. In KIP-58, we want to delay log compaction based on a configurable >> amount of time. Time-based index allows us to do this more accurately. >> >> /good point, seems reasonable/ >> >> 3. We plan to add an api in the consumer to allow seeking to an offset >> based on a timestamp. The time based index allows us to do this more >> accurately and fast. >> >> /Sure, I personally feel that you rarely want to do this. For Camus, we >> used max.pull.historic.days (or simmilliar) successfully quite often. we >> just gave it an extra day and got what we wanted >> and for debugging my bisect tool works well enough. So these are the 2 >> usecases we expierenced already and found a decent way around it./ >> >> Now for the impact. >> >> a. There is a slight change on how time-based rolling works. Before >> KIP-33, >> rolling was based on the time when a segment was loaded in the broker. >> After KIP-33, rolling is based on the time of the first message of a >> segment. Not sure if this is your concern. In the common case, the two >> behave more or less the same. The latter is actually more deterministic >> since it's not sensitive to broker restarts. >> >> /This is part of my main concern indeed. This is what scares me and I >> preffered to just opt out, instead of reviewing all our pipelines to check >> whats gonna happen when we put it live. >> For Example the Mirrormakers, If they want to preserve create time from >> the source cluster and publish the same create time (wich they should do, >> if you don't encode your own timestamps and want >> to have proper kafka-streams windowing). Then I am quite concerned when >> have problems if our cross ocian links and fall behind, say a day or two. >> Then I can think of an very up to date MirrorMaker from >> one colocation and a very laggy Mirrormaker from another colocation. For >> me its not 100% clear whats gonna happen. But I can't think of sane >> defaults there. That i love kafka for. >> Just tricky to be convinced that an upgrade is safe, wich was usually >> easy. >> / >> b. Time-based index potentially adds overhead to producing messages and >> loading segments. Our experiments show that the impact to producing is >> insignificant. The time to load segments when restarting a broker can be >> doubled. However, the absolute time is still reasonable. For example, >> loading 10K log segments with time-based index takes about 5 seconds. >> / >> //Loading should be fine/, totally agree >> >> c Because time-based index is useful in several cases and the impact seems >> small, we didn't consider making time based index optional. Finally, >> although it's possible to make the time based index optional, it will add >> more complexity to the code base. So, we probably should only consider it >> if it's truly needed. Thanks, >> >> /I think one can get away with an easier codebase here. The trick is not >> to have the LOG to implement all the logic, >> but just have the broker maintain a Set of Indexes, that gets initialized >> in starup and passed to the LOG. One could ask each individual >> index, if that logsegment should be rolled, compacted, truncated >> whatever. Once could also give that LogSegment to each index and make it >> rebuild >> the index for example. I didn't figure out the details. But this >> https://github.com/apache/kafka/blob/79d3fd2bf0e5c89ff74a298 >> 8c403882ae8a9852e/core/src/main/scala/kafka/log/Log.scala#L715 >> might end up with for(Index i : indexes) [i.shouldRoll(segment)}? wich >> should already be easier. >> If users don't want time based indexing, just don't put the timebased >> index in the Set then and everything should work like a charm. >> RPC calls that work on the specific indexes would need to throw an >> exception of some kind. >> Just an idea. >> / >> Jun >> >> >> >> >> >> On 22.08.2016 09:24, Jan Filipiak wrote: >> >>> Hello everyone, >>> >>> I stumbled across KIP-33 and the time based index, while briefly >>> checking the wiki and commits, I fail to find a way to opt out. >>> I saw it having quite some impact on when logs are rolled and was hoping >>> not to have to deal with all of that. Is there a disable switch I >>> overlooked? >>> >>> Does anybody have a good use case where the timebase index comes in >>> handy? I made a custom console consumer for me, >>> that can bisect a log based on time. Its just a quick probabilistic shot >>> into the log but is sometimes quite useful for some debugging. >>> >>> Best Jan >>> >> >> > >
