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From XIAOHE DONG <dannyriv...@gmail.com>
Subject Re: [DISCUSS] KIP-354 Time-based log compaction policy
Date Thu, 16 Aug 2018 06:42:10 GMT
Hi Xiongqi

Thanks for thinking about implementing this as well. :)

I was thinking about using `segment.ms` to trigger the segment roll. Also, its value can be
the largest time bias for the record deletion. For example, if the `segment.ms` is 1 day and
`max.compaction.ms` is 30 days, the compaction may happen around 31 days. 

For my curiosity, is there a way we can do some performance test for this and any tools you
can recommend. As you know, previously, it is cleaned up by respecting dirty ratio, but now
it may happen anytime if max lag has passed for each message. I wonder what would happen if
clients send huge amount of tombstone records at the same time. 

I am looking forward to have a quick chat with you to avoid double effort on this. I am in
confluent community slack during the work time. My name is Xiaohe Dong. :)

Rgds
Xiaohe Dong



On 2018/08/16 01:22:22, xiongqi wu <xiongqiwu@gmail.com> wrote: 
> Brett,
> 
> Thank you for your comments.
> I was thinking since we already has immediate compaction setting by setting
> min dirty ratio to 0, so I decide to use "0" as disabled state.
> I am ok to go with -1(disable), 0 (immediate) options.
> 
> For the implementation, there are a few differences between mine and
> "Xiaohe Dong"'s :
> 1) I used the estimated creation time of a log segment instead of largest
> timestamp of a log to determine the compaction eligibility, because a log
> segment might stay as an active segment up to "max compaction lag". (see
> the KIP for detail).
> 2) I measure how much bytes that we must clean to follow the "max
> compaction lag" rule, and use that to determine the order of compaction.
> 3) force active segment to roll to follow the "max compaction lag"
> 
> I can share my code so we can coordinate.
> 
> I haven't think about a new API to force a compaction. what is the use case
> for this one?
> 
> 
> On Wed, Aug 15, 2018 at 5:33 PM, Brett Rann <brann@zendesk.com.invalid>
> wrote:
> 
> > We've been looking into this too.
> >
> > Mailing list:
> > https://lists.apache.org/thread.html/ed7f6a6589f94e8c2a705553f364ef
> > 599cb6915e4c3ba9b561e610e4@%3Cdev.kafka.apache.org%3E
> > jira wish: https://issues.apache.org/jira/browse/KAFKA-7137
> > confluent slack discussion:
> > https://confluentcommunity.slack.com/archives/C49R61XMM/p1530760121000039
> >
> > A person on my team has started on code so you might want to coordinate:
> > https://github.com/dongxiaohe/kafka/tree/dongxiaohe/log-
> > cleaner-compaction-max-lifetime-2.0
> >
> >  He's been working with Jason Gustafson and James Chen around the changes.
> > You can ping him on confluent slack as Xiaohe Dong.
> >
> > It's great to know others are thinking on it as well.
> >
> > You've added the requirement to force a segment roll which we hadn't gotten
> > to yet, which is great. I was content with it not including the active
> > segment.
> >
> > > Adding topic level configuration "max.compaction.lag.ms",  and
> > corresponding broker configuration "log.cleaner.max.compaction.lag.ms",
> > which is set to 0 (disabled) by default.
> >
> > Glancing at some other settings convention seems to me to be -1 for
> > disabled (or infinite, which is more meaningful here).  0 to me implies
> > instant, a little quicker than 1.
> >
> > We've been trying to think about a way to trigger compaction as well
> > through an API call, which would need to be flagged somewhere (ZK admin/
> > space?) but we're struggling to think how that would be coordinated across
> > brokers and partitions.  Have you given any thought to that?
> >
> >
> >
> >
> >
> >
> > On Thu, Aug 16, 2018 at 8:44 AM xiongqi wu <xiongqiwu@gmail.com> wrote:
> >
> > > Eno, Dong,
> > >
> > > I have updated the KIP. We decide not to address the issue that we might
> > > have for both compaction and time retention enabled topics (see the
> > > rejected alternative item 2). This KIP will only ensure log can be
> > > compacted after a specified time-interval.
> > >
> > > As suggested by Dong, we will also enforce "max.compaction.lag.ms" is
> > not
> > > less than "min.compaction.lag.ms".
> > >
> > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-354: Time-based
> > log
> > > compaction policy
> > > <https://cwiki.apache.org/confluence/display/KAFKA/KIP-354: Time-based
> > log compaction policy>
> > >
> > >
> > > On Tue, Aug 14, 2018 at 5:01 PM, xiongqi wu <xiongqiwu@gmail.com> wrote:
> > >
> > > >
> > > > Per discussion with Dong, he made a very good point that if compaction
> > > > and time based retention are both enabled on a topic, the compaction
> > > might
> > > > prevent records from being deleted on time. The reason is when
> > compacting
> > > > multiple segments into one single segment, the newly created segment
> > will
> > > > have same lastmodified timestamp as latest original segment. We lose
> > the
> > > > timestamp of all original segments except the last one. As a result,
> > > > records might not be deleted as it should be through time based
> > > retention.
> > > >
> > > > With the current KIP proposal, if we want to ensure timely deletion, we
> > > > have the following configurations:
> > > > 1) enable time based log compaction only : deletion is done though
> > > > overriding the same key
> > > > 2) enable time based log retention only: deletion is done though
> > > > time-based retention
> > > > 3) enable both log compaction and time based retention: Deletion is not
> > > > guaranteed.
> > > >
> > > > Not sure if we have use case 3 and also want deletion to happen on
> > time.
> > > > There are several options to address deletion issue when enable both
> > > > compaction and retention:
> > > > A) During log compaction, looking into record timestamp to delete
> > expired
> > > > records. This can be done in compaction logic itself or use
> > > > AdminClient.deleteRecords() . But this assumes we have record
> > timestamp.
> > > > B) retain the lastModifed time of original segments during log
> > > compaction.
> > > > This requires extra meta data to record the information or not grouping
> > > > multiple segments into one during compaction.
> > > >
> > > > If we have use case 3 in general, I would prefer solution A and rely on
> > > > record timestamp.
> > > >
> > > >
> > > > Two questions:
> > > > Do we have use case 3? Is it nice to have or must have?
> > > > If we have use case 3 and want to go with solution A, should we
> > introduce
> > > > a new configuration to enforce deletion by timestamp?
> > > >
> > > >
> > > > On Tue, Aug 14, 2018 at 1:52 PM, xiongqi wu <xiongqiwu@gmail.com>
> > wrote:
> > > >
> > > >> Dong,
> > > >>
> > > >> Thanks for the comment.
> > > >>
> > > >> There are two retention policy: log compaction and time based
> > retention.
> > > >>
> > > >> Log compaction:
> > > >>
> > > >> we have use cases to keep infinite retention of a topic (only
> > > >> compaction). GDPR cares about deletion of PII (personal identifiable
> > > >> information) data.
> > > >> Since Kafka doesn't know what records contain PII, it relies on upper
> > > >> layer to delete those records.
> > > >> For those infinite retention uses uses, kafka needs to provide a way
> > to
> > > >> enforce compaction on time. This is what we try to address in this
> > KIP.
> > > >>
> > > >> Time based retention,
> > > >>
> > > >> There are also use cases that users of Kafka might want to expire
all
> > > >> their data.
> > > >> In those cases, they can use time based retention of their topics.
> > > >>
> > > >>
> > > >> Regarding your first question, if a user wants to delete a key in
the
> > > >> log compaction topic, the user has to send a deletion using the same
> > > key.
> > > >> Kafka only makes sure the deletion will happen under a certain time
> > > >> periods (like 2 days/7 days).
> > > >>
> > > >> Regarding your second question. In most cases, we might want to delete
> > > >> all duplicated keys at the same time.
> > > >> Compaction might be more efficient since we need to scan the log and
> > > find
> > > >> all duplicates. However, the expected use case is to set the time
> > based
> > > >> compaction interval on the order of days, and be larger than 'min
> > > >> compaction lag". We don't want log compaction to happen frequently
> > since
> > > >> it is expensive. The purpose is to help low production rate topic
to
> > get
> > > >> compacted on time. For the topic with "normal" incoming message
> > message
> > > >> rate, the "min dirty ratio" might have triggered the compaction before
> > > this
> > > >> time based compaction policy takes effect.
> > > >>
> > > >>
> > > >> Eno,
> > > >>
> > > >> For your question, like I mentioned we have long time retention use
> > case
> > > >> for log compacted topic, but we want to provide ability to delete
> > > certain
> > > >> PII records on time.
> > > >> Kafka itself doesn't know whether a record contains sensitive
> > > information
> > > >> and relies on the user for deletion.
> > > >>
> > > >>
> > > >> On Mon, Aug 13, 2018 at 6:58 PM, Dong Lin <lindong28@gmail.com>
> > wrote:
> > > >>
> > > >>> Hey Xiongqi,
> > > >>>
> > > >>> Thanks for the KIP. I have two questions regarding the use-case
for
> > > >>> meeting
> > > >>> GDPR requirement.
> > > >>>
> > > >>> 1) If I recall correctly, one of the GDPR requirement is that
we can
> > > not
> > > >>> keep messages longer than e.g. 30 days in storage (e.g. Kafka).
Say
> > > there
> > > >>> exists a partition p0 which contains message1 with key1 and message2
> > > with
> > > >>> key2. And then user keeps producing messages with key=key2 to
this
> > > >>> partition. Since message1 with key1 is never overridden, sooner
or
> > > later
> > > >>> we
> > > >>> will want to delete message1 and keep the latest message with
> > key=key2.
> > > >>> But
> > > >>> currently it looks like log compact logic in Kafka will always
put
> > > these
> > > >>> messages in the same segment. Will this be an issue?
> > > >>>
> > > >>> 2) The current KIP intends to provide the capability to delete
a
> > given
> > > >>> message in log compacted topic. Does such use-case also require
Kafka
> > > to
> > > >>> keep the messages produced before the given message? If yes, then
we
> > > can
> > > >>> probably just use AdminClient.deleteRecords() or time-based log
> > > retention
> > > >>> to meet the use-case requirement. If no, do you know what is the
> > GDPR's
> > > >>> requirement on time-to-deletion after user explicitly requests
the
> > > >>> deletion
> > > >>> (e.g. 1 hour, 1 day, 7 day)?
> > > >>>
> > > >>> Thanks,
> > > >>> Dong
> > > >>>
> > > >>>
> > > >>> On Mon, Aug 13, 2018 at 3:44 PM, xiongqi wu <xiongqiwu@gmail.com>
> > > wrote:
> > > >>>
> > > >>> > Hi Eno,
> > > >>> >
> > > >>> > The GDPR request we are getting here at linkedin is if we
get a
> > > >>> request to
> > > >>> > delete a record through a null key on a log compacted topic,
> > > >>> > we want to delete the record via compaction in a given time
period
> > > >>> like 2
> > > >>> > days (whatever is required by the policy).
> > > >>> >
> > > >>> > There might be other issues (such as orphan log segments
under
> > > certain
> > > >>> > conditions) that lead to GDPR problem but they are more like
> > > >>> something we
> > > >>> > need to fix anyway regardless of GDPR.
> > > >>> >
> > > >>> >
> > > >>> > -- Xiongqi (Wesley) Wu
> > > >>> >
> > > >>> > On Mon, Aug 13, 2018 at 2:56 PM, Eno Thereska <
> > > eno.thereska@gmail.com>
> > > >>> > wrote:
> > > >>> >
> > > >>> > > Hello,
> > > >>> > >
> > > >>> > > Thanks for the KIP. I'd like to see a more precise definition
of
> > > what
> > > >>> > part
> > > >>> > > of GDPR you are targeting as well as some sort of verification
> > that
> > > >>> this
> > > >>> > > KIP actually addresses the problem. Right now I find
this a bit
> > > >>> vague:
> > > >>> > >
> > > >>> > > "Ability to delete a log message through compaction
in a timely
> > > >>> manner
> > > >>> > has
> > > >>> > > become an important requirement in some use cases (e.g.,
GDPR)"
> > > >>> > >
> > > >>> > >
> > > >>> > > Is there any guarantee that after this KIP the GDPR
problem is
> > > >>> solved or
> > > >>> > do
> > > >>> > > we need to do something else as well, e.g., more KIPs?
> > > >>> > >
> > > >>> > >
> > > >>> > > Thanks
> > > >>> > >
> > > >>> > > Eno
> > > >>> > >
> > > >>> > >
> > > >>> > >
> > > >>> > > On Thu, Aug 9, 2018 at 4:18 PM, xiongqi wu <xiongqiwu@gmail.com>
> > > >>> wrote:
> > > >>> > >
> > > >>> > > > Hi Kafka,
> > > >>> > > >
> > > >>> > > > This KIP tries to address GDPR concern to fulfill
deletion
> > > request
> > > >>> on
> > > >>> > > time
> > > >>> > > > through time-based log compaction on a compaction
enabled
> > topic:
> > > >>> > > >
> > > >>> > > > https://cwiki.apache.org/confluence/display/KAFKA/KIP-
> > > <https://cwiki.apache.org/confluence/display/KAFKA/KIP->
> > > >>> > > > 354%3A+Time-based+log+compaction+policy
> > > >>> > > >
> > > >>> > > > Any feedback will be appreciated.
> > > >>> > > >
> > > >>> > > >
> > > >>> > > > Xiongqi (Wesley) Wu
> > > >>> > > >
> > > >>> > >
> > > >>> >
> > > >>>
> > > >>
> > > >>
> > > >>
> > > >> --
> > > >> Xiongqi (Wesley) Wu
> > > >>
> > > >
> > > >
> > > >
> > > > --
> > > > Xiongqi (Wesley) Wu
> > > >
> > >
> > >
> > >
> > > --
> > > Xiongqi (Wesley) Wu
> > >
> >
> >
> > --
> >
> > Brett Rann
> >
> > Senior DevOps Engineer
> >
> >
> > Zendesk International Ltd
> >
> > 395 Collins Street, Melbourne VIC 3000 Australia
> >
> > Mobile: +61 (0) 418 826 017
> >
> 
> 
> 
> -- 
> Xiongqi (Wesley) Wu
> 
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