I would not get gc_grace seconds to 0, set to to something small. gc_grace_seconds or ttl is only the minimum amount of time the column will stay in the data files. The columns are only purged when compaction runs some time after that timespan has ended.
If you are seeing issues where a heavy delete workload is having an noticeably adverse effect on read performance then you should look at the data model. Consider ways to spread the write / read / delete workload over multiple rows. If you cannot get away from it then experiment with reducing the min_compactioon_threshold of the CF's so that compaction kicks in quicker, and (potentially) tombstones are purged faster. Chees ----------------- Aaron Morton Freelance Cassandra Developer @aaronmorton http://www.thelastpickle.com On 5/10/2011, at 6:03 AM, Daning wrote: > Thanks Aaron. How about I set the gc_grace_seconds to 0 or like 2 hours? I > like to clean up tomebstone sooner, I don't care losing some data and all > my columns have ttl. > > If one node is down longer than gc_grace_seconds, and I got tombstone > removed, once the node is up, from my understanding deleted data will be > synced back. In this case my data will be processed twice and it will not be > a big deal to me. > > Thanks, > > Daning > > > On 10/04/2011 01:27 AM, aaron morton wrote: >> >> Yes that's the slice query skipping past the tombstone columns. >> >> Cheers >> >> ----------------- >> Aaron Morton >> Freelance Cassandra Developer >> @aaronmorton >> http://www.thelastpickle.com >> >> On 4/10/2011, at 4:24 PM, Daning Wang wrote: >> >>> Lots of SliceQueryFilter in the log, is that handling tombstone? >>> >>> DEBUG [ReadStage:49] 2011-10-03 20:15:07,942 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317582939743663:true:4@1317582939933000 >>> DEBUG [ReadStage:50] 2011-10-03 20:15:07,942 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317573253148778:true:4@1317573253354000 >>> DEBUG [ReadStage:43] 2011-10-03 20:15:07,942 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317669552951428:true:4@1317669553018000 >>> DEBUG [ReadStage:33] 2011-10-03 20:15:07,942 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317581886709261:true:4@1317581886957000 >>> DEBUG [ReadStage:52] 2011-10-03 20:15:07,942 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317568165152246:true:4@1317568165482000 >>> DEBUG [ReadStage:36] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317567265089211:true:4@1317567265405000 >>> DEBUG [ReadStage:53] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317674324843122:true:4@1317674324946000 >>> DEBUG [ReadStage:38] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317571990078721:true:4@1317571990141000 >>> DEBUG [ReadStage:57] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317671855234221:true:4@1317671855239000 >>> DEBUG [ReadStage:54] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317558305262954:true:4@1317558305337000 >>> DEBUG [RequestResponseStage:11] 2011-10-03 20:15:07,941 >>> ResponseVerbHandler.java (line 48) Processing response on a callback from >>> 12347@/10.210.101.104 >>> DEBUG [RequestResponseStage:9] 2011-10-03 20:15:07,941 >>> AbstractRowResolver.java (line 66) Preprocessed data response >>> DEBUG [RequestResponseStage:13] 2011-10-03 20:15:07,941 >>> AbstractRowResolver.java (line 66) Preprocessed digest response >>> DEBUG [ReadStage:58] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317581337972739:true:4@1317581338044000 >>> DEBUG [ReadStage:64] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317582656796332:true:4@1317582656970000 >>> DEBUG [ReadStage:55] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317569432886284:true:4@1317569432984000 >>> DEBUG [ReadStage:45] 2011-10-03 20:15:07,941 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317572658687019:true:4@1317572658718000 >>> DEBUG [ReadStage:47] 2011-10-03 20:15:07,940 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317582281617755:true:4@1317582281717000 >>> DEBUG [ReadStage:48] 2011-10-03 20:15:07,940 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: 1317549607869226:true:4@1317549608118000 >>> DEBUG [ReadStage:34] 2011-10-03 20:15:07,940 SliceQueryFilter.java (line >>> 123) collecting 0 of 1: >>> On Thu, Sep 29, 2011 at 2:17 PM, aaron morton <aa...@thelastpickle.com> >>> wrote: >>> As with any situation involving the un-dead, it really is the number of >>> Zombies, Mummies or Vampires that is the concern. >>> >>> If you delete data there will always be tombstones. If you have a delete >>> heavy workload there will be more tombstones. This is why implementing a >>> queue with cassandra is a bad idea. >>> >>> gc_grace_seconds (and column TTL) are the *minimum* about of time the >>> tombstones will stay in the data files, there is no maximum. >>> >>> Your read performance also depends on the number of SSTables the row is >>> spread over, see >>> http://thelastpickle.com/2011/04/28/Forces-of-Write-and-Read/ >>> >>> If you really wanted to purge them then yes a repair and then major >>> compaction would be the way to go. Also consider if it's possible to design >>> the data model around the problem, e.g. partitioning rows by date. IMHO I >>> would look to make data model changes before implementing a compaction >>> policy, or consider if cassandra is the right store if you have a delete >>> heavy workload. >>> >>> Cheers >>> >>> >>> ----------------- >>> Aaron Morton >>> Freelance Cassandra Developer >>> @aaronmorton >>> http://www.thelastpickle.com >>> >>> On 30/09/2011, at 3:27 AM, Daning Wang wrote: >>> >>>> Jonathan/Aaron, >>>> >>>> Thank you guy's reply, I will change GCGracePeriod to 1 day to see what >>>> will happen. >>>> >>>> Is there a way to purge tombstones at anytime? because if tombstones >>>> affect performance, we want them to be purged right away, not after >>>> GCGracePeriod. We know all the nodes are up, and we can do repair first to >>>> make sure the consistency before purging. >>>> >>>> Thanks, >>>> >>>> Daning >>>> >>>> >>>> On Wed, Sep 28, 2011 at 5:22 PM, aaron morton <aa...@thelastpickle.com> >>>> wrote: >>>> if I had to guess I would say it was spending time handling tombstones. If >>>> you see it happen again, and are interested, turn the logging up to DEBUG >>>> and look for messages from something starting with "Slice" >>>> >>>> Minor (automatic) compaction will, over time, purge the tombstones. Until >>>> then reads must read discard the data deleted by the tombstones. If you >>>> perform a big (i.e. 100k's ) delete this can reduce performance until >>>> compaction does it's thing. >>>> >>>> My second guess would be read repair (or the simple consistency checks on >>>> read) kicking in. That would show up in the "ReadRepairStage" in TPSTATS >>>> >>>> it may have been neither of those two things, just guesses. If you have >>>> more issues let us know and provide some more info. >>>> >>>> Cheers >>>> >>>> >>>> ----------------- >>>> Aaron Morton >>>> Freelance Cassandra Developer >>>> @aaronmorton >>>> http://www.thelastpickle.com >>>> >>>> On 29/09/2011, at 6:35 AM, Daning wrote: >>>> >>>> > I have an app polling a few CFs (select first N * from CF), there were >>>> > data in CFs but later were deleted so CFs were empty for a long time. I >>>> > found Cassandra CPU usage was getting high to 80%, normally it uses less >>>> > than 30%. I issued the select query manually and feel the response is >>>> > slow. I have tried nodetool compact/repair for those CFs but that does >>>> > not work. later, I issue 'truncate' for all the CFs and CPU usage gets >>>> > down to 1%. >>>> > >>>> > Can somebody explain to me why I need to truncate an empty CF? and what >>>> > else I could do to bring the CPU usage down? >>>> > >>>> > I am running 0.8.6. >>>> > >>>> > Thanks, >>>> > >>>> > Daning >>>> > >>>> >>>> >>> >>> >> >
