Hi,

i wasn´t really that aware that this could only led to higher usage of CPU 
and RAM, but to say so, the cpu load has indeed increased by about 20-30% 
compared to not compressing the storage. The RAM usage didnt increase by a 
big deal.

IMHO a bit higher CPU-load is definietly worth it, if you could save about 
60% of your hard disk space - every financial manager would agree.

Am Montag, 4. August 2014 14:06:47 UTC+2 schrieb Jörg Prante:
>
> You are aware of the fact the kind of search performance you mean 
> depends on RAM and virtual memory organization of the cluster, not on 
> storage, so "without any siginifcant performace losses" could be expected 
> ? 
>
> Jörg 
>
> Am 04.08.14 12:41, schrieb horst knete: 
> > We are indexing all sort of events (Windows, Linux, Apache, Netflow 
> > and so on...) and impact is defined in speed of the Kibana GUI / how 
> > long it takes to load 7 or 14 days of data. Thats what is important 
> > for my colleagues. 
> > 
> > 
> > Am Montag, 4. August 2014 10:52:25 UTC+2 schrieb Mark Walkom: 
> > 
> >     What sort of data are you indexing? When you said performance 
> >     impact was minimal, how minimal and at what points are you seeing 
> it? 
> > 
> >     Regards, 
> >     Mark Walkom 
> > 
> >     Infrastructure Engineer 
> >     Campaign Monitor 
> >     email: [email protected] 
> >     web: www.campaignmonitor.com <http://www.campaignmonitor.com> 
> > 
> > 
> >     On 4 August 2014 16:43, horst knete <[email protected]> wrote: 
> > 
> >         Hi again, 
> > 
> >         a quick report regarding compression: 
> > 
> >         we are using a 3-TB btrfs-volume with 32k block size now which 
> >         reduced the amount of data from 3,2 TB to 1,1TB without any 
> >         segnificant performance losses ( we are using a 8 CPU, 20 GB 
> >         Memory machine with an iSCSI.Link to the volume ). 
> > 
> >         So for us i can only suggest using the btrfs-volume for long 
> >         term storage. 
> > 
> >         Am Montag, 21. Juli 2014 08:48:12 UTC+2 schrieb Patrick 
> >         Proniewski: 
> > 
> >             Hi, 
> > 
> >             gzip/zlib compression is very bad for performance, so it 
> >             can be interesting for closed indices, but for live data I 
> >             would not recommend it. 
> >             Also, you must know that: 
> > 
> >             Compression using lz4 is already enabled into indices, 
> >             ES/Lucene/Java usually read&write 4k blocks, 
> > 
> >             -> hence, compression is achieved on 4k blocks. If your 
> >             filesystem uses 4k blocks and you add FS compression, you 
> >             will probably have a very small gain, if any. I've tried 
> >             on ZFS: 
> > 
> >             Filesystem             Size    Used   Avail Capacity 
> >              Mounted on 
> >             zdata/ES-lz4           1.1T    1.9G    1.1T 0%   
> >              /zdata/ES-lz4 
> >             zdata/ES               1.1T    1.9G    1.1T 0%    /zdata/ES 
> > 
> >             If you are using a larger block size, like 128k, a 
> >             compressed filesystem does show some benefit: 
> > 
> >             Filesystem             Size    Used   Avail Capacity 
> >              Mounted on 
> >             zdata/ES-lz4           1.1T    1.1G    1.1T 0%   
> >              /zdata/ES-lz4        -> compressratio  1.73x 
> >             zdata/ES-gzip          1.1T    901M    1.1T 0%   
> >              /zdata/ES-gzip        -> compressratio  2.27x 
> >             zdata/ES               1.1T    1.9G    1.1T 0%    /zdata/ES 
> > 
> >             But a file system block larger than 4k is very suboptimal 
> >             for IO (ES read or write one 4k block -> your FS must read 
> >             or write a 128k block). 
> > 
> >             On 21 juil. 2014, at 07:58, horst knete 
> >             <[email protected]> wrote: 
> > 
> >             > Hey guys, 
> >             > 
> >             > we have mounted an btrfs file system with the 
> >             compression method "zlib" for 
> >             > testing purposes on our elasticsearchserver and copied 
> >             one of the indices 
> >             > on the btrfs volume, unfortunately it had no success and 
> >             still got the size 
> >             > of 50gb :/ 
> >             > 
> >             > I will further try it with other compression methods and 
> >             will report here 
> >             > 
> >             > Am Samstag, 19. Juli 2014 07:21:20 UTC+2 schrieb Otis 
> >             Gospodnetic: 
> >             >> 
> >             >> Hi Horst, 
> >             >> 
> >             >> I wouldn't bother with this for the reasons Joerg 
> >             mentioned, but should 
> >             >> you try it anyway, I'd love to hear your 
> >             findings/observations. 
> >             >> 
> >             >> Otis 
> >             >> -- 
> >             >> Performance Monitoring * Log Analytics * Search Analytics 
> >             >> Solr & Elasticsearch Support * http://sematext.com/ 
> >             >> 
> >             >> 
> >             >> 
> >             >> On Wednesday, July 16, 2014 6:56:36 AM UTC-4, horst 
> >             knete wrote: 
> >             >>> 
> >             >>> Hey Guys, 
> >             >>> 
> >             >>> to save a lot of hard disk space, we are going to use 
> >             an compression file 
> >             >>> system, which allows us transparent compression for 
> >             the es-indices. (It 
> >             >>> seems like es-indices are very good compressable, got 
> >             up to 65% 
> >             >>> compression-rate in some tests). 
> >             >>> 
> >             >>> Currently the indices are laying at a ext4-Linux 
> >             Filesystem which 
> >             >>> unfortunately dont have the transparent compression 
> >             ability. 
> >             >>> 
> >             >>> Anyone of you got experience with compression file 
> >             systems like BTRFS or 
> >             >>> ZFS/OpenZFS and can tell us if this led to big 
> >             performance losses? 
> >             >>> 
> >             >>> Thanks for responding 
> > 
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