Ahh yes, I see that now... Is that what the grey faint line on the end of those graphs represent? I actually didn't notice that the first time, just thought the black line going up was it...
On Tue, Jun 1, 2010 at 10:13 AM, Randall Leeds <[email protected]> wrote: > If you look at the script the compaction is only performed at the end > and not on each iteration. > > On Mon, May 31, 2010 at 16:58, Nicholas Orr <[email protected]> wrote: >> This all makes sense except the OP says a compaction step is being >> performed. >> A compaction is essentially a copy/paste/delete/rename operation, so the on >> disk size should be fairly constant as the data copied is just the info >> required isn't it? >> >> Nick >> >> On Tue, Jun 1, 2010 at 9:39 AM, Randall Leeds <[email protected]>wrote: >> >>> Hi Konrad, >>> >>> I'll take a stab at this and if I'm wrong hopefully someone will correct >>> me. >>> >>> The on disk BTree is written in an append only fashion rather than >>> modified in place. Append only updates mean that every inner node of >>> the BTree along the path from the root to the new update has to be >>> re-written each time. Initially, when there are very few inner nodes, >>> the amount of disk space used for each new update is relatively >>> constant. Since the tree has a large fan-out the depth does not change >>> much at first. In the second graph you are seeing a tree that has a >>> depth of 1 (just the root) being written over an over again to disk >>> and the corresponding expected linear growth results. However, when >>> you have a higher revision limit the old revisions are kept in the >>> tree and the tree grows taller and fatter with each update. As you >>> make more updates more inner nodes need to be rewritten for each >>> update which causes the growth to accelerate. Eventually, you hit the >>> revision limit and old revisions are discarded, the tree stops getting >>> any taller or fatter and the number of inner nodes that need to be >>> changed for each update remains relatively constant (but greater than >>> in the case of rev_limit=1). I suspect that the first graph becomes >>> linear above 1000 updates and does not continue to accelerate. >>> >>> Cheers, >>> Randall >>> >>> 2010/5/31 Konrad Förstner <[email protected]>: >>> > Hi, >>> > >>> > I have an issue with CouchDB and posted the question on stackoverflow >>> > [1] but did not get any helpful answer. I would be great if somebody >>> > could answer this here or a stackoverflow (there I also had a problem >>> > with the compaction which was just a timing issue as explaint in the >>> > comment) >>> > >>> > I was wondering why my CouchDB database was growing to fast so I wrote >>> > a little test script [2]. This script changes an attributed of a CouchDB >>> > document 1200 times and takes the size of the database after each >>> > change. After performing these 1200 writing steps the database is >>> > doing a compaction step and the db size is measured again. In the end >>> > the script plots the databases size against the revision numbers. The >>> > benchmarking is run twice: >>> > >>> > * The first time the default number of document revision (=1000) is used >>> (_revs_limit). >>> > >>> > * The second time the number of document revisions is set to 1. >>> > >>> > The first run produces the following plot >>> > http://www.flickr.com/photos/konradfoerstner/4656011444/ >>> > >>> > The second run produces this plot second run >>> > http://www.flickr.com/photos/konradfoerstner/4656012732/ >>> > >>> > For me this is quite an unexpected behavior. In the first run I would >>> > have expected a linear growth as every change produces a new >>> > revision. When the 1000 revisions are reached the size value should be >>> > constant as the older revisions are discarded. >>> > >>> > In the second run the first revision should result in certain database >>> > size that is then keeps during the following writing steps as every >>> > new revision leads to the deletion of the previous one. >>> > >>> > I could understand if there is a little bit of overhead needed to >>> > manage the changes but this growth behavior seems weird to me. Can >>> > anybody explain this phenomenon or correct my assumptions that lead to >>> > the wrong expectations? >>> > >>> > Many thanks in advance >>> > >>> > Konrad >>> > >>> > [1] >>> http://stackoverflow.com/questions/2921151/why-do-my-couchdb-databases-grow-so-fast >>> > [2] http://github.com/konrad/couchdb-benchmarking >>> > >>> > >>> > >>> > >>> > >>> > >>> >> >
