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 > > > > > > > > > > > > >
