A few more hints, after investigation with the team. 1. We can't really have rotating DBs as sometimes we want to keep older transaction records in the DB for a longer time. 2. We never replicate nor update the statements (so the _rev_limit won't really change much (or will it for the compaction??))
On Thu, Jun 14, 2012 at 3:14 PM, Nicolas Peeters <[email protected]>wrote: > Actually we never modify those records. Just query them up in certain > cases. > > Regarding Robert's suggestion, I was indeed confused because he was > suggesting to delete them one by one. > > I need to read about the "lower_revs_limit". We never replicate this data. > > > On Thu, Jun 14, 2012 at 3:08 PM, Tim Tisdall <[email protected]> wrote: > >> I think he's suggesting avoiding compaction completely. Just delete >> the old DB when you've finished deleting all the records. >> >> On Thu, Jun 14, 2012 at 9:05 AM, Nicolas Peeters <[email protected]> >> wrote: >> > Interesting suggestion. However, this would perhaps have the same effect >> > (deleting/compacting the old DB is what makes the system slower)...? >> > >> > On Thu, Jun 14, 2012 at 2:54 PM, Robert Newson <[email protected]> >> wrote: >> > >> >> Do you eventually delete every document you add? >> >> >> >> If so, consider using a rolling database scheme instead. At some >> >> point, perhaps daily, start a new database and write new transaction >> >> logs there. Continue deleting old logs from the previous database(s) >> >> until they're empty (doc_count:0) and then delete the database. >> >> >> >> B. >> >> >> >> On 14 June 2012 13:44, Nicolas Peeters <[email protected]> wrote: >> >> > I'd like some advice from the community regarding compaction. >> >> > >> >> > *Scenario:* >> >> > >> >> > We have a large-ish CouchDB database that is being used for >> transactional >> >> > logs (very write heavy). Once in a while, we delete some of the >> records >> >> in >> >> > large batches and we have scheduled compaction (not automatic (yet)) >> >> every >> >> > 12hours. >> >> > >> >> > From what I can see, the DB is being hammered significantly every 12 >> >> hours >> >> > and the compaction is taking 4 hours (with a size of 50-100GB of log >> >> data). >> >> > >> >> > *The problem:* >> >> > >> >> > The problem is that compaction takes a very long time and reduces the >> >> > performance of the stack. It seems that it's hard for the compaction >> >> > process to "keep up" with the insertions, hence why it takes so long. >> >> Also, >> >> > what I'm not sure is how "incremental" the compaction is... >> >> > >> >> > 1. In this case, would it make sense to run the compaction more >> often >> >> > (every 10 minutes); since we're write-heavy. >> >> > 1. Should we just run more often? (so hopefully it doesn't do >> >> > unnecessary work too often). Actually, in our case, we should >> >> probably >> >> > never have automatic compaction if there has been no >> "termination". >> >> > 2. Or actually only once in a while? (bigger batch, but less >> >> > "useless" overhead) >> >> > 3. Or should we just wait that a given size (which is the >> problem >> >> > really) is hit and use the auto compaction (in CouchDB 1.2.0) >> for >> >> this? >> >> > 2. In CouchDB 1.2.0 there's a new feature: auto >> >> > compaction< >> >> http://wiki.apache.org/couchdb/Compaction#Automatic_Compaction> >> >> > which >> >> > may be useful for us. There's the "strict_window" feature to give >> a max >> >> > amount of time to compact and cancel the compaction after that (in >> >> order >> >> > not to have it running for 4h+…). I'm wondering what the impact of >> >> that is >> >> > on the long run. What if the compaction cannot be completed in that >> >> window? >> >> > >> >> > Thanks a lot! >> >> > >> >> > Nicolas >> >> >> > >
