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From Vladimir Ralev <>
Subject Re: Issues with terabytes databases
Date Tue, 22 Apr 2014 16:56:15 GMT
Hi very interesting case, are you sure you are not exceeding the write
capacity of the RAID, few MBs per second is actually enough to starve a lot
of the older HDDs, remember they have to reposition themselves for almost
every write when load is concurrent and out of context, essentially random
access writes on sequential media. This effect is amplified if you are
partitioning your databases. What errors do you get when you go above the
capacity? Do you see error lines in the log? How is the IOwait? Are you
running with debug logs enabled? Do you monitor your couchjs workers and
the system limits?

I think your compaction problem can be solved by BigCouch since it tries to
split the databases into smaller partitions, but splitting the data into
separate databases manually is still common.

On Tue, Apr 22, 2014 at 5:09 PM, Jean-Yves Moulin <> wrote:

> Hi everybody,
> we use CouchDB in production for more than two years now. And we are
> almost happy with it :-) We have a heavy writing workload, with very few
> update, and we never delete data. Some of our databases are terabytes with
> billions of documents (sometimes 20 millions of doc per day). But we are
> experiencing some issues, and the only solution was to split our data:
> today we create a new database each week, with even and odd on two
> different servers (thus we have on-line and off-line servers). This is not
> perfect, and we look forward BigCouch :-)
> Below is some of our current problems with these big databases. For the
> record, we use couchdb-1.2 and couchdb-1.4 on twelve servers running
> FreeBSD (because we like ZFS).
> I don't know if these issues are known or not (or specific to us).
> * Overall speed: we are far from our real server performance: it seems
> that CouchDB is not able to use the full potential of the system. Even with
> 24 disks in RAID10, we can't go faster that 2000 doc/sec (with an average
> document size of 1k, that's only a few MB/s on disk) on replication or
> compaction. CPU and disk are almost idle. Tweaking the number of Erlang I/O
> thread doesn't help.
> * Insert time: At 1000 PUT/sec the insert time is good, even without bulk.
> But it collapses when launching view calculation, replication or
> compaction. So, we use stale view in our applications and views are
> processed regularly by a crontab scripts. We avoid compaction on live
> servers. Compaction are launched manually on off-line servers only. We also
> avoid replication on heavy loaded servers.
> * Compaction: When size of database increase, compaction time can be
> really really long. It will be great if compaction process can run faster
> on already compressed doc. This is our biggest drawback, which implies the
> database split each week. And the speed decreases slowly: compaction starts
> fast (>2000 doc/sec) but slow down to ~100 doc/sec after hundred of
> millions of documents.
> Is there other people using CouchDB this kind of database ? How do you
> handle a write-heavy workload ?
> Sorry for my english and thank you for the reading.
> Best,

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