[jira] Updated: (COUCHDB-768) Constant Bulk Saving results in Eventual Timeouts

["Paul Joseph Davis (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/COUCHDB-768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Paul Joseph Davis updated COUCHDB-768:
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    Skill Level: Regular Contributors Level (Easy to Medium)

> Constant Bulk Saving results in Eventual Timeouts
> -------------------------------------------------
>
>                 Key: COUCHDB-768
>                 URL: https://issues.apache.org/jira/browse/COUCHDB-768
>             Project: CouchDB
>          Issue Type: Bug
>          Components: HTTP Interface
>    Affects Versions: 0.10.2, 0.11
>         Environment: Software: Using Python 2.6 (couchdbkit OR httplib) OR curl to submit.  The 0.11 is the Debian unstable version; the 0.10.2 install is from Ubuntu.
> CouchDB 0.11 is running on a Sun Fire X4600 M2, with NFS mounted storage to a Linux software RAID10 (x4 WD20EARS SATA drives).  However, same issue arises using the server's 3G/s (10k RPM) SAS drives.  The NFS share is mounted over dual intel gigabit NICs in a round-robin configuration.
>            Reporter: A.W. Stanley
>            Priority: Minor
>
> Situation:
> Saving documents in bulk (lots of 1,000, 4,000, and 10,000 have been tested) to a single database results in degraded performance, and then a string of timeouts.  The timeouts are not logged by CouchDB, so the HTTP interface becomes unusable for a period.  It then returns and rapidly processes the next batch of jobs (read: the timeout is temporary).
> Replication:
> - I am having trouble replicating the behaviour with saving bulk loads of documents (I have been working against doing so), but it appears to happen after an extended period;
> - I can replicate the behaviour by submitting a lot of individual files (single document saves) in rapid succession.
> Diagnostics:
> - I had tried true and false for delayed_commits, just to rule that out;
> - Testing outside of CouchDB (postgres, file transfers, streaming, or otherwise trying to hammer the I/O) yielded no issues with the systems involved.
> Functional Workarounds:
> - I have sharded the database in question.

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