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https://issues.apache.org/jira/browse/COUCHDB-1334?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13838313#comment-13838313
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James Birmingham commented on COUCHDB-1334:
-------------------------------------------
A performance gain in this area is of great practical use for many of us.
The skills necessary to solve this for Windows isn't forthcoming but the
majority of the user base is non Windows (I don't know the actual figures, do
they even exist?).
If there is a real world user on Windows who needs this fix then perhaps they
will step up once this is released and the issue is wider known, please don't
hold the rest of us back for the sake of purity of code.
> Indexer speedup (for non-native view servers)
> ---------------------------------------------
>
> Key: COUCHDB-1334
> URL: https://issues.apache.org/jira/browse/COUCHDB-1334
> Project: CouchDB
> Issue Type: Improvement
> Components: Database Core, JavaScript View Server, View Server
> Support
> Reporter: Filipe Manana
> Assignee: Dave Cottlehuber
> Fix For: 1.6.0
>
> Attachments: 0001-More-efficient-view-updater-writes.patch,
> 0002-More-efficient-communication-with-the-view-server.patch,
> master-0002-More-efficient-communication-with-the-view-server.patch,
> master-2-0002-More-efficient-communication-with-the-view-server.patch,
> master-3-0002-More-efficient-communication-with-the-view-server.patch,
> master-4-0002-More-efficient-communication-with-the-view-server.patch
>
>
> The following 2 patches significantly improve view index generation/update
> time and reduce CPU consumption.
> The first patch makes the view updater's batching more efficient, by ensuring
> each btree bulk insertion adds/removes a minimum of N (=100) key/value
> pairts. This also makes the index file size grow not so fast with old data
> (old btree nodes basically). This behaviour is already done in master/trunk
> in the new indexer (by Paul Davis).
> The second patch maximizes the throughput with an external view server (such
> as couchjs). Basically it makes the pipe (erlang port) communication between
> the Erlang VM (couch_os_process basically) and the view server more efficient
> since the 2 sides spend less time block on reading from the pipe.
> Here follow some benchmarks.
> test database at http://fdmanana.iriscouch.com/test_db (1 million documents)
> branch 1.2.x
> $ echo 3 > /proc/sys/vm/drop_caches
> $ time curl http://localhost:5984/test_db/_design/test/_view/test1
> {"rows":[
> {"key":null,"value":1000000}
> ]}
> real 2m45.097s
> user 0m0.006s
> sys 0m0.007s
> view file size: 333Mb
> CPU usage:
> $ sar 1 60
> 22:27:20 %usr %nice %sys %idle
> 22:27:21 38 0 12 50
> (....)
> 22:28:21 39 0 13 49
> Average: 39 0 13 47
> branch 1.2.x + batch patch (first patch)
> $ echo 3 > /proc/sys/vm/drop_caches
> $ time curl http://localhost:5984/test_db/_design/test/_view/test1
> {"rows":[
> {"key":null,"value":1000000}
> ]}
> real 2m12.736s
> user 0m0.006s
> sys 0m0.005s
> view file size 72Mb
> branch 1.2.x + batch patch + os_process patch
> $ echo 3 > /proc/sys/vm/drop_caches
> $ time curl http://localhost:5984/test_db/_design/test/_view/test1
> {"rows":[
> {"key":null,"value":1000000}
> ]}
> real 1m9.330s
> user 0m0.006s
> sys 0m0.004s
> view file size: 72Mb
> CPU usage:
> $ sar 1 60
> 22:22:55 %usr %nice %sys %idle
> 22:23:53 22 0 6 72
> (....)
> 22:23:55 22 0 6 72
> Average: 22 0 7 70
> master/trunk
> $ echo 3 > /proc/sys/vm/drop_caches
> $ time curl http://localhost:5984/test_db/_design/test/_view/test1
> {"rows":[
> {"key":null,"value":1000000}
> ]}
> real 1m57.296s
> user 0m0.006s
> sys 0m0.005s
> master/trunk + os_process patch
> $ echo 3 > /proc/sys/vm/drop_caches
> $ time curl http://localhost:5984/test_db/_design/test/_view/test1
> {"rows":[
> {"key":null,"value":1000000}
> ]}
> real 0m53.768s
> user 0m0.006s
> sys 0m0.006s
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