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https://issues.apache.org/jira/browse/COUCHDB-738?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12863646#action_12863646
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Adam Kocoloski commented on COUCHDB-738:
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Ok, here's a first pass. I ran the usual perf.py script which loads 1000
'simple' and 1000 'unsimple' docs into a DB and computes the MegaView and
SimpleView. I modified the script to update each document 100 times instead of
only once. Here are the numbers for trunk:
DB size: 1.1G pre-compaction, 12MB post
MegaView
Elapsed time: 7.20 (s)
Elapsed time: 5.65 (s)
Elapsed time: 5.13 (s)
SimpleView
Elapsed time: 0.75 (s)
Elapsed time: 1.04 (s)
Elapsed time: 0.74 (s)
Indexing times after compaction
Elapsed time: 4.91 (s)
Elapsed time: 0.74 (s)
Note that only the first measurement included a full load_docs step. For the
latter measurements I just deleted and rebuilt the index files (updating the
docs 100 times took several minutes, and I didn't feel like waiting). Here are
the equivalent numbers with the patch:
DB size: 1.5G pre-compaction, 17MB post
MegaView
Elapsed time: 9.03 (s)
Elapsed time: 8.22 (s)
Elapsed time: 5.92 (s)
SimpleView
Elapsed time: 0.99 (s)
Elapsed time: 0.94 (s)
Elapsed time: 0.91 (s)
After compaction
Elapsed time: 5.81 (s)
Elapsed time: 0.90 (s)
There seems to be quite a bit of variance in these numbers. I usually take the
minimum when benchmarking on my laptop, although due to my skipping the
load_docs step the minimum is probably a little too good (the seq_tree is fully
cached). Anyway, if I stick with that methodology I'd say that for DBs with
100 edits/document we see
MegaView: 15-18% slower with patch
SimpleView: 22-23% slower with patch
The database is 35-40% larger, too.
I might try loading a 500 edits / document DB tonight. I may also look at
eprof to see if there are simple optimizations for this use case. Is the
number of edit branches significant? So far I haven't been introducting any
conflicts in the test.
> more efficient DB compaction (fewer seeks)
> ------------------------------------------
>
> Key: COUCHDB-738
> URL: https://issues.apache.org/jira/browse/COUCHDB-738
> Project: CouchDB
> Issue Type: Improvement
> Components: Database Core
> Affects Versions: 0.9.2, 0.10.1, 0.11
> Reporter: Adam Kocoloski
> Assignee: Adam Kocoloski
> Fix For: 1.1
>
> Attachments: 738-efficient-compaction-v1.patch
>
>
> CouchDB's database compaction algorithm walks the by_seq btree, then does a
> lookup in the by_id btree for every document in the database. It does this
> because the #full_doc_info{} record with the full revision tree is only
> stored in the by_id tree. I'm proposing instead to store duplicate copies of
> #full_doc_info{} in both trees, and to have the compactor use the by_seq tree
> exclusively. The net effect is significantly fewer calls to pread(), and an
> compaction IO pattern where reads tend to be clustered close to each other in
> the file.
> If the by_id tree is fully cached, or if the id tree nodes are located near
> the seq tree nodes, the performance improvement is small but noticeable (~10%
> in some simple tests). On the other hand, in the worst-case scenario of
> randomly-generated docids and a database much larger than main memory the
> improvement is huge. Joe Williams did some simple benchmarks with a 50k
> document, 600 MB database on a 256MB VPS. The compaction time for that DB
> dropped from 15m to 2m20s, so more than 6x faster.
> Storing the #full_doc_info{} in the seq tree also allows for some similar
> optimizations in the replicator.
> This patch might have downsides when documents have a large number of edits.
> These include an increase in the size of the database and slower view
> indexing. I expect both to be small effects.
> The patch can be applied directly to tr...@934272. Existing DBs are still
> readable, new updates will be written in the new format, and databases can be
> fully upgraded by compacting.
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