[Gluster-devel] Performance tuning for MySQL

[David Sickmiller]

Hi,

I really appreciate the information from Raghavendra regarding how the 
performance translators affect MySQL's integrity.  This week I spent 
some hours coarsely testing various performance options, and I would be 
interested in validating whether I'm getting typical results as well as 
learning ways to improve from here.  Perhaps my experience would be 
useful for others.

I'm running 2.0rc1 with the 2.6.27 kernel.  I have a 2-node cluster.  
GlusterFS runs on both nodes, and MySQL runs on the active node.  If the 
active node fails or is put on standby, MySQL fires up on the other 
node.  Unlike MySQL Replication with its slave lag, I know my data 
changes are durable in the event of a server failure.  Most people use 
DRBD for this, but I'm hoping to enjoy GlusterFS's benefits of handling 
split-brain situations at the file level instead of the volume level, 
future scalability avenues, and general ease of use.  Hopefully DRBD 
doesn't have unmatchable performance advantages I'm overlooking.

I've been running two tests.  They aren't necessarily realistic usage, 
but I'm just looking for the big settings that affect performance by a 
factor of two or more.  My database files are about 1GB.  The first test 
is "time mysqldump --no-data" which simply prints out the schema.  The 
second test is "time mysqldump | gzip > /glusterfs/export.gz" which 
exports the entire database, compresses it, and saves it onto the 
GlusterFS filesystem.  The 450MB of exported SQL statements compress to 
75MB.

I'm going to report my testing in order, because the changes were 
cumulative.  I used server-side io-threads from the start.  Before I 
started recording the speed, I discovered that running in single process 
mode was dramatically faster.  At that time, I also configured 
read-subvolume to use the local server.  At this point I started measuring:

    * Printing schema: 18s
    * Compressed export: 2m45s

For a benchmark, I moved MySQL's datafiles to the local ext3 disk (but 
kept writing the export to GlusterFS).  It was 10-100X faster!

    * Printing schema: 0.2s
    * Compressed export: 28s

There was no appreciable changes from installing fuse-2.7.4glfs11, using 
Booster, or running blockdev to increase readahead from 256 to 16384.

Adding the io-cache client-side translator didn't affect printing the 
schema but cut the export in half:

    * Compressed export: 1m10s

Going off on a tangent, I shut down the remote node.  This increased the 
performance by an order of magnitude:

    * Printing schema: 2s
    * Compressed export: 24s

I resumed testing with both servers running.  Switching the I/O 
scheduler to deadline had no appreciable affect.  Neither did adding 
client-side io-threads, or server-side write-behind.  Surprisingly, I 
found that changing read-subvolume to the remove server had only a minor 
penalty.

Then I noticed that the remote server was listed first in the volfile, 
which means that it gets used for the lock server.  Swapping the order 
in the volfile on one server seemed to cause split-brain errors -- does 
the order need to be the same on both servers?  When I changed both 
servers' volfiles to use the active MySQL server as the lock server, 
there was a dramatic performance increase, to roughly around the 2s/24s 
speed I saw with one server down.  (I lost the exact stats.)

In summary, running in single process mode, client-side io-cache, and a 
local lock file were the changes that made a significant difference.


Since I'm only going to have one server writing to the filesystem at a 
time, I could mount it read-only (or not at all) on the other server.  
Would that mean I could safely set data-lock-server-count=0 and 
entry-lock-server-count=0 because I can be confident that there won't be 
any conflicting writes?  I don't want to take unnecessary risks, but it 
seems like unnecessary overhead for my use case.

Are there any additional recommended performance changes?  Would 
server-side AFR change things?  Printing the schema still runs 10X 
faster when the database is on a local ext3 filesystem.

Thank you,
David

-- 
David Sickmiller

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