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Segmented Key Cache Performance

Testing method for segmented key cache performance

We used SysBench v0.5 from Launchpad to test the segmented key cache performance for the MyISAM storage engine of MariaDB 5.2.2-gamma.

As wrapper scripts for automated running of SysBench we used the sysbench/ directory from MariaDB Tools.

To test that splitting the key cache's global mutex into several mutex helps under multi user load, we wrote a new SysBench test called select_random_points.lua. We used one big table and selected random points with increasing number of concurrent users.

Main testing outcomes

We see up to 250% performance gain depending on the amount of concurrent users.

Detailed testing outcomes

On our machine pitbull

On pitbull with --random-points=10

pitbull_rp10

In relative numbers:

Threads	               1      4      8      16      32      64      128
(32/off)             -3%    53%    122%    155%    226%    269%    237%
(64/off)             -6%    55%    130%    162%    234%    270%    253%

select_random_points.lua --random-points=10

On pitbull with --random-points=50

pitbull_rp50

In relative numbers:

Threads	               1      4      8      16      32      64      128
(32/off)             -3%    53%    113%    154%    232%    254%    231%
(64/off)             -1%    55%    121%    161%    235%    268%    244%

select_random_points.lua --random-points=50

On pitbull with --random-points=100

pitbull_rp100

In relative numbers:

Threads	               1      4      8      16      32      64      128
(32/off)             -3%    54%    121%    160%    209%    246%    219%
(64/off)             -6%    56%    129%    167%    219%    260%    241%

select_random_points.lua --random-points=100

Detailed numbers of all runs on pitbull

You can find the absolute and relative numbers in our OpenOffice.org spread sheet here: SysBench v0.5 select_random_points on pitbull

On our machine perro

On perro with --random-points=10

perro_rp10

In relative numbers:

Threads	               1      4      8      16      32      64      128
(32/off)              1%     2%     17%     45%     73%     70%     71%
(64/off)             -0.3%   6%     19%     46%     72%     74%     80%

select_random_points.lua --random-points=10

On perro with --random-points=50

perro_rp50

In relative numbers:

Threads	               1      4      8      16      32      64      128
(32/off)              1%    10%     26%     69%    105%    122%    114%
(64/off)             -1%     8%     27%     75%    111%    120%    131%

select_random_points.lua --random-points=50

On perro with --random-points=100

perro_rp100

In relative numbers:

Threads	               1      4      8      16      32      64      128
(32/off)            -0.2%    1%     22%	    73%    114%    114%    126%
(64/off)            -0.1%    4%     22%     75%    112%    125%    135%

select_random_points.lua --random-points=100

Detailed numbers of all runs on perro

You can find the absolute and relative numbers in our OpenOffice.org spread sheet here: SysBench v0.5 select_random_points on perro

Table and query used

Table definition:

CREATE TABLE sbtest (
  id  int unsigned NOT NULL AUTO_INCREMENT,
  k   int unsigned NOT NULL DEFAULT '0',
  c   char(120) NOT NULL DEFAULT '',
  pad char(60) NOT NULL DEFAULT '',
  PRIMARY KEY (id),
  KEY k (k)
) ENGINE=MyISAM 

Query used:

SELECT id, k, c, pad
    FROM sbtest
    WHERE k IN (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)

The ? parameters were replaced by random numbers when running the SysBench test. We used 10, 50, and 100 random points in our tests.

We inserted 20 million rows using random data, which gave us a data and index file size of:

3.6G    sbtest.MYD
313M    sbtest.MYI

We chose our key buffer size to be big enough to hold the index file.

Testing environment

MariaDB sources

We used MariaDB 5.2.2-gamma with following revision from our launchpad repository Revision #2878

revno: 2878
committer: Sergei Golubchik <sergii@pisem.net>
branch nick: 5.2
timestamp: Tue 2010-10-26 07:37:44 +0200
message:
  fixes for windows

Compiling MariaDB

We compiled MariaDB using this line:

BUILD/compile-amd64-max

MariaDB runtime options

We used following configuration for running MariaDB

MYSQLD_OPTIONS="--no-defaults \
  --datadir=$DATA_DIR \
  --language=./sql/share/english \
  --log-error \
  --key_buffer_size=512M \
  --max_connections=256 \
  --query_cache_size=0 \
  --query_cache_type=0 \
  --skip-grant-tables \
  --socket=$MY_SOCKET \
  --table_open_cache=512 \
  --thread_cache=512 \
  --key_cache_segments=0 \ # 0 | 32 | 64
  --tmpdir=$TEMP_DIR"

SysBench v0.5 select_random_points.lua options

We run the SysBench v0.5 select_random_points.lua test with following options:

# 20 million rows.
TABLE_SIZE=20000000

SYSBENCH_OPTIONS="--oltp-table-size=$TABLE_SIZE \
  --max-requests=0 \
  --mysql-table-engine=MyISAM \
  --mysql-user=root \
  --mysql-engine-trx=no \
  --myisam-max-rows=50000000 \
  --rand-seed=303"

We tested with increasing number of concurrent users with a warm up time of 8 minutes and a run time of 20 minutes:

NUM_THREADS="1 4 8 16 32 64 128"
...
  --num-threads=$THREADS

We also tested an increasing number of random points:

# Default option is --random-points=10.
SYSBENCH_TESTS[0]="select_random_points.lua"
SYSBENCH_TESTS[1]="select_random_points.lua --random-points=50"
SYSBENCH_TESTS[2]="select_random_points.lua --random-points=100"

Kernel parameters

IO scheduler

For optimal IO performance running a database we are using the noop scheduler. You can check your scheduler setting with:

cat /sys/block/${DEVICE}/queue/scheduler

For instance, it should look like this output:

cat /sys/block/sda/queue/scheduler
[noop] deadline cfq

You can find detailed notes about Linux schedulers here: Linux schedulers in TPCC like benchmark.

Open file limits

Having a lot of concurrent connections can hit the open file limit on your system. On most Linux systems the open file limit is at 1024, which can be not enough. Please set your open file limit higher by editing

$EDITOR /etc/security/limits.conf

and adding a line like

#ftp             hard    nproc           0
#@student        -       maxlogins       4
*                -       nofile          16384

# End of file

Your ulimit -a output should look like this afterwards:

ulimit -a
core file size          (blocks, -c) 0
data seg size           (kbytes, -d) unlimited
scheduling priority             (-e) 0
file size               (blocks, -f) unlimited
pending signals                 (-i) 15975
max locked memory       (kbytes, -l) 64
max memory size         (kbytes, -m) 1744200
open files                      (-n) 16384

Machines used for testing

perro

# OS: openSUSE 11.1 (x86_64)
# Platform: x86_64
# CPU: Quad-core Intel @ 3.20GHz: 4 CPUs
# RAM: 2GB
# Disk(s): 2 x ST31000528AS S-ATA as software RAID 0

pitbull

# OS: Ubuntu 10.10
# Platform: x86_64
# CPU: Two-socket x hexa-core Intel Xeon X5660 @ 2.80GHz. With hyperthreading: 24CPUs
# RAM: 28GB
# Disk(s): 1 x ST3500320NS S-ATA
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