Mutilate with scons patch
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Jacob Leverich fc0f1a78a4 1. Implemented --measure_* options to reasonably separate
configuration of measurement client (mutilate master) from
load generating clients (mutilate agents).  Use -C and
--measure_depth to approximate open-loop measurement control
(i.e. so long latency requests don't screw up the sample
population), and use -Q to ensure that you see minimal
client-side queuing delay.

2. Quickly documented agent "protocol".  Lots of improvement
to be had here...
2013-03-08 13:19:47 -08:00
.gitignore Initial check-in. 2012-08-23 14:30:32 -07:00
AdaptiveSampler.h Fix compilation on OSX. 2013-01-30 19:46:39 -08:00
AgentStats.h Initial check-in. 2012-08-23 14:30:32 -07:00
barrier.cc Initial check-in. 2012-08-23 14:30:32 -07:00
barrier.h Initial check-in. 2012-08-23 14:30:32 -07:00
binary_protocol.h Merged Stephen Yang's and David Terei's binary protocol and SASL implementations. 2013-03-04 09:31:13 -08:00
cmdline.ggo 1. Implemented --measure_* options to reasonably separate 2013-03-08 13:19:47 -08:00
Connection.cc Remove unused useBinary class variable. 2013-03-04 14:23:50 -08:00
Connection.h Remove unused useBinary class variable. 2013-03-04 14:23:50 -08:00
ConnectionOptions.h Merged Stephen Yang's and David Terei's binary protocol and SASL implementations. 2013-03-04 09:31:13 -08:00
ConnectionStats.h Implement a log-based histogram sampler to increase fidelity for small samples and maximum range for large samples. 2012-12-26 17:08:00 -07:00
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distributions.h Initial check-in. 2012-08-23 14:30:32 -07:00
Generator.cc Added location parameter to GPareto distribution. Validated value-size distribution against Atikoglu's paper by comparing CDF and PDF. 2012-08-24 14:02:57 -07:00
Generator.h Added location parameter to GPareto distribution. Validated value-size distribution against Atikoglu's paper by comparing CDF and PDF. 2012-08-24 14:02:57 -07:00
HistogramSampler.h Initial check-in. 2012-08-23 14:30:32 -07:00
log.cc Initial check-in. 2012-08-23 14:30:32 -07:00
log.h Initial check-in. 2012-08-23 14:30:32 -07:00
LogHistogramSampler.h Fix compilation on OSX. 2013-01-30 19:46:39 -08:00
mutilate.cc 1. Implemented --measure_* options to reasonably separate 2013-03-08 13:19:47 -08:00
mutilate.h Initial check-in. 2012-08-23 14:30:32 -07:00
Operation.h Added binary plaintext SASL support, toggable with --sasl=user[:pass] 2013-03-02 05:46:39 -08:00
README.md Indentation for command-line options. 2013-01-18 14:29:57 -08:00
SConstruct Fix compilation on OSX. 2013-01-30 19:46:39 -08:00
TestGenerator.cc Added location parameter to GPareto distribution. Validated value-size distribution against Atikoglu's paper by comparing CDF and PDF. 2012-08-24 14:02:57 -07:00
util.cc Initial check-in. 2012-08-23 14:30:32 -07:00
util.h Initial check-in. 2012-08-23 14:30:32 -07:00

Mutilate

Mutilate is a memcached load generator designed for high request rates, good tail-latency measurements, and realistic request stream generation.

Requirements

  1. A C++0x compiler
  2. scons
  3. libevent
  4. gengetopt
  5. zeromq (optional)

Mutilate has only been thoroughly tested on Ubuntu 11.10. We'll flesh out compatibility over time.

Building

apt-get install scons libevent-dev gengetopt libzmq-dev
scons

Usage

Type './mutilate -h' for a full list of command-line options. At minimum, a server must be specified.

$ ./mutilate -s localhost
#type       avg     min     1st     5th    10th    90th    95th    99th
read       52.4    41.0    43.1    45.2    48.1    55.8    56.6    71.5
update      0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0
op_q        1.5     1.0     1.0     1.1     1.1     1.9     2.0     2.0

Total QPS = 18416.6 (92083 / 5.0s)

Misses = 0 (0.0%)

RX   22744501 bytes :    4.3 MB/s
TX    3315024 bytes :    0.6 MB/s

Mutilate reports the latency (average, minimum, and various percentiles) for get and set commands, as well as achieved QPS and network goodput.

To achieve high request rate, you must configure mutilate to use multiple threads, multiple connections, connection pipelining, or remote agents.

$ ./mutilate -s zephyr2-10g -T 24 -c 8
#type       avg     min     1st     5th    10th    90th    95th    99th
read      598.8    86.0   437.2   466.6   482.6   977.0  1075.8  1170.6
update      0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0
op_q        1.5     1.0     1.0     1.1     1.1     1.9     1.9     2.0

Total QPS = 318710.8 (1593559 / 5.0s)

Misses = 0 (0.0%)

RX  393609073 bytes :   75.1 MB/s
TX   57374136 bytes :   10.9 MB/s

Command-line Options

Usage: mutilate -s server[:port] [options]

"High-performance" memcached benchmarking tool

  -h, --help               Print help and exit
      --version            Print version and exit
  -v, --verbose            Verbosity. Repeat for more verbose.
      --quiet              Disable log messages.

Basic options:
  -s, --server=STRING      Memcached server hostname[:port].  Repeat to specify
                             multiple servers.
  -q, --qps=INT            Target aggregate QPS. 0 = peak QPS.  (default=`0')
  -t, --time=INT           Maximum time to run (seconds).  (default=`5')
  -K, --keysize=STRING     Length of memcached keys (distribution).
                             (default=`30')
  -V, --valuesize=STRING   Length of memcached values (distribution).
                             (default=`200')
  -r, --records=INT        Number of memcached records to use.  If multiple
                             memcached servers are given, this number is
                             divided by the number of servers.
                             (default=`10000')
  -u, --update=FLOAT       Ratio of set:get commands.  (default=`0.0')

Advanced options:
  -T, --threads=INT        Number of threads to spawn.  (default=`1')
  -c, --connections=INT    Connections to establish per server.  (default=`1')
  -d, --depth=INT          Maximum depth to pipeline requests.  (default=`1')
  -R, --roundrobin         Assign threads to servers in round-robin fashion.
                             By default, each thread connects to every server.
  -i, --iadist=STRING      Inter-arrival distribution (distribution).  Note:
                             The distribution will automatically be adjusted to
                             match the QPS given by --qps.
                             (default=`exponential')
      --noload             Skip database loading.
      --loadonly           Load database and then exit.
  -B, --blocking           Use blocking epoll().  May increase latency.
  -D, --no_nodelay         Don't use TCP_NODELAY.
  -w, --warmup=INT         Warmup time before starting measurement.
  -W, --wait=INT           Time to wait after startup to start measurement.
  -S, --search=N:X         Search for the QPS where N-order statistic < Xus.
                             (i.e. --search 95:1000 means find the QPS where
                             95% of requests are faster than 1000us).
      --scan=min:max:step  Scan latency across QPS rates from min to max.

Agent-mode options:
  -A, --agentmode          Run client in agent mode.
  -a, --agent=host         Enlist remote agent.
  -l, --lambda_mul=INT     Lambda multiplier.  Increases share of QPS for this
                             client.  (default=`1')

Some options take a 'distribution' as an argument.
Distributions are specified by <distribution>[:<param1>[,...]].
Parameters are not required.  The following distributions are supported:

   [fixed:]<value>              Always generates <value>.
   uniform:<max>                Uniform distribution between 0 and <max>.
   normal:<mean>,<sd>           Normal distribution.
   exponential:<lambda>         Exponential distribution.
   pareto:<loc>,<scale>,<shape> Generalized Pareto distribution.
   gev:<loc>,<scale>,<shape>    Generalized Extreme Value distribution.

   To recreate the Facebook "ETC" request stream from [1], the
   following hard-coded distributions are also provided:

   fb_value   = a hard-coded discrete and GPareto PDF of value sizes
   fb_key     = "gev:30.7984,8.20449,0.078688", key-size distribution
   fb_ia      = "pareto:0.0,16.0292,0.154971", inter-arrival time dist.

[1] Berk Atikoglu et al., Workload Analysis of a Large-Scale Key-Value Store,
    SIGMETRICS 2012