Mutilate is a memcached load generator designed for high request rates, good tail-latency measurements, and realistic request stream generation.
- A C++0x compiler
- scons
- libevent
- gengetopt
- zeromq (optional)
Mutilate has only been thoroughly tested on Ubuntu 11.10. We'll flesh out compatibility over time.
apt-get install scons libevent-dev gengetopt libzmq-dev
scons
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
Real deployments of memcached often handle the requests of dozens, hundreds, or thousands of front-end clients simultaneously. However, by default, mutilate establishes one connection per server and meters requests one at a time (it waits for a reply before sending the next request). This artificially limits throughput (i.e. queries per second), as the round-trip network latency is almost certainly far longer than the time it takes for the memcached server to process one request.
In order to get reasonable benchmark results with mutilate, it needs to be configured to more accurately portray a realistic client workload. In general, this means ensuring that (1) there are a large number of client connections, (2) there is the potential for a large number of outstanding requests, and (3) the memcached server saturates and experiences queuing delay far before mutilate does. I suggest the following guidelines:
- Establish on the order of 100 connections per memcached server thread.
- Don't exceed more than about 16 connections per mutilate thread.
- Use multiple mutilate agents in order to achieve (1) and (2).
- Do not use more mutilate threads than hardware cores/threads.
- Use -Q to configure the "master" agent to take latency samples at slow, a constant rate.
Here's an example:
memcached_server$ memcached -t 4 -c 32768
agent1$ mutilate -T 16 -A
agent2$ mutilate -T 16 -A
agent3$ mutilate -T 16 -A
agent4$ mutilate -T 16 -A
agent5$ mutilate -T 16 -A
agent6$ mutilate -T 16 -A
agent7$ mutilate -T 16 -A
agent8$ mutilate -T 16 -A
master$ mutilate -s memcached_server --loadonly
master$ mutilate -s memcached_server --noload \
-B -T 16 -Q 1000 -D 4 -C 4 \
-a agent1 -a agent2 -a agent3 -a agent4 \
-a agent5 -a agent6 -a agent7 -a agent8 \
-c 4 -q 200000
This will create 8164 = 512 connections total, which is about 128 per memcached server thread. This ought to be enough outstanding requests to cause server-side queuing delay, and no possibility of client-side queuing delay adulterating the latency measurements.
To simulate production environment QPS requests, this repositry add special support for multiple QPS intensities and its Times. After finish one QPS intensity injection, the connection will not be deleted but start next another round QPS injection, which saves the time of pthread barrier wait for multiple threads. Currently Adhoc mode not support Agent mode. For example,
./mutilate -s 172.16.190.84 -c 16 --thread 52 -G 1000000 -G 10000 --adhoc -u 0.5 --save 1.txt
#type avg std min 5th 10th 90th 95th 99th
read 201.3 43.5 28.1 123.1 139.7 249.8 262.2 275.5
update 200.8 43.2 34.0 122.7 139.1 249.5 261.7 275.5
op_q 1.0 0.0 1.0 1.0 1.0 1.1 1.1 1.1
Total QPS = 999757.2 (4998867 / 5.0s)
Misses = 0 (0.0%)
Skipped TXs = 0 (0.0%)
RX 635772262 bytes : 121.3 MB/s
TX 704584410 bytes : 134.4 MB/s
Saving latency samples to 1.txt.
#type avg std min 5th 10th 90th 95th 99th
read 401.6 10479.5 23.2 52.6 64.5 246.6 269.4 3352.8
update 381.4 9340.1 21.1 52.3 64.4 246.1 269.5 3922.0
op_q 1.0 0.0 1.0 1.0 1.0 1.1 1.1 1.1
Total QPS = 10050.6 (50253 / 5.0s)
Misses = 0 (0.0%)
Skipped TXs = 0 (0.0%)
RX 6371826 bytes : 1.2 MB/s
TX 6952086 bytes : 1.3 MB/s
Saving latency samples to 1.txt.
mutilate3 0.1
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.
--binary Use binary memcached protocol instead of ASCII.
-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:
--adhoc Continuous connection under different qps
intensity.
-G, --qps_group=INT Multi QPSs for different workload intensity.
-H, --time_group=INT Multi Times for different workload intensity.
-U, --username=STRING Username to use for SASL authentication.
-P, --password=STRING Password to use for SASL authentication.
-T, --threads=INT Number of threads to spawn. (default=`1')
--affinity Set CPU affinity for threads, round-robin
-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')
-S, --skip Skip transmissions if previous requests are
late. This harms the long-term QPS average,
but reduces spikes in QPS after long latency
requests.
--moderate Enforce a minimum delay of ~1/lambda between
requests.
--noload Skip database loading.
--loadonly Load database and then exit.
-B, --blocking Use blocking epoll(). May increase latency.
--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.
--save=STRING Record latency samples to given file.
--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.
-p, --agent_port=STRING Agent port. (default=`5556')
-l, --lambda_mul=INT Lambda multiplier. Increases share of QPS for
this client. (default=`1')
-C, --measure_connections=INT Master client connections per server, overrides
--connections.
-Q, --measure_qps=INT Explicitly set master client QPS, spread across
threads and connections.
-D, --measure_depth=INT Set master client connection depth.
The --measure_* options aid in taking latency measurements of the
memcached server without incurring significant client-side queuing
delay. --measure_connections allows the master to override the
--connections option. --measure_depth allows the master to operate as
an "open-loop" client while other agents continue as a regular
closed-loop clients. --measure_qps lets you modulate the QPS the
master queries at independent of other clients. This theoretically
normalizes the baseline queuing delay you expect to see across a wide
range of --qps values.
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