/memcache-perf

Load generator for memcached (multi threaded, multi machine)

Primary LanguageC++BSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

Memcache-perf

Memcache-perf 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. libevent2 (get headers and install build-dev for memcached for rest)
  3. zeromq

Tested on ubuntu 14.04,16.04,18.04 x86 64b and ARMv8.

Building

apt-get install libevent-dev libzmq3-dev
apt-get build-dep memcached
make

Basic Usage

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

$ ./mcperf -s localhost
#type       avg     std     min      p5     p10     p50     p67     p75     p80     p85     p90     p95     p99    p999   p9999
read       62.2    24.1    54.7    59.1    59.4    61.5    62.3    62.8    63.0    63.3    63.5    63.8    68.8    80.2  1012.5
update      0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0
op_q        1.0     0.0     1.0     1.0     1.0     1.0     1.1     1.1     1.1     1.1     1.1     1.1     1.1     1.1     1.1

Total QPS = 16082.2 (80411 / 5.0s)

Misses = 0 (0.0%)
Skipped TXs = 0 (0.0%)

RX   19861517 bytes :    3.8 MB/s
TX    2894832 bytes :    0.6 MB/s
CPU Usage Stats (avg/min/max): 2.21%,0.38%,4.05%

mcperf reports the latency (average, minimum, and various percentiles) for get and set commands, as well as achieved QPS and network goodput. A separate thread is also keeping track of client CPU usage on the master. A warning will be issued if the master client CPU usage goes above 95%. In that case, it is recommended to add more machines as agents. If verbose (-v) flag is enabled on the an agent, it will report it's cpu usage as well.

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

$ ./mcperf -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

Suggested Usage

Real deployments of memcached often handle the requests of dozens, hundreds, or thousands of front-end clients simultaneously. However, by default, mcperf 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 mcperf, 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 mcperf does. I suggest the following guidelines:

  1. Establish more than 50 connections per memcached server thread.
  2. Don't exceed more than about 10 connections per mcperf thread.
  3. Use multiple mcperf agents in order to achieve (1) and (2).
  4. Do not use more mcperf threads than hardware cores/threads.

Here's an example:

memcached_server$ memcached -t 4 -c 32768
agent1$ mcperf -T 16 -A
agent2$ mcperf -T 16 -A
agent3$ mcperf -T 16 -A
agent4$ mcperf -T 16 -A
agent5$ mcperf -T 16 -A
agent6$ mcperf -T 16 -A
agent7$ mcperf -T 16 -A
agent8$ mcperf -T 16 -A
master$ mcperf -s memcached_server --loadonly
master$ mcperf -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 8*16*4 = 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.

Command-line Options

mcperf 0.2

Usage: mcperf -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:
  -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


mcperf 0.3

Usage: mcperf -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[-end_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')
	  --profile=INT             Select one of several predefined profiles.
  -K, --keysize=STRING          Length of memcached keys (distribution).
								  (default=`30')
	  --keyorder=STRING         Selection of memcached keys to use
								  (distribution).  (default=`none')
  -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:
  -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.
  -e, --trace                   To enable server tracing based on client
								  activity, will issue special
								  start_trace/stop_trace commands. Requires
								  memcached to support these commands.
  -G, --getq_size=INT           Size of queue for multiget requests.
								  (default=`100')
  -g, --getq_freq=FLOAT         Frequency of multiget requests, 0 for no
								  multi-get, 100 for only multi-get.
								  (default=`0.0')
	  --keycache_capacity=INT   Cached key capacity. (default 10000)
								  (default=`10000')
	  --keycache_reuse=INT      Number of times to reuse key cache before
								  generating new req sequence. (Default 100)
								  (default=`100')
	  --keycache_regen=INT      When regenerating control number of requests to
								  regenerate. (Default 1%)  (default=`1')
	  --plot_all                Create plot/csv of latency histogram at each
								  step when using gnuplot and loghistogram
								  sampler

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.
  -m, --poll_freq=INT           Set frequency in seconds for agent protocol
								  recv polling.  (default=`1')
  -M, --poll_max=INT            Set timeout for agent protocol recv polling. An
								  agent not responding within time limit will
								  be dropped.  (default=`120')

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.

Predefined profiles to approximate some use cases:
1. memcached for web serving benchmark : p95, 20ms, FB key/value/IA, >4000
connections to the device under test.
2. memcached for applications backends : p99, 10ms, 32B key , 1000B value,
uniform IA,  >1000 connections
3. memcached for low latency (e.g. stock trading): p99.9, 32B key, 200B value,
uniform IA, QPS rate set to 100000	
4. P99.9, 1 msec. Key size = 32 bytes; value size has uniform distribution from
100 bytes to 1k; 

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