/
riak_perftest.erl
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/
riak_perftest.erl
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%% This file is provided to you under the Apache License,
%% Version 2.0 (the "License"); you may not use this file
%% except in compliance with the License. You may obtain
%% a copy of the License at
%% http://www.apache.org/licenses/LICENSE-2.0
%% Unless required by applicable law or agreed to in writing,
%% software distributed under the License is distributed on an
%% "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
%% KIND, either express or implied. See the License for the
%% specific language governing permissions and limitations
%% under the License.
-module(riak_perftest).
-compile([export_all]).
client_setup(ClientSettings) ->
Defaults = [{fresh_clients, false},
{netlocs, [{"127.0.0.1",9000}]},
{cookie, default_riak_cookie},
{bucket, riak_perftest_bucket},
{object_size, 1000},
{num_unique_objects, 5000},
{num_test_attempts, 1000},
{read_write_ratio, {10,1}}],
NewKeys = proplists:get_keys(ClientSettings),
PrunedDefaults = [{K,V} || {K,V} <- Defaults, not lists:member(K,NewKeys)],
Settings = ClientSettings ++ PrunedDefaults,
% fresh_clients is bool, if true make new client connect each time
% netlocs is list of {IP,Port} to connect with
% cookie is cluster cookie
% object_size is the number of bytes in each object's value
% num_unique_objects is the integer number of independent objects to use
% read_write_ratio is a two-tuple expressing the average # of reads/writes
CGen = client_gen(proplists:get_value(fresh_clients, Settings),
proplists:get_value(netlocs, Settings),
proplists:get_value(cookie, Settings)),
ObjBitSize = 8 * proplists:get_value(object_size, Settings),
ObjValue = <<1:ObjBitSize>>,
Bucket = proplists:get_value(bucket, Settings),
KGen = populate(CGen, Bucket, ObjValue,
proplists:get_value(num_unique_objects, Settings)),
TestAttempts = proplists:get_value(num_test_attempts, Settings),
{R,W} = proplists:get_value(read_write_ratio, Settings),
RWSelector = [read || _ <- lists:seq(1,R)] ++
[write || _ <- lists:seq(1,W)],
{CGen,KGen,ObjValue,RWSelector,TestAttempts}.
perftest({CGen,KGen,ObjValue,RWSelector,TestAttempts}) ->
perftest(CGen,KGen,ObjValue,RWSelector,[],TestAttempts).
perftest(_,_,_,_,Acc,0) -> Acc;
perftest(CGen,KGen,ObjValue,RWSelector,Acc,TestAttempts) ->
{Client,NextCGen} = CGen(),
{{Bucket,Key},NextKGen} = KGen(),
R = 3,
W = 3, % SET THESE ABOVE!
{ReadRes, ReadObj} = case perf_read(Client,Bucket,Key,R) of
{Time, {ok, Obj}} -> {{Time, ok}, Obj};
X -> {X, fail}
end,
Result = case lists:nth(random:uniform(length(RWSelector)),RWSelector) of
read ->
{read, ReadRes};
write ->
case ReadObj of
fail ->
{read, ReadRes};
_ ->
NewObj = riak_object:update_value(ReadObj,ObjValue),
{write, perf_write(Client,NewObj,W)}
end
end,
perftest(NextCGen,NextKGen,ObjValue,RWSelector,
[Result|Acc],TestAttempts-1).
perf_read(Client,Bucket,Key,R) ->
timer:tc(?MODULE, perf_read1, [Client,Bucket,Key,R]).
perf_read1(Client,Bucket,Key,R) -> Client:get(Bucket,Key,R).
%%% NEED TO READ OBJECT FIRST!
perf_write(Client,Obj,W) ->
timer:tc(?MODULE, perf_write1, [Client,Obj,W]).
perf_write1(Client,Obj,W) -> Client:put(Obj,W).
% create an endless thunk producing {Client, ClientGen}
client_gen(FreshClients, NetLocs, Cookie) ->
case FreshClients of
true -> % make a new client every time, can be slower
{IP, Port} = hd(NetLocs),
NextLocs = tl(NetLocs) ++ [hd(NetLocs)],
fun() ->
{ok,C} = riak:client_connect(IP, Port, Cookie),
{C, client_gen(true, NextLocs, Cookie)}
end;
false -> % make the clients up front and re-use
C0 = [riak:client_connect(IP, Port, Cookie) ||
{IP, Port} <- NetLocs],
Clients = [C || {ok,C} <- C0],
client_gen(Clients)
end.
client_gen(Clients) ->
H = hd(Clients),
fun() -> {H, client_gen(tl(Clients) ++ [H])} end.
% put a lot of objects into the perftest_bucket, then return
% an endless thunk of {{Bucket,Key}, KeyGen}
populate(CGen, Bucket, ObjValue, NumUnique) ->
populate(CGen, Bucket, ObjValue, NumUnique, NumUnique).
populate(_,Bucket,_,NumUnique,0) ->
fun() ->
{{Bucket,integer_to_list(NumUnique)},
make_next_keygen(Bucket,NumUnique,NumUnique)}
end;
populate(CGen, Bucket, ObjValue, NumUnique, NumLeft) ->
{Client, NextCGen} = CGen(),
Key = integer_to_list(NumLeft),
Obj = riak_object:new(Bucket,Key,ObjValue),
Client:put(Obj,3),
populate(NextCGen, Bucket, ObjValue, NumUnique, NumLeft-1).
make_next_keygen(Bucket,NumUnique,Prev) ->
Next = case Prev of
1 -> NumUnique;
_ -> Prev - 1
end,
fun() -> {{Bucket,integer_to_list(Next)},
make_next_keygen(Bucket,NumUnique,Next)}
end.
analyze_times(Times) ->
T = lists:sort(Times),
N = length(T),
[Fifty,Ninety,NinetyFive,NinetyNine,NineNineNine] =
[lists:nth(trunc(N * X),T) || X <- [0.5, 0.9, 0.95, 0.99, 0.999]],
{lists:nth(1,T),
trunc(lists:sum(T) / N), Fifty,Ninety,NinetyFive,NinetyNine,NineNineNine,
lists:nth(N,T)}.
% below are various notes, mainly snippets from other storage systems
% people on their benchmarking. obviously to be removed before public
% release.
%% important performance note: goal isn't "simple fast"
%% but goal does include not reducing performance when large in # objects/nodes
%% on testing, vary across:
%% - client against 1 node or spread across all
%% - all-write/all-read/various mixes
%% - object size
%% - number of nodes
%% - number of partitions
%% - storage backend (include nop backend, always 'ok')
%% - R, W, RW settings (rw=0!)
%% measure
%% - req latency (avg, min, max, 50/90/95/99/99.9 percentiles)
%% - requests/sec (just derive from above)
%% http://cliffmoon.tumblr.com/post/128847520/performance-followup-from-nosql
%% I know that if I configure Dynomite to not hit disk and use the native
%% binary term protocol then I can get the throughput up to 20k reqs/s
%% with random reads and writes.
%% http://jan.prima.de/~jan/plok/archives/175-Benchmarks-You-are-Doing-it-Wrong.html
%% Hypertable has failure inducers throughout the code that can be triggered for testing.
%% also hypertable:Doug: Perf on single node: 1 dual core Opteron, 4GB RAM. 31000 inserts/sec in batched mode(?), 500 inserts/sec, 800 random reads/sec #nosql
%% june 11 2009:
%% Cliff: Latency: 10ms avg, 5ms median, 1s at 99.9% #nosql
%% Cliff: Throughput is influenced by Erlang runtime: R12B 2000 req/s; R13B 6500 req/s. No code changes. #nosql
%% Cliff: Used for image serving at Powerset. 12 machines; 6M images + metadata; 2TB of data; 139KB avg size #nosql
%% some couch perf notes:
%% Just passed 4,000,000 documents in CouchDB. I'm excited. It's still fast.
%% Approaching 4 million documents in CouchDB. Handling ~400 writes/s
%% the most I've pulled off on my MacBook was 6k docs/sec but that's
%% direct in Erlang skipping the HTTP and JSON conversion.
%% and dynomite sometime in jan:
%% dynomite avg latency for read/write is under 20ms, median is under
%% 10ms. 99.9 is still high, but that's due to running in virt hosts.
%% dynomite feb 22:
%% buffered write stats: 4ms avg, 2ms median, 98 ms 99.9%
%% JS NOTE: 99.9 is the one that matters!
%% feb 23 on twit:
%% Am seeing Couch's puts taking up to 1.3s (99% level) under load,
%% Dynomite's 99% only hits 200ms under load.
%% feb 24:
%% ~~ while performing 3000 writes [a min] ~ CouchDB's beam process
%% used a total of 7 MB memory~
%% http://till.klampaeckel.de/blog/archives/16-Measuring-CouchDB-performance.html
%% cliff moon:
%% at_kevsmith ops/sec is a silly metric for benchmarks imo. it's easier to
%% manipulate and depends heavily on concurrent load and value size.
%% at_kevsmith latency percentiles are a much better proxy for the relative
%% overhead of your particular system.
%% benblack, twit mar 8
%% nice work! RT at_antirez New Redis benchmark: 100000 writes/sec, 54000
%% reads/sec: http://tinyurl.com/am9nzw
%% at_antirez what happens if you run the tests 100x longer? similar
%% numbers?
%% http://code.google.com/p/redis/wiki/Benchmarks is good!
%% http://wiki.github.com/jpellerin/dynomite/ec2-performance-tests
%% gets: 23502 puts: 23502 collisions: 0
%% get avg: 14.1821250.3ms median: 7.9438690.3ms 99.9: 228.2829280.3ms
%% put avg: 19.9633930.3ms median: 11.6100310.3ms 99.9: 191.6468140.3ms
%% gets:
%% 10% < 1.790ms
%% 20% < 2.918ms
%% 30% < 4.905ms
%% 40% < 6.386ms
%% 50% < 7.941ms
%% 60% < 10.555ms
%% 70% < 13.275ms
%% 80% < 18.824ms
%% 90% < 29.427ms
%% 100% < 3685.608ms
%% puts:
%% 10% < 3.440ms
%% 20% < 4.979ms
%% 30% < 6.438ms
%% 40% < 8.214ms
%% 50% < 11.607ms
%% 60% < 15.936ms
%% 70% < 22.062ms
%% 80% < 31.926ms
%% 90% < 47.970ms
%% 100% < 3778.776ms
%% VPORK
%% Mar 31, 2009 6:21:17 PM - Writes:
%% Mar 31, 2009 6:21:17 PM - Num Writes: 159855
%% Mar 31, 2009 6:21:17 PM - Write Failures: 0
%% Mar 31, 2009 6:21:17 PM - Write Latency: 85.94 ms
%% Mar 31, 2009 6:21:19 PM - Write Latency (%99): 319.00 ms
%% Mar 31, 2009 6:21:19 PM - Bytes Written: 3658.79 MB
%% Mar 31, 2009 6:21:19 PM - Thread w/Throughput: 0.27 KB / ms
%% Mar 31, 2009 6:21:19 PM - Total w/Throughput: 24.29 KB / ms
%% Mar 31, 2009 6:21:19 PM -
%% Mar 31, 2009 6:21:19 PM - Reads:
%% Mar 31, 2009 6:21:19 PM - Num Read: 19872
%% Mar 31, 2009 6:21:19 PM - Read Failures: 0
%% Mar 31, 2009 6:21:19 PM - Read Latency: 70.36 ms
%% Mar 31, 2009 6:21:19 PM - Read Latency (%99): 298.00 ms
%% Mar 31, 2009 6:21:19 PM - Read Not Found: 12 (%0.06)
%% Mar 31, 2009 6:21:19 PM - Bytes Read: 453.94 MB
%% Mar 31, 2009 6:21:19 PM - Thread r/Throughput: 0.33 KB / ms
%% Mar 31, 2009 6:21:19 PM - Total r/Throughput: 3.01 KB / ms