D7net
Home
Console
Upload
information
Create File
Create Folder
About
Tools
:
/
opt
/
alt
/
alt-nodejs10
/
root
/
lib
/
node_modules
/
npm
/
html
/
html
/
guides
/
Filename :
writing-and-running-benchmarks.md
back
Copy
# How to Write and Run Benchmarks in Node.js Core ## Table of Contents * [Prerequisites](#prerequisites) * [HTTP Benchmark Requirements](#http-benchmark-requirements) * [Benchmark Analysis Requirements](#benchmark-analysis-requirements) * [Running benchmarks](#running-benchmarks) * [Running individual benchmarks](#running-individual-benchmarks) * [Running all benchmarks](#running-all-benchmarks) * [Comparing Node.js versions](#comparing-nodejs-versions) * [Comparing parameters](#comparing-parameters) * [Running Benchmarks on the CI](#running-benchmarks-on-the-ci) * [Creating a benchmark](#creating-a-benchmark) * [Basics of a benchmark](#basics-of-a-benchmark) * [Creating an HTTP benchmark](#creating-an-http-benchmark) ## Prerequisites Basic Unix tools are required for some benchmarks. [Git for Windows][git-for-windows] includes Git Bash and the necessary tools, which need to be included in the global Windows `PATH`. ### HTTP Benchmark Requirements Most of the HTTP benchmarks require a benchmarker to be installed. This can be either [`wrk`][wrk] or [`autocannon`][autocannon]. `Autocannon` is a Node.js script that can be installed using `npm install -g autocannon`. It will use the Node.js executable that is in the path. In order to compare two HTTP benchmark runs, make sure that the Node.js version in the path is not altered. `wrk` may be available through one of the available package managers. If not, it can be easily built [from source][wrk] via `make`. By default, `wrk` will be used as the benchmarker. If it is not available, `autocannon` will be used in its place. When creating an HTTP benchmark, the benchmarker to be used should be specified by providing it as an argument: `node benchmark/run.js --set benchmarker=autocannon http` `node benchmark/http/simple.js benchmarker=autocannon` #### HTTP/2 Benchmark Requirements To run the `http2` benchmarks, the `h2load` benchmarker must be used. The `h2load` tool is a component of the `nghttp2` project and may be installed from [nghttp2.org][] or built from source. `node benchmark/http2/simple.js benchmarker=autocannon` ### Benchmark Analysis Requirements To analyze the results, `R` should be installed. Use one of the available package managers or download it from https://www.r-project.org/. The R packages `ggplot2` and `plyr` are also used and can be installed using the R REPL. ```R $ R install.packages("ggplot2") install.packages("plyr") ``` In the event that a message is reported stating that a CRAN mirror must be selected first, specify a mirror by adding in the repo parameter. If we used the "http://cran.us.r-project.org" mirror, it could look something like this: ```R install.packages("ggplot2", repo="http://cran.us.r-project.org") ``` Of course, use an appropriate mirror based on location. A list of mirrors is [located here](https://cran.r-project.org/mirrors.html). ## Running benchmarks ### Running individual benchmarks This can be useful for debugging a benchmark or doing a quick performance measure. But it does not provide the statistical information to make any conclusions about the performance. Individual benchmarks can be executed by simply executing the benchmark script with node. ```console $ node benchmark/buffers/buffer-tostring.js buffers/buffer-tostring.js n=10000000 len=0 arg=true: 62710590.393305704 buffers/buffer-tostring.js n=10000000 len=1 arg=true: 9178624.591787899 buffers/buffer-tostring.js n=10000000 len=64 arg=true: 7658962.8891432695 buffers/buffer-tostring.js n=10000000 len=1024 arg=true: 4136904.4060201733 buffers/buffer-tostring.js n=10000000 len=0 arg=false: 22974354.231509723 buffers/buffer-tostring.js n=10000000 len=1 arg=false: 11485945.656765845 buffers/buffer-tostring.js n=10000000 len=64 arg=false: 8718280.70650129 buffers/buffer-tostring.js n=10000000 len=1024 arg=false: 4103857.0726124765 ``` Each line represents a single benchmark with parameters specified as `${variable}=${value}`. Each configuration combination is executed in a separate process. This ensures that benchmark results aren't affected by the execution order due to V8 optimizations. **The last number is the rate of operations measured in ops/sec (higher is better).** Furthermore a subset of the configurations can be specified, by setting them in the process arguments: ```console $ node benchmark/buffers/buffer-tostring.js len=1024 buffers/buffer-tostring.js n=10000000 len=1024 arg=true: 3498295.68561504 buffers/buffer-tostring.js n=10000000 len=1024 arg=false: 3783071.1678948295 ``` ### Running all benchmarks Similar to running individual benchmarks, a group of benchmarks can be executed by using the `run.js` tool. To see how to use this script, run `node benchmark/run.js`. Again this does not provide the statistical information to make any conclusions. ```console $ node benchmark/run.js assert assert/deepequal-buffer.js assert/deepequal-buffer.js method="deepEqual" strict=0 len=100 n=20000: 773,200.4995493788 assert/deepequal-buffer.js method="notDeepEqual" strict=0 len=100 n=20000: 964,411.712953848 ... assert/deepequal-map.js assert/deepequal-map.js method="deepEqual_primitiveOnly" strict=0 len=500 n=500: 20,445.06368453332 assert/deepequal-map.js method="deepEqual_objectOnly" strict=0 len=500 n=500: 1,393.3481642240833 ... assert/deepequal-object.js assert/deepequal-object.js method="deepEqual" strict=0 size=100 n=5000: 1,053.1950937538475 assert/deepequal-object.js method="notDeepEqual" strict=0 size=100 n=5000: 9,734.193251965213 ... ``` It is possible to execute more groups by adding extra process arguments. ```console $ node benchmark/run.js assert async_hooks ``` ### Comparing Node.js versions To compare the effect of a new Node.js version use the `compare.js` tool. This will run each benchmark multiple times, making it possible to calculate statistics on the performance measures. To see how to use this script, run `node benchmark/compare.js`. As an example on how to check for a possible performance improvement, the [#5134](https://github.com/nodejs/node/pull/5134) pull request will be used as an example. This pull request _claims_ to improve the performance of the `string_decoder` module. First build two versions of Node.js, one from the master branch (here called `./node-master`) and another with the pull request applied (here called `./node-pr-5134`). To run multiple compiled versions in parallel you need to copy the output of the build: `cp ./out/Release/node ./node-master`. Check out the following example: ```console $ git checkout master $ ./configure && make -j4 $ cp ./out/Release/node ./node-master $ git checkout pr-5134 $ ./configure && make -j4 $ cp ./out/Release/node ./node-pr-5134 ``` The `compare.js` tool will then produce a csv file with the benchmark results. ```console $ node benchmark/compare.js --old ./node-master --new ./node-pr-5134 string_decoder > compare-pr-5134.csv ``` *Tips: there are some useful options of `benchmark/compare.js`. For example, if you want to compare the benchmark of a single script instead of a whole module, you can use the `--filter` option:* ```console --new ./new-node-binary new node binary (required) --old ./old-node-binary old node binary (required) --runs 30 number of samples --filter pattern string to filter benchmark scripts --set variable=value set benchmark variable (can be repeated) --no-progress don't show benchmark progress indicator ``` For analysing the benchmark results use the `compare.R` tool. ```console $ cat compare-pr-5134.csv | Rscript benchmark/compare.R confidence improvement accuracy (*) (**) (***) string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=128 encoding='ascii' *** -3.76 % ±1.36% ±1.82% ±2.40% string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=128 encoding='utf8' ** -0.81 % ±0.53% ±0.71% ±0.93% string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=32 encoding='ascii' *** -2.70 % ±0.83% ±1.11% ±1.45% string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=32 encoding='base64-ascii' *** -1.57 % ±0.83% ±1.11% ±1.46% ... ``` In the output, _improvement_ is the relative improvement of the new version, hopefully this is positive. _confidence_ tells if there is enough statistical evidence to validate the _improvement_. If there is enough evidence then there will be at least one star (`*`), more stars is just better. **However if there are no stars, then don't make any conclusions based on the _improvement_.** Sometimes this is fine, for example if no improvements are expected, then there shouldn't be any stars. **A word of caution:** Statistics is not a foolproof tool. If a benchmark shows a statistical significant difference, there is a 5% risk that this difference doesn't actually exist. For a single benchmark this is not an issue. But when considering 20 benchmarks it's normal that one of them will show significance, when it shouldn't. A possible solution is to instead consider at least two stars (`**`) as the threshold, in that case the risk is 1%. If three stars (`***`) is considered the risk is 0.1%. However this may require more runs to obtain (can be set with `--runs`). _For the statistically minded, the R script performs an [independent/unpaired 2-group t-test][t-test], with the null hypothesis that the performance is the same for both versions. The confidence field will show a star if the p-value is less than `0.05`._ The `compare.R` tool can also produce a box plot by using the `--plot filename` option. In this case there are 48 different benchmark combinations, and there may be a need to filter the csv file. This can be done while benchmarking using the `--set` parameter (e.g. `--set encoding=ascii`) or by filtering results afterwards using tools such as `sed` or `grep`. In the `sed` case be sure to keep the first line since that contains the header information. ```console $ cat compare-pr-5134.csv | sed '1p;/encoding='"'"ascii"'"'/!d' | Rscript benchmark/compare.R --plot compare-plot.png confidence improvement accuracy (*) (**) (***) string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=128 encoding='ascii' *** -3.76 % ±1.36% ±1.82% ±2.40% string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=32 encoding='ascii' *** -2.70 % ±0.83% ±1.11% ±1.45% string_decoder/string-decoder.js n=2500000 chunkLen=16 inLen=4096 encoding='ascii' *** -4.06 % ±0.31% ±0.41% ±0.54% string_decoder/string-decoder.js n=2500000 chunkLen=256 inLen=1024 encoding='ascii' *** -1.42 % ±0.58% ±0.77% ±1.01% ... ```  ### Comparing parameters It can be useful to compare the performance for different parameters, for example to analyze the time complexity. To do this use the `scatter.js` tool, this will run a benchmark multiple times and generate a csv with the results. To see how to use this script, run `node benchmark/scatter.js`. ```console $ node benchmark/scatter.js benchmark/string_decoder/string-decoder.js > scatter.csv ``` After generating the csv, a comparison table can be created using the `scatter.R` tool. Even more useful it creates an actual scatter plot when using the `--plot filename` option. ```console $ cat scatter.csv | Rscript benchmark/scatter.R --xaxis chunkLen --category encoding --plot scatter-plot.png --log aggregating variable: inLen chunkLen encoding rate confidence.interval 16 ascii 1515855.1 334492.68 16 base64-ascii 403527.2 89677.70 16 base64-utf8 322352.8 70792.93 16 utf16le 1714567.5 388439.81 16 utf8 1100181.6 254141.32 64 ascii 3550402.0 661277.65 64 base64-ascii 1093660.3 229976.34 64 base64-utf8 997804.8 227238.04 64 utf16le 3372234.0 647274.88 64 utf8 1731941.2 360854.04 256 ascii 5033793.9 723354.30 256 base64-ascii 1447962.1 236625.96 256 base64-utf8 1357269.2 231045.70 256 utf16le 4039581.5 655483.16 256 utf8 1828672.9 360311.55 1024 ascii 5677592.7 624771.56 1024 base64-ascii 1494171.7 227302.34 1024 base64-utf8 1399218.9 224584.79 1024 utf16le 4157452.0 630416.28 1024 utf8 1824266.6 359628.52 ``` Because the scatter plot can only show two variables (in this case _chunkLen_ and _encoding_) the rest is aggregated. Sometimes aggregating is a problem, this can be solved by filtering. This can be done while benchmarking using the `--set` parameter (e.g. `--set encoding=ascii`) or by filtering results afterwards using tools such as `sed` or `grep`. In the `sed` case be sure to keep the first line since that contains the header information. ```console $ cat scatter.csv | sed -E '1p;/([^,]+, ){3}128,/!d' | Rscript benchmark/scatter.R --xaxis chunkLen --category encoding --plot scatter-plot.png --log chunkLen encoding rate confidence.interval 16 ascii 1302078.5 71692.27 16 base64-ascii 338669.1 15159.54 16 base64-utf8 281904.2 20326.75 16 utf16le 1381515.5 58533.61 16 utf8 831183.2 33631.01 64 ascii 4363402.8 224030.00 64 base64-ascii 1036825.9 48644.72 64 base64-utf8 780059.3 60994.98 64 utf16le 3900749.5 158366.84 64 utf8 1723710.6 80665.65 256 ascii 8472896.1 511822.51 256 base64-ascii 2215884.6 104347.53 256 base64-utf8 1996230.3 131778.47 256 utf16le 5824147.6 234550.82 256 utf8 2019428.8 100913.36 1024 ascii 8340189.4 598855.08 1024 base64-ascii 2201316.2 111777.68 1024 base64-utf8 2002272.9 128843.11 1024 utf16le 5789281.7 240642.77 1024 utf8 2025551.2 81770.69 ```  ### Running Benchmarks on the CI To see the performance impact of a Pull Request by running benchmarks on the CI, check out [How to: Running core benchmarks on Node.js CI][benchmark-ci]. ## Creating a benchmark ### Basics of a benchmark All benchmarks use the `require('../common.js')` module. This contains the `createBenchmark(main, configs[, options])` method which will setup the benchmark. The arguments of `createBenchmark` are: * `main` {Function} The benchmark function, where the code running operations and controlling timers should go * `configs` {Object} The benchmark parameters. `createBenchmark` will run all possible combinations of these parameters, unless specified otherwise. Each configuration is a property with an array of possible values. Note that the configuration values can only be strings or numbers. * `options` {Object} The benchmark options. At the moment only the `flags` option for specifying command line flags is supported. `createBenchmark` returns a `bench` object, which is used for timing the runtime of the benchmark. Run `bench.start()` after the initialization and `bench.end(n)` when the benchmark is done. `n` is the number of operations performed in the benchmark. The benchmark script will be run twice: The first pass will configure the benchmark with the combination of parameters specified in `configs`, and WILL NOT run the `main` function. In this pass, no flags except the ones directly passed via commands when running the benchmarks will be used. In the second pass, the `main` function will be run, and the process will be launched with: * The flags passed into `createBenchmark` (the third argument) * The flags in the command passed when the benchmark was run Beware that any code outside the `main` function will be run twice in different processes. This could be troublesome if the code outside the `main` function has side effects. In general, prefer putting the code inside the `main` function if it's more than just declaration. ```js 'use strict'; const common = require('../common.js'); const { SlowBuffer } = require('buffer'); const configs = { // Number of operations, specified here so they show up in the report. // Most benchmarks just use one value for all runs. n: [1024], type: ['fast', 'slow'], // Custom configurations size: [16, 128, 1024] // Custom configurations }; const options = { // Add --expose-internals in order to require internal modules in main flags: ['--zero-fill-buffers'] }; // main and configs are required, options is optional. const bench = common.createBenchmark(main, configs, options); // Note that any code outside main will be run twice, // in different processes, with different command line arguments. function main(conf) { // Only flags that have been passed to createBenchmark // earlier when main is run will be in effect. // In order to benchmark the internal modules, require them here. For example: // const URL = require('internal/url').URL // Start the timer bench.start(); // Do operations here const BufferConstructor = conf.type === 'fast' ? Buffer : SlowBuffer; for (let i = 0; i < conf.n; i++) { new BufferConstructor(conf.size); } // End the timer, pass in the number of operations bench.end(conf.n); } ``` ### Creating an HTTP benchmark The `bench` object returned by `createBenchmark` implements `http(options, callback)` method. It can be used to run external tool to benchmark HTTP servers. ```js 'use strict'; const common = require('../common.js'); const bench = common.createBenchmark(main, { kb: [64, 128, 256, 1024], connections: [100, 500] }); function main(conf) { const http = require('http'); const len = conf.kb * 1024; const chunk = Buffer.alloc(len, 'x'); const server = http.createServer((req, res) => { res.end(chunk); }); server.listen(common.PORT, () => { bench.http({ connections: conf.connections, }, () => { server.close(); }); }); } ``` Supported options keys are: * `port` - defaults to `common.PORT` * `path` - defaults to `/` * `connections` - number of concurrent connections to use, defaults to 100 * `duration` - duration of the benchmark in seconds, defaults to 10 * `benchmarker` - benchmarker to use, defaults to `common.default_http_benchmarker` [autocannon]: https://github.com/mcollina/autocannon [wrk]: https://github.com/wg/wrk [t-test]: https://en.wikipedia.org/wiki/Student%27s_t-test#Equal_or_unequal_sample_sizes.2C_unequal_variances [git-for-windows]: http://git-scm.com/download/win [nghttp2.org]: http://nghttp2.org [benchmark-ci]: https://github.com/nodejs/benchmarking/blob/master/docs/core_benchmarks.md