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diff --git a/src/zstd/CONTRIBUTING.md b/src/zstd/CONTRIBUTING.md new file mode 100644 index 000000000..637e37188 --- /dev/null +++ b/src/zstd/CONTRIBUTING.md @@ -0,0 +1,392 @@ +# Contributing to Zstandard +We want to make contributing to this project as easy and transparent as +possible. + +## Our Development Process +New versions are being developed in the "dev" branch, +or in their own feature branch. +When they are deemed ready for a release, they are merged into "master". + +As a consequences, all contributions must stage first through "dev" +or their own feature branch. + +## Pull Requests +We actively welcome your pull requests. + +1. Fork the repo and create your branch from `dev`. +2. If you've added code that should be tested, add tests. +3. If you've changed APIs, update the documentation. +4. Ensure the test suite passes. +5. Make sure your code lints. +6. If you haven't already, complete the Contributor License Agreement ("CLA"). + +## Contributor License Agreement ("CLA") +In order to accept your pull request, we need you to submit a CLA. You only need +to do this once to work on any of Facebook's open source projects. + +Complete your CLA here: <https://code.facebook.com/cla> + +## Workflow +Zstd uses a branch-based workflow for making changes to the codebase. Typically, zstd +will use a new branch per sizable topic. For smaller changes, it is okay to lump multiple +related changes into a branch. + +Our contribution process works in three main stages: +1. Local development + * Update: + * Checkout your fork of zstd if you have not already + ``` + git checkout https://github.com/<username>/zstd + cd zstd + ``` + * Update your local dev branch + ``` + git pull https://github.com/facebook/zstd dev + git push origin dev + ``` + * Topic and development: + * Make a new branch on your fork about the topic you're developing for + ``` + # branch names should be consise but sufficiently informative + git checkout -b <branch-name> + git push origin <branch-name> + ``` + * Make commits and push + ``` + # make some changes = + git add -u && git commit -m <message> + git push origin <branch-name> + ``` + * Note: run local tests to ensure that your changes didn't break existing functionality + * Quick check + ``` + make shortest + ``` + * Longer check + ``` + make test + ``` +2. Code Review and CI tests + * Ensure CI tests pass: + * Before sharing anything to the community, make sure that all CI tests pass on your local fork. + See our section on setting up your CI environment for more information on how to do this. + * Ensure that static analysis passes on your development machine. See the Static Analysis section + below to see how to do this. + * Create a pull request: + * When you are ready to share you changes to the community, create a pull request from your branch + to facebook:dev. You can do this very easily by clicking 'Create Pull Request' on your fork's home + page. + * From there, select the branch where you made changes as your source branch and facebook:dev + as the destination. + * Examine the diff presented between the two branches to make sure there is nothing unexpected. + * Write a good pull request description: + * While there is no strict template that our contributors follow, we would like them to + sufficiently summarize and motivate the changes they are proposing. We recommend all pull requests, + at least indirectly, address the following points. + * Is this pull request important and why? + * Is it addressing an issue? If so, what issue? (provide links for convenience please) + * Is this a new feature? If so, why is it useful and/or necessary? + * Are there background references and documents that reviewers should be aware of to properly assess this change? + * Note: make sure to point out any design and architectural decisions that you made and the rationale behind them. + * Note: if you have been working with a specific user and would like them to review your work, make sure you mention them using (@<username>) + * Submit the pull request and iterate with feedback. +3. Merge and Release + * Getting approval: + * You will have to iterate on your changes with feedback from other collaborators to reach a point + where your pull request can be safely merged. + * To avoid too many comments on style and convention, make sure that you have a + look at our style section below before creating a pull request. + * Eventually, someone from the zstd team will approve your pull request and not long after merge it into + the dev branch. + * Housekeeping: + * Most PRs are linked with one or more Github issues. If this is the case for your PR, make sure + the corresponding issue is mentioned. If your change 'fixes' or completely addresses the + issue at hand, then please indicate this by requesting that an issue be closed by commenting. + * Just because your changes have been merged does not mean the topic or larger issue is complete. Remember + that the change must make it to an official zstd release for it to be meaningful. We recommend + that contributers track the activity on their pull request and corresponding issue(s) page(s) until + their change makes it to the next release of zstd. Users will often discover bugs in your code or + suggest ways to refine and improve your initial changes even after the pull request is merged. + +## Static Analysis +Static analysis is a process for examining the correctness or validity of a program without actually +executing it. It usually helps us find many simple bugs. Zstd uses clang's `scan-build` tool for +static analysis. You can install it by following the instructions for your OS on https://clang-analyzer.llvm.org/scan-build. + +Once installed, you can ensure that our static analysis tests pass on your local development machine +by running: +``` +make staticAnalyze +``` + +In general, you can use `scan-build` to static analyze any build script. For example, to static analyze +just `contrib/largeNbDicts` and nothing else, you can run: + +``` +scan-build make -C contrib/largeNbDicts largeNbDicts +``` + +## Performance +Performance is extremely important for zstd and we only merge pull requests whose performance +landscape and corresponding trade-offs have been adequately analyzed, reproduced, and presented. +This high bar for performance means that every PR which has the potential to +impact performance takes a very long time for us to properly review. That being said, we +always welcome contributions to improve performance (or worsen performance for the trade-off of +something else). Please keep the following in mind before submitting a performance related PR: + +1. Zstd isn't as old as gzip but it has been around for time now and its evolution is +very well documented via past Github issues and pull requests. It may be the case that your +particular performance optimization has already been considered in the past. Please take some +time to search through old issues and pull requests using keywords specific to your +would-be PR. Of course, just because a topic has already been discussed (and perhaps rejected +on some grounds) in the past, doesn't mean it isn't worth bringing up again. But even in that case, +it will be helpful for you to have context from that topic's history before contributing. +2. The distinction between noise and actual performance gains can unfortunately be very subtle +especially when microbenchmarking extremely small wins or losses. The only remedy to getting +something subtle merged is extensive benchmarking. You will be doing us a great favor if you +take the time to run extensive, long-duration, and potentially cross-(os, platform, process, etc) +benchmarks on your end before submitting a PR. Of course, you will not be able to benchmark +your changes on every single processor and os out there (and neither will we) but do that best +you can:) We've adding some things to think about when benchmarking below in the Benchmarking +Performance section which might be helpful for you. +3. Optimizing performance for a certain OS, processor vendor, compiler, or network system is a perfectly +legitimate thing to do as long as it does not harm the overall performance health of Zstd. +This is a hard balance to strike but please keep in mind other aspects of Zstd when +submitting changes that are clang-specific, windows-specific, etc. + +## Benchmarking Performance +Performance microbenchmarking is a tricky subject but also essential for Zstd. We value empirical +testing over theoretical speculation. This guide it not perfect but for most scenarios, it +is a good place to start. + +### Stability +Unfortunately, the most important aspect in being able to benchmark reliably is to have a stable +benchmarking machine. A virtual machine, a machine with shared resources, or your laptop +will typically not be stable enough to obtain reliable benchmark results. If you can get your +hands on a desktop, this is usually a better scenario. + +Of course, benchmarking can be done on non-hyper-stable machines as well. You will just have to +do a little more work to ensure that you are in fact measuring the changes you've made not and +noise. Here are some things you can do to make your benchmarks more stable: + +1. The most simple thing you can do to drastically improve the stability of your benchmark is +to run it multiple times and then aggregate the results of those runs. As a general rule of +thumb, the smaller the change you are trying to measure, the more samples of benchmark runs +you will have to aggregate over to get reliable results. Here are some additional things to keep in +mind when running multiple trials: + * How you aggregate your samples are important. You might be tempted to use the mean of your + results. While this is certainly going to be a more stable number than a raw single sample + benchmark number, you might have more luck by taking the median. The mean is not robust to + outliers whereas the median is. Better still, you could simply take the fastest speed your + benchmark achieved on each run since that is likely the fastest your process will be + capable of running your code. In our experience, this (aggregating by just taking the sample + with the fastest running time) has been the most stable approach. + * The more samples you have, the more stable your benchmarks should be. You can verify + your improved stability by looking at the size of your confidence intervals as you + increase your sample count. These should get smaller and smaller. Eventually hopefully + smaller than the performance win you are expecting. + * Most processors will take some time to get `hot` when running anything. The observations + you collect during that time period will very different from the true performance number. Having + a very large number of sample will help alleviate this problem slightly but you can also + address is directly by simply not including the first `n` iterations of your benchmark in + your aggregations. You can determine `n` by simply looking at the results from each iteration + and then hand picking a good threshold after which the variance in results seems to stabilize. +2. You cannot really get reliable benchmarks if your host machine is simultaneously running +another cpu/memory-intensive application in the background. If you are running benchmarks on your +personal laptop for instance, you should close all applications (including your code editor and +browser) before running your benchmarks. You might also have invisible background applications +running. You can see what these are by looking at either Activity Monitor on Mac or Task Manager +on Windows. You will get more stable benchmark results of you end those processes as well. + * If you have multiple cores, you can even run your benchmark on a reserved core to prevent + pollution from other OS and user processes. There are a number of ways to do this depending + on your OS: + * On linux boxes, you have use https://github.com/lpechacek/cpuset. + * On Windows, you can "Set Processor Affinity" using https://www.thewindowsclub.com/processor-affinity-windows + * On Mac, you can try to use their dedicated affinity API https://developer.apple.com/library/archive/releasenotes/Performance/RN-AffinityAPI/#//apple_ref/doc/uid/TP40006635-CH1-DontLinkElementID_2 +3. To benchmark, you will likely end up writing a separate c/c++ program that will link libzstd. +Dynamically linking your library will introduce some added variation (not a large amount but +definitely some). Statically linking libzstd will be more stable. Static libraries should +be enabled by default when building zstd. +4. Use a profiler with a good high resolution timer. See the section below on profiling for +details on this. +5. Disable frequency scaling, turbo boost and address space randomization (this will vary by OS) +6. Try to avoid storage. On some systems you can use tmpfs. Putting the program, inputs and outputs on +tmpfs avoids touching a real storage system, which can have a pretty big variability. + +Also check our LLVM's guide on benchmarking here: https://llvm.org/docs/Benchmarking.html + +### Zstd benchmark +The fastest signal you can get regarding your performance changes is via the in-build zstd cli +bench option. You can run Zstd as you typically would for your scenario using some set of options +and then additionally also specify the `-b#` option. Doing this will run our benchmarking pipeline +for that options you have just provided. If you want to look at the internals of how this +benchmarking script works, you can check out programs/benchzstd.c + +For example: say you have made a change that you believe improves the speed of zstd level 1. The +very first thing you should use to asses whether you actually achieved any sort of improvement +is `zstd -b`. You might try to do something like this. Note: you can use the `-i` option to +specify a running time for your benchmark in seconds (default is 3 seconds). +Usually, the longer the running time, the more stable your results will be. + +``` +$ git checkout <commit-before-your-change> +$ make && cp zstd zstd-old +$ git checkout <commit-after-your-change> +$ make && cp zstd zstd-new +$ zstd-old -i5 -b1 <your-test-data> + 1<your-test-data> : 8990 -> 3992 (2.252), 302.6 MB/s , 626.4 MB/s +$ zstd-new -i5 -b1 <your-test-data> + 1<your-test-data> : 8990 -> 3992 (2.252), 302.8 MB/s , 628.4 MB/s +``` + +Unless your performance win is large enough to be visible despite the intrinsic noise +on your computer, benchzstd alone will likely not be enough to validate the impact of your +changes. For example, the results of the example above indicate that effectively nothing +changed but there could be a small <3% improvement that the noise on the host machine +obscured. So unless you see a large performance win (10-15% consistently) using just +this method of evaluation will not be sufficient. + +### Profiling +There are a number of great profilers out there. We're going to briefly mention how you can +profile your code using `instruments` on mac, `perf` on linux and `visual studio profiler` +on windows. + +Say you have an idea for a change that you think will provide some good performance gains +for level 1 compression on Zstd. Typically this means, you have identified a section of +code that you think can be made to run faster. + +The first thing you will want to do is make sure that the piece of code is actually taking up +a notable amount of time to run. It is usually not worth optimzing something which accounts for less than +0.0001% of the total running time. Luckily, there are tools to help with this. +Profilers will let you see how much time your code spends inside a particular function. +If your target code snippit is only part of a function, it might be worth trying to +isolate that snippit by moving it to its own function (this is usually not necessary but +might be). + +Most profilers (including the profilers dicusssed below) will generate a call graph of +functions for you. Your goal will be to find your function of interest in this call grapch +and then inspect the time spent inside of it. You might also want to to look at the +annotated assembly which most profilers will provide you with. + +#### Instruments +We will once again consider the scenario where you think you've identified a piece of code +whose performance can be improved upon. Follow these steps to profile your code using +Instruments. + +1. Open Instruments +2. Select `Time Profiler` from the list of standard templates +3. Close all other applications except for your instruments window and your terminal +4. Run your benchmarking script from your terminal window + * You will want a benchmark that runs for at least a few seconds (5 seconds will + usually be long enough). This way the profiler will have something to work with + and you will have ample time to attach your profiler to this process:) + * I will just use benchzstd as my bencharmking script for this example: +``` +$ zstd -b1 -i5 <my-data> # this will run for 5 seconds +``` +5. Once you run your benchmarking script, switch back over to instruments and attach your +process to the time profiler. You can do this by: + * Clicking on the `All Processes` drop down in the top left of the toolbar. + * Selecting your process from the dropdown. In my case, it is just going to be labled + `zstd` + * Hitting the bright red record circle button on the top left of the toolbar +6. You profiler will now start collecting metrics from your bencharking script. Once +you think you have collected enough samples (usually this is the case after 3 seconds of +recording), stop your profiler. +7. Make sure that in toolbar of the bottom window, `profile` is selected. +8. You should be able to see your call graph. + * If you don't see the call graph or an incomplete call graph, make sure you have compiled + zstd and your benchmarking scripg using debug flags. On mac and linux, this just means + you will have to supply the `-g` flag alone with your build script. You might also + have to provide the `-fno-omit-frame-pointer` flag +9. Dig down the graph to find your function call and then inspect it by double clicking +the list item. You will be able to see the annotated source code and the assembly side by +side. + +#### Perf + +This wiki has a pretty detailed tutorial on getting started working with perf so we'll +leave you to check that out of you're getting started: + +https://perf.wiki.kernel.org/index.php/Tutorial + +Some general notes on perf: +* Use `perf stat -r # <bench-program>` to quickly get some relevant timing and +counter statistics. Perf uses a high resolution timer and this is likely one +of the first things your team will run when assessing your PR. +* Perf has a long list of hardware counters that can be viewed with `perf --list`. +When measuring optimizations, something worth trying is to make sure the handware +counters you expect to be impacted by your change are in fact being so. For example, +if you expect the L1 cache misses to decrease with your change, you can look at the +counter `L1-dcache-load-misses` +* Perf hardware counters will not work on a virtual machine. + +#### Visual Studio + +TODO + + +## Setting up continuous integration (CI) on your fork +Zstd uses a number of different continuous integration (CI) tools to ensure that new changes +are well tested before they make it to an official release. Specifically, we use the platforms +travis-ci, circle-ci, and appveyor. + +Changes cannot be merged into the main dev branch unless they pass all of our CI tests. +The easiest way to run these CI tests on your own before submitting a PR to our dev branch +is to configure your personal fork of zstd with each of the CI platforms. Below, you'll find +instructions for doing this. + +### travis-ci +Follow these steps to link travis-ci with your github fork of zstd + +1. Make sure you are logged into your github account +2. Go to https://travis-ci.org/ +3. Click 'Sign in with Github' on the top right +4. Click 'Authorize travis-ci' +5. Click 'Activate all repositories using Github Apps' +6. Select 'Only select repositories' and select your fork of zstd from the drop down +7. Click 'Approve and Install' +8. Click 'Sign in with Github' again. This time, it will be for travis-pro (which will let you view your tests on the web dashboard) +9. Click 'Authorize travis-pro' +10. You should have travis set up on your fork now. + +### circle-ci +TODO + +### appveyor +Follow these steps to link circle-ci with your girhub fork of zstd + +1. Make sure you are logged into your github account +2. Go to https://www.appveyor.com/ +3. Click 'Sign in' on the top right +4. Select 'Github' on the left panel +5. Click 'Authorize appveyor' +6. You might be asked to select which repositories you want to give appveyor permission to. Select your fork of zstd if you're prompted +7. You should have appveyor set up on your fork now. + +### General notes on CI +CI tests run every time a pull request (PR) is created or updated. The exact tests +that get run will depend on the destination branch you specify. Some tests take +longer to run than others. Currently, our CI is set up to run a short +series of tests when creating a PR to the dev branch and a longer series of tests +when creating a PR to the master branch. You can look in the configuration files +of the respective CI platform for more information on what gets run when. + +Most people will just want to create a PR with the destination set to their local dev +branch of zstd. You can then find the status of the tests on the PR's page. You can also +re-run tests and cancel running tests from the PR page or from the respective CI's dashboard. + +## Issues +We use GitHub issues to track public bugs. Please ensure your description is +clear and has sufficient instructions to be able to reproduce the issue. + +Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe +disclosure of security bugs. In those cases, please go through the process +outlined on that page and do not file a public issue. + +## Coding Style +* 4 spaces for indentation rather than tabs + +## License +By contributing to Zstandard, you agree that your contributions will be licensed +under both the [LICENSE](LICENSE) file and the [COPYING](COPYING) file in the root directory of this source tree. |