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Contributing to Cockroach

Getting and Building

  1. Install the following prerequisites, as necessary:
  • A C++ compiler that supports C++11. Note that GCC prior to 6.0 doesn't work due to https://gcc.gnu.org/bugzilla/show_bug.cgi?id=48891
  • A Go environment with a recent 64-bit version of the toolchain. Note that the Makefile enforces the specific version required, as it is updated frequently.
  • Git 1.8+
  • Bash (4+ is preferred)
  • GNU Make (3.81+ is known to work)
  • CMake 2.8.12+
  • XZ Utils (5.2.3+ is known to work), except on macOS, where xz support is built in to tar.
  • Optional: NodeJS 6.x and Yarn 0.22.0+. Required when compiling protocol buffers.

Note that at least 4GB of RAM is required to build from source and run tests.

  1. Get the CockroachDB code:

    go get -d github.com/cockroachdb/cockroach
cd $GOPATH/src/github.com/cockroachdb/cockroach

  2. Run make build, make test, or anything else our Makefile offers. Note that the first time you run make, it can take some time to download and install various dependencies. After running make build, the cockroach executable will be in your current directory and can be run as shown in the README.

Other Considerations

  • The default binary contains core open-source functionally covered by the Apache License 2 (APL2) and enterprise functionality covered by the CockroachDB Community License (CCL). To build a pure open-source (APL2) version excluding enterprise functionality, use make buildoss. See this blog post for more details.

  • If you edit a .proto or .ts file, you will need to manually regenerate the associated .pb.{go,cc,h} or .js files using make generate.

  • We advise to run make generate using our embedded Docker setup. build/builder.sh is a wrapper script designed to make this convenient. You can run build/builder.sh make generate from the repository root to get the intended result.

  • If you plan on working on the UI, check out the UI README.

  • To add or update a Go dependency:

    • See build/README.md for details on adding or updating dependencies.
    • Run make generate to update generated files.
    • Create a PR with all the changes.

Style Guide

Style Guide

Code Review Workflow

  • All contributors need to sign the Contributor License Agreement.

  • Create a local feature branch to do work on, ideally on one thing at a time. If you are working on your own fork, see this tip on forking in Go, which ensures that Go import paths will be correct.

    git checkout -b update-readme

  • Hack away and commit your changes locally using git add and git commit. Remember to write tests! The following are helpful for running specific subsets of tests:

    make test
# Run all tests in ./pkg/storage
make test PKG=./pkg/storage
# Run all kv tests matching '^TestFoo' with a timeout of 10s
make test PKG=./pkg/kv TESTS='^TestFoo' TESTTIMEOUT=10s
# Run the sql logic tests
make test PKG=./pkg/sql TESTS='TestLogic$$'
# or, using a shortcut,
make testlogic
# Run a specific sql logic subtest
make test PKG=./pkg/sql TESTS='TestLogic$$/select$$'
# or, using a shortcut,
make testlogic FILES=select

    Logs are disabled during tests by default. To enable them, include TESTFLAGS="-v -show-logs" as an argument the test command:

    make test ... TESTFLAGS="-v -show-logs"

    When you're ready to commit, be sure to write a Good Commit Message™. Consult https://github.com/erlang/otp/wiki/Writing-good-commit-messages if you're not sure what constitutes a Good Commit Message™. In addition to the general rules referenced above, please also prefix your commit subject line with the affected package, if one can easily be chosen. For example, the subject line of a commit mostly affecting the server/serverpb package might read: "server/serverpb: made great again". Commits which affect many packages as a result of a shared dependency change should probably begin their subjects with the name of the shared dependency. Finally, some commits may need to affect many packages in a way which does not point to a specific package; those commits may begin with "*:" or "all:" to indicate their reach.

  • Run the linters, code generators, and unit test suites locally:

    make pre-push

    This will take several minutes.

  • When you’re ready for review, groom your work: each commit should pass tests and contain a substantial (but not overwhelming) unit of work. You may also want to git fetch origin and run git rebase -i --exec "make lint test" origin/master to make sure you're submitting your changes on top of the newest version of our code. Next, push to your fork:

    git push -u <yourfork> update-readme

  • Then create a pull request using GitHub’s UI. If you know of another GitHub user particularly suited to reviewing your pull request, be sure to mention them in the pull request body. If you possess the necessary GitHub privileges, please also assign them to the pull request using GitHub's UI. This will help focus and expedite the code review process.

  • If you get a test failure in CircleCI, check the Test Failure tab to see why the test failed. When the failure is logged in excerpt.txt, you can find the file from the Artifacts tab and see log messages. (You need to sign in to see the Artifacts tab.)

  • Address feedback by amending your commits. If your change contains multiple commits, address each piece of feedback by amending that commit to which the particular feedback is aimed. Wait (or ask) for new feedback on those commits if they are not straightforward. An LGTM ("looks good to me") by someone qualified is usually posted when you're free to go ahead and merge. Most new contributors aren't allowed to merge themselves; in that case, we'll do it for you.

Debugging

Peeking into a running cluster can be done in several ways:

  • the net/trace endpoint at /debug/requests. It has a breakdown of the recent traced requests, in particularly slow ones. Two families are traced: node and coord, the former (and likely more interesting one) containing what happens inside of Node/Store/Replica and the other inside of the coordinator (TxnCoordSender).
  • pprof gives us (among other things) heap and cpu profiles; this golang blog post explains it extremely well and this one by Dmitry Vuykov goes into even more detail.

An easy way to locally run a workload against a cluster are the acceptance tests. For example,

make acceptance TESTS='TestPut$$' TESTFLAGS='-v -d 1200s -l .' TESTTIMEOUT=1210s

runs the Put acceptance test for 20 minutes with logging (useful to look at the stack trace in case of a node dying). When it starts, all the relevant commands for pprof, trace and logs are logged to allow for convenient inspection of the cluster.