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Contributing to elasticsearch

Elasticsearch is an open source project and we love to receive contributions from our community — you! There are many ways to contribute, from writing tutorials or blog posts, improving the documentation, submitting bug reports and feature requests or writing code which can be incorporated into Elasticsearch itself.

If you want to be rewarded for your contributions, sign up for the Elastic Contributor Program. Each time you make a valid contribution, you’ll earn points that increase your chances of winning prizes and being recognized as a top contributor.

Bug reports

If you think you have found a bug in Elasticsearch, first make sure that you are testing against the latest version of Elasticsearch - your issue may already have been fixed. If not, search our issues list on GitHub in case a similar issue has already been opened.

It is very helpful if you can prepare a reproduction of the bug. In other words, provide a small test case which we can run to confirm your bug. It makes it easier to find the problem and to fix it. Test cases should be provided as curl commands which we can copy and paste into a terminal to run it locally, for example:

# delete the index
curl -XDELETE localhost:9200/test

# insert a document
curl -XPUT localhost:9200/test/test/1 -d '{
 "title": "test document"
}'

# this should return XXXX but instead returns YYY
curl ....

Provide as much information as you can. You may think that the problem lies with your query, when actually it depends on how your data is indexed. The easier it is for us to recreate your problem, the faster it is likely to be fixed.

Feature requests

If you find yourself wishing for a feature that doesn't exist in Elasticsearch, you are probably not alone. There are bound to be others out there with similar needs. Many of the features that Elasticsearch has today have been added because our users saw the need. Open an issue on our issues list on GitHub which describes the feature you would like to see, why you need it, and how it should work.

Contributing code and documentation changes

If you would like to contribute a new feature or a bug fix to Elasticsearch, please discuss your idea first on the Github issue. If there is no Github issue for your idea, please open one. It may be that somebody is already working on it, or that there are particular complexities that you should know about before starting the implementation. There are often a number of ways to fix a problem and it is important to find the right approach before spending time on a PR that cannot be merged.

We add the help wanted label to existing Github issues for which community contributions are particularly welcome, and we use the good first issue label to mark issues that we think will be suitable for new contributors.

The process for contributing to any of the Elastic repositories is similar. Details for individual projects can be found below.

Fork and clone the repository

You will need to fork the main Elasticsearch code or documentation repository and clone it to your local machine. See github help page for help.

Further instructions for specific projects are given below.

Submitting your changes

Once your changes and tests are ready to submit for review:

Test your changes

Run the test suite to make sure that nothing is broken. See the TESTING file for help running tests.
Sign the Contributor License Agreement

Please make sure you have signed our Contributor License Agreement. We are not asking you to assign copyright to us, but to give us the right to distribute your code without restriction. We ask this of all contributors in order to assure our users of the origin and continuing existence of the code. You only need to sign the CLA once.
Rebase your changes

Update your local repository with the most recent code from the main Elasticsearch repository, and rebase your branch on top of the latest master branch. We prefer your initial changes to be squashed into a single commit. Later, if we ask you to make changes, add them as separate commits. This makes them easier to review. As a final step before merging we will either ask you to squash all commits yourself or we'll do it for you.
Submit a pull request

Push your local changes to your forked copy of the repository and submit a pull request. In the pull request, choose a title which sums up the changes that you have made, and in the body provide more details about what your changes do. Also mention the number of the issue where discussion has taken place, eg "Closes #123".

Then sit back and wait. There will probably be discussion about the pull request and, if any changes are needed, we would love to work with you to get your pull request merged into Elasticsearch.

Please adhere to the general guideline that you should never force push to a publicly shared branch. Once you have opened your pull request, you should consider your branch publicly shared. Instead of force pushing you can just add incremental commits; this is generally easier on your reviewers. If you need to pick up changes from master, you can merge master into your branch. A reviewer might ask you to rebase a long-running pull request in which case force pushing is okay for that request. Note that squashing at the end of the review process should also not be done, that can be done when the pull request is integrated via GitHub.

Contributing to the Elasticsearch codebase

Repository: https://github.com/elastic/elasticsearch

JDK 14 is required to build Elasticsearch. You must have a JDK 14 installation with the environment variable JAVA_HOME referencing the path to Java home for your JDK 14 installation. By default, tests use the same runtime as JAVA_HOME. However, since Elasticsearch supports JDK 8, the build supports compiling with JDK 14 and testing on a JDK 8 runtime; to do this, set RUNTIME_JAVA_HOME pointing to the Java home of a JDK 8 installation. Note that this mechanism can be used to test against other JDKs as well, this is not only limited to JDK 8.

Note: It is also required to have JAVA8_HOME, JAVA9_HOME, JAVA10_HOME and JAVA11_HOME, and JAVA12_HOME available so that the tests can pass.

Elasticsearch uses the Gradle wrapper for its build. You can execute Gradle using the wrapper via the gradlew script on Unix systems or gradlew.bat script on Windows in the root of the repository. The examples below show the usage on Unix.

We support development in IntelliJ versions IntelliJ 2019.2 and onwards. We would like to support Eclipse, but few of us use it and has fallen into disrepair.

Docker is required for building some Elasticsearch artifacts and executing certain test suites. You can run Elasticsearch without building all the artifacts with:

./gradlew :run

That'll spend a while building Elasticsearch and then it'll start Elasticsearch, writing its log above Gradle's status message. We log a lot of stuff on startup, specifically these lines tell you that Elasticsearch is ready:

[2020-05-29T14:50:35,167][INFO ][o.e.h.AbstractHttpServerTransport] [runTask-0] publish_address {127.0.0.1:9200}, bound_addresses {[::1]:9200}, {127.0.0.1:9200}
[2020-05-29T14:50:35,169][INFO ][o.e.n.Node               ] [runTask-0] started

But to be honest its typically easier to wait until the console stops scrolling and then run curl in another window like this:

curl -u elastic:password localhost:9200

Importing the project into IntelliJ IDEA

Elasticsearch builds using Java 14. When importing into IntelliJ you will need to define an appropriate SDK. The convention is that this SDK should be named "14" so that the project import will detect it automatically. For more details on defining an SDK in IntelliJ please refer to their documentation. SDK definitions are global, so you can add the JDK from any project, or after project import. Importing with a missing JDK will still work, IntelliJ will simply report a problem and will refuse to build until resolved.

You can import the Elasticsearch project into IntelliJ IDEA via:

Select File > Open
In the subsequent dialog navigate to the root build.gradle file
In the subsequent dialog select Open as Project

Java Language Formatting Guidelines

Java files in the Elasticsearch codebase are formatted with the Eclipse JDT formatter, using the Spotless Gradle plugin. This plugin is configured on a project-by-project basis, via build.gradle in the root of the repository. So long as at least one project is configured, the formatting check can be run explicitly with:

./gradlew spotlessJavaCheck

The code can be formatted with:

./gradlew spotlessApply

These tasks can also be run for specific subprojects, e.g.

./gradlew server:spotlessJavaCheck

Please follow these formatting guidelines:

Java indent is 4 spaces
Line width is 140 characters
Lines of code surrounded by // tag::NAME and // end::NAME comments are included in the documentation and should only be 76 characters wide not counting leading indentation. Such regions of code are not formatted automatically as it is not possible to change the line length rule of the formatter for part of a file. Please format such sections sympathetically with the rest of the code, while keeping lines to maximum length of 76 characters.
Wildcard imports (import foo.bar.baz.*) are forbidden and will cause the build to fail.
If absolutely necessary, you can disable formatting for regions of code with the // tag::NAME and // end::NAME directives, but note that these are intended for use in documentation, so please make it clear what you have done, and only do this where the benefit clearly outweighs the decrease in consistency.
Note that JavaDoc and block comments i.e. /* ... */ are not formatted, but line comments i.e // ... are.
There is an implicit rule that negative boolean expressions should use the form foo == false instead of !foo for better readability of the code. While this isn't strictly enforced, if might get called out in PR reviews as something to change.

Editor / IDE Support

Eclipse IDEs can import the file [elasticsearch.eclipseformat.xml] directly.

IntelliJ IDEs can import the same settings file, and / or use the Eclipse Code Formatter plugin.

You can also tell Spotless to format a specific file from the command line.

Formatting failures

Sometimes Spotless will report a "misbehaving rule which can't make up its mind" and will recommend enabling the paddedCell() setting. If you enabled this settings and run the format check again, Spotless will write files to $PROJECT/build/spotless-diagnose-java/ to aid diagnosis. It writes different copies of the formatted files, so that you can see how they differ and infer what is the problem.

The paddedCell() option is disabled for normal operation in order to detect any misbehaviour. You can enabled the option from the command line by running Gradle with -Dspotless.paddedcell.

NOTE: If you have imported the project into IntelliJ IDEA the project will be automatically configured to add the correct license header to new source files based on the source location.

Creating A Distribution

Run all build commands from within the root directory:

cd elasticsearch/

To build a darwin-tar distribution, run this command:

./gradlew -p distribution/archives/darwin-tar assemble

You will find the distribution under: ./distribution/archives/darwin-tar/build/distributions/

To create all build artifacts (e.g., plugins and Javadocs) as well as distributions in all formats, run this command:

./gradlew assemble

NOTE: Running the task above will fail if you don't have a available Docker installation.

The package distributions (Debian and RPM) can be found under: ./distribution/packages/(deb|rpm|oss-deb|oss-rpm)/build/distributions/

Running The Full Test Suite

Before submitting your changes, run the test suite to make sure that nothing is broken, with:

./gradlew check

If your changes affect only the documentation, run:

./gradlew -p docs check

For more information about testing code examples in the documentation, see https://github.com/elastic/elasticsearch/blob/master/docs/README.asciidoc

Project layout

This repository is split into many top level directories. The most important ones are:

`docs`

Documentation for the project.

`distribution`

Builds our tar and zip archives and our rpm and deb packages.

`libs`

Libraries used to build other parts of the project. These are meant to be internal rather than general purpose. We have no plans to semver their APIs or accept feature requests for them. We publish them to maven central because they are dependencies of our plugin test framework, high level rest client, and jdbc driver but they really aren't general purpose enough to belong in maven central. We're still working out what to do here.

`modules`

Features that are shipped with Elasticsearch by default but are not built in to the server. We typically separate features from the server because they require permissions that we don't believe all of Elasticsearch should have or because they depend on libraries that we don't believe all of Elasticsearch should depend on.

For example, reindex requires the connect permission so it can perform reindex-from-remote but we don't believe that the all of Elasticsearch should have the "connect". For another example, Painless is implemented using antlr4 and asm and we don't believe that all of Elasticsearch should have access to them.

`plugins`

Officially supported plugins to Elasticsearch. We decide that a feature should be a plugin rather than shipped as a module because we feel that it is only important to a subset of users, especially if it requires extra dependencies.

The canonical example of this is the ICU analysis plugin. It is important for folks who want the fairly language neutral ICU analyzer but the library to implement the analyzer is 11MB so we don't ship it with Elasticsearch by default.

Another example is the discovery-gce plugin. It is vital to folks running in GCP but useless otherwise and it depends on a dozen extra jars.

`qa`

Honestly this is kind of in flux and we're not 100% sure where we'll end up. Right now the directory contains

Tests that require multiple modules or plugins to work
Tests that form a cluster made up of multiple versions of Elasticsearch like full cluster restart, rolling restarts, and mixed version tests
Tests that test the Elasticsearch clients in "interesting" places like the wildfly project.
Tests that test Elasticsearch in funny configurations like with ingest disabled
Tests that need to do strange things like install plugins that thrown uncaught Throwables or add a shutdown hook But we're not convinced that all of these things belong in the qa directory. We're fairly sure that tests that require multiple modules or plugins to work should just pick a "home" plugin. We're fairly sure that the multi-version tests do belong in qa. Beyond that, we're not sure. If you want to add a new qa project, open a PR and be ready to discuss options.

`server`

The server component of Elasticsearch that contains all of the modules and plugins. Right now things like the high level rest client depend on the server but we'd like to fix that in the future.

`test`

Our test framework and test fixtures. We use the test framework for testing the server, the plugins, and modules, and pretty much everything else. We publish the test framework so folks who develop Elasticsearch plugins can use it to test the plugins. The test fixtures are external processes that we start before running specific tests that rely on them.

For example, we have an hdfs test that uses mini-hdfs to test our repository-hdfs plugin.

Gradle Build

We use Gradle to build Elasticsearch because it is flexible enough to not only build and package Elasticsearch, but also orchestrate all of the ways that we have to test Elasticsearch.

Configurations

Gradle organizes dependencies and build artifacts into "configurations" and allows you to use these configurations arbitrarily. Here are some of the most common configurations in our build and how we use them:

`implementation`: Dependencies that are used by the project at compile and runtime but are not exposed as a compile dependency to other dependent projects. Dependencies added to the `implementation` configuration are considered an implementation detail that can be changed at a later date without affecting any dependent projects.
`api`: Dependencies that are used as compile and runtime dependencies of a project and are considered part of the external api of the project.
`runtimeOnly`: Dependencies that not on the classpath at compile time but are on the classpath at runtime. We mostly use this configuration to make sure that we do not accidentally compile against dependencies of our dependencies also known as "transitive" dependencies".
`compileOnly`: Code that is on the classpath at compile time but that should not be shipped with the project because it is "provided" by the runtime somehow. Elasticsearch plugins use this configuration to include dependencies that are bundled with Elasticsearch's server.
`testImplementation`: Code that is on the classpath for compiling tests that are part of this project but not production code. The canonical example of this is `junit`.

Reviewing and accepting your contribution

We review every contribution carefully to ensure that the change is of high quality and fits well with the rest of the Elasticsearch codebase. If accepted, we will merge your change and usually take care of backporting it to appropriate branches ourselves.

We really appreciate everyone who is interested in contributing to Elasticsearch and regret that we sometimes have to reject contributions even when they might appear to make genuine improvements to the system. Reviewing contributions can be a very time-consuming task, yet the team is small and our time is very limited. In some cases the time we would need to spend on reviews would outweigh the benefits of a change by preventing us from working on other more beneficial changes instead.

Please discuss your change in a Github issue before spending much time on its implementation. We sometimes have to reject contributions that duplicate other efforts, take the wrong approach to solving a problem, or solve a problem which does not need solving. An up-front discussion often saves a good deal of wasted time in these cases.

We normally immediately reject isolated PRs that only perform simple refactorings or otherwise "tidy up" certain aspects of the code. We think the benefits of this kind of change are very small, and in our experience it is not worth investing the substantial effort needed to review them. This especially includes changes suggested by tools.

We sometimes reject contributions due to the low quality of the submission since low-quality submissions tend to take unreasonable effort to review properly. Quality is rather subjective so it is hard to describe exactly how to avoid this, but there are some basic steps you can take to reduce the chances of rejection. Follow the guidelines listed above when preparing your changes. You should add tests that correspond with your changes, and your PR should pass affected test suites too. It makes it much easier to review if your code is formatted correctly and does not include unnecessary extra changes.

We sometimes reject contributions if we find ourselves performing many review iterations without making enough progress. Some iteration is expected, particularly on technically complicated changes, and there's no fixed limit on the acceptable number of review cycles since it depends so much on the nature of the change. You can help to reduce the number of iterations by reviewing your contribution yourself or in your own team before asking us for a review. You may be surprised how many comments you can anticipate and address by taking a short break and then carefully looking over your changes again.

We expect you to follow up on review comments somewhat promptly, but recognise that everyone has many priorities for their time and may not be able to respond for several days. We will understand if you find yourself without the time to complete your contribution, but please let us know that you have stopped working on it. We will try to send you a reminder if we haven't heard from you in a while, but may end up closing your PR if you do not respond for too long.

If your contribution is rejected we will close the pull request with a comment explaining why. This decision isn't always final: if you feel we have misunderstood your intended change or otherwise think that we should reconsider then please continue the conversation with a comment on the pull request and we'll do our best to address any further points you raise.

Contributing as part of a class

In general Elasticsearch is happy to accept contributions that were created as part of a class but strongly advise against making the contribution as part of the class. So if you have code you wrote for a class feel free to submit it.

Please, please, please do not assign contributing to Elasticsearch as part of a class. If you really want to assign writing code for Elasticsearch as an assignment then the code contributions should be made to your private clone and opening PRs against the primary Elasticsearch clone must be optional, fully voluntary, not for a grade, and without any deadlines.

Because:

While the code review process is likely very educational, it can take wildly varying amounts of time depending on who is available, where the change is, and how deep the change is. There is no way to predict how long it will take unless we rush.
We do not rush reviews without a very, very good reason. Class deadlines aren't a good enough reason for us to rush reviews.
We deeply discourage opening a PR you don't intend to work through the entire code review process because it wastes our time.
We don't have the capacity to absorb an entire class full of new contributors, especially when they are unlikely to become long time contributors.

Finally, we require that you run ./gradlew check before submitting a non-documentation contribution. This is mentioned above, but it is worth repeating in this section because it has come up in this context.

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