MarkLogic Data Hub welcomes new contributors. This document will guide you through the process.
If you find a bug in the source code or a mistake in the documentation, you can help us by submitting an issue to our GitHub Issue Tracker. If you'd like to submit a feature enhancement, please first create an issue with your proposed idea so that we can start a discussion about the problem you want to solve and what the best solution would be.
You can request a new feature by submitting an issue to our GitHub Issue Tracker. If you would like to implement a new feature then first create a new issue and discuss it with one of our project maintainers.
This section describes how to build and test new features and fixes in Data Hub. This includes changes to the following subprojects in this project:
- the Data Hub library in ./marklogic-data-hub
- the Data Hub Gradle plugin in ./ml-data-hub-plugin
- the web application in ./marklogic-data-hub-central
You need:
- MarkLogic Server (see Version Compatibility for the correct version)
- Java JDK 9, 10 or 11
- Gradle 6.4 (6.4.x and higher may work, but 6.4 is preferred)
The source code for the Data Hub library is in the ./marklogic-data-hub subproject. This project contains hundreds of tests, written in JUnit and also written using marklogic-unit-test. While developing, you'll create/modify/run tests to verify the changes that you're making.
To run the tests, you first need to deploy a test instance of Data Hub to MarkLogic. The configuration for this instance is in the ./marklogic-data-hub/gradle.properties; you can override these values in gradle-local.properties. Verify that the values for mlSecurityUsername and mlSecurityPassword are correct, as that user will be used to deploy the test instance of Data Hub. Also, ensure that you do not have a Data Hub instance already deployed to the MarkLogic that you will connect to. Then, run the following Gradle task from the root project:
./gradlew -i bootstrap
After two or three minutes, the bootstrap process will finish, and the test instance of Data Hub will be installed in MarkLogic.
At this point, you could run all the tests, but those can take an hour or more to finish. Instead, running the marklogic-unit-test tests is a better way to do a quick sanity check on your deployment:
./gradlew testUnit
After running that, you can also access the marklogic-unit-test GUI test runner at http://localhost:8011/test/default.xqy . This GUI allows you to run individual tests or sets of tests, which "testUnit" does not yet support.
If you'd instead like to run the JUnit tests, you can use the Gradle "--tests" feature to run a subset of tests - e.g.
./gradlew test --tests FlowRunnerTest
Or, if you've loaded this project into an IDE such as Intellij, you can simply use the IDE's capabilities for running one or more tests at once.
If you are looking to change Data Hub code that runs in MarkLogic - i.e. the files under ./marklogic-data-hub/src/main/resources/ml-modules - consider running the following Gradle task that will automatically load files into MarkLogic as you change them:
./gradlew -i -PignoreDirty=true mlWatch
The "ignoreDirty" parameters tells the mlWatch task to only load files that are modified once mlWatch starts running.
If you wish to make changes to or try out the latest code in the Data Hub Java library (marklogic-data-hub-(version).jar), follow these instructions:
- Publish the Data Hub library and Data Hub Gradle plugin to your local Maven repository (defaults to ~/.m2/repository).
./gradlew publishToMavenLocal - In the build.gradle file for the project that will use the library, add your local Maven repository as a repository if it's not alreaded included:
repositories {
mavenLocal()
}- Assuming that you're using Gradle's java plugin, add the library as a dependency to your project:
dependencies {
compile "com.marklogic:marklogic-data-hub:(version)"The version is defined in gradle.properties in the marklogic-data-hub root project directory. You can override this if desired when publishing to your local Maven repository - e.g.
./gradlew publishToMavenLocal -Pversion=myVersion
The source code for the Data Hub library is in the ./ml-data-hub-plugin subproject. While tests exist for these tasks and it's possible to add your own, you may also want to publish a local copy of the Data Hub plugin and test it in another project. To do so, follow the steps below.
- Publish the Data Hub library and Gradle plugin to your local Maven repository (defaults to ~/.m2/repository).
./gradlew publishToMavenLocal- Then add the following to the build.gradle file of the project where you'd like to test your just-published Data Hub Gradle plugin:
// this goes at the top above the plugins section
buildscript {
repositories {
mavenLocal()
mavenCentral()
}
dependencies {
classpath "com.marklogic:ml-data-hub:(the version number you chose)"
}
}
plugins {
...
// comment out this line. It pulls the version from the cloud
// id 'com.marklogic.ml-data-hub' version '5.5.0'
}
// this tells gradle to apply the plugin you included above in the buildscript section
apply plugin: "com.marklogic.ml-data-hub"Your Data Hub project will now be using the Data Hub plugin that you published.
Note that while you're testing the Data Hub plugin in another project, you can also use the technique mentioned above for loading modules via the Gradle "mlWatch" task. That is - while you test the plugin, you can make changes to the Data Hub modules under ./marklogic-data-hub/src/main/resources/ml-modules as see the impact within the project application that you're testing.
To run the plugin's unit tests, first follow the instructions above for deploying a test instance of Data Hub to MarkLogic.
Then, similar to testing the Data Hub library, you can run all of the tests:
cd ml-data-hub-plugin
../gradlew test
Or just run a specific test:
../gradlew test --tests CreateEntityTaskTest
See the marklogic-data-hub-central README.md file for more information.
Before you submit your issue, search the archive to check if your question has been answered.
If your issue appears to be a bug and hasn't been reported, open a new issue.
By not reporting duplicate issues, you help us maximize the time we spend fixing issues and adding new features.
Please fill out the issue template so that your issue can be dealt with quickly.
Fork the project on GitHub and clone your copy.
$ git clone git@github.com:username/marklogic-data-hub.git
$ cd marklogic-data-hub
$ git remote add upstream git://github.com/marklogic/marklogic-data-hub.gitImportant: Please open an issue in the issue tracker and get your proposed changes pre-approved by at least one of the project maintainers before you start coding. Nothing is more frustrating than seeing your hard work go to waste because your vision does not align with that of the project maintainers.
If you decide to fix something, create a feature branch and start hacking.
Note: We use git flow and our most recent changes live on the develop branch.
$ git checkout -b my-feature-branch -t origin/developWe use [.editorconfig][] to configure our editors for proper code formatting. If you don't
use a tool that supports editorconfig, be sure to configure your editor to use the settings
equivalent to our .editorconfig file.
Make sure git knows your name and email address:
$ git config --global user.name "J. Random User"
$ git config --global user.email "j.random.user@example.com"Writing good commit logs is important. A commit log should describe what changed and why. Follow these guidelines when writing one:
- The first line should be 50 characters or less and contain a short description of the change including the issue number prefixed by a hash (#).
- Keep the second line blank.
- Wrap all other lines at 72 columns.
Example of a good commit log:
Fixing Issue #123: make the whatchamajigger work in MarkLogic 9
Body of commit message is a few lines of text, explaining things
in more detail, possibly giving some background about the issue
being fixed, etc.
The body of the commit message can be several paragraphs, and
please do proper word-wrap and keep columns shorter than about
72 characters or so. That way `git log` will show things
nicely even when it is indented.
The header line should be meaningful; it is what other people see when they
run git shortlog or git log --oneline.
Use git rebase (not git merge) to sync your work from time to time.
$ git fetch upstream
$ git rebase upstream/developSee the sections above on how to test changes to the Data Hub library and/or to the Data Hub Gradle plugin.
Once your pull request is submitted (see below), MarkLogic's internal CI process will handle running all of the tests against your branch in a clean environment. Project maintainers will notify you of any failures so that you can address them.
$ git push origin my-feature-branchBefore we can accept and merge your changes, you must sign a Contributor License Agreement. You only need to do this once.
Go to https://github.com/username/marklogic-data-hub and select your feature branch. Click the 'Pull Request' button and fill out the form.
Pull requests are usually reviewed within a few days. If you get comments that need to be to addressed, apply your changes in a separate commit and push that to your feature branch. Post a comment in the pull request afterwards; GitHub does not send out notifications when you add commits to existing pull requests.
That's it! Thank you for your contribution!
After your pull request is merged, you can safely delete your branch and pull the changes from the main (upstream) repository:
-
Delete the remote branch on GitHub either through the GitHub web UI or your local shell as follows:
git push origin --delete my-feature-branch
-
Check out the develop branch:
git checkout develop -f
-
Delete the local branch:
git branch -D my-feature-branch
-
Update your develop with the latest upstream version:
git pull --ff upstream develop