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- 1. Introduction
- 2. Documentation
- 3. Prerequisites
- 4. Build
- 5. Testing
- 6. CI/CD
- 7. Submitting Issues
- 8. Submitting PRs
- 9. References
- 10. License
The TDengine Kafka Connector is a high-efficiency data integration tool designed for data synchronization between TDengine and Kafka. It supports real-time synchronization of data from Kafka to the TDengine database, as well as real-time synchronization of data from TDengine to Kafka. Leveraging TDengine's high-performance time-series data processing capabilities, the TDengine Kafka Connector enables enterprises to effortlessly achieve real-time storage and analysis of massive time-series data.
- To use
TDengine Kafka Connector, please check TDengine Kafka Connector, it includes instructions and examples on how to install, configure, and use theTDengine Kafka Connector. - This quick guide is mainly for developers who like to contribute/build/test the
TDengine Kafka Connectorby themselves. To learn about TDengine, you can visit the official documentation.
- Java 1.8 or above runtime environment and Maven 3.6 or above installed, with environment variables correctly set.
- TDengine has been deployed locally. For specific steps, please refer to Deploy TDengine. Please make sure taosd and taosAdapter have been started. If you are using a Mac system, please use the command
sudo ln -s /usr/local/lib/libtaos.dylib /Library/Java/Extensions/libtaos.dylibto create a symbolic link for thetaosdynamic library.
Execute mvn clean package in the project directory to build the project.
Execute mvn test in the project directory to run the tests. The test cases will connect to the local TDengine server and taosAdapter for testing.
After running the tests, the result similar to the following will be printed eventually. If all test cases pass, both Failures and Errors will be 0.
[INFO] Results:
[INFO]
[INFO] Tests run: 8, Failures: 0, Errors: 0, Skipped: 0
All tests are located in the src/test/java/com/taosdata/kafka/connect directory of the project. The directory is divided according to the functions being tested. You can add new test files or add test cases in existing test files.
The test cases use the JUnit framework. Generally, resources are typically initialized in the before method and released in the after method.
Performance testing is in progress.
We welcome the submission of GitHub Issue. When submitting, please provide the following information:
- Problem description, whether it always occurs, and it's best to include a detailed call stack.
- Kafka version.
- TDengine Kafka Connector version.
- TDengine Kafka Connector configure file (username and password not required).
- TDengine server version.
We welcome developers to contribute to this project. When submitting PRs, please follow these steps:
- Fork this project, refer to (how to fork a repo).
- Create a new branch from the main branch with a meaningful branch name (
git checkout -b my_branch). Do not modify the main branch directly. - Modify the code, ensure all unit tests pass, and add new unit tests to verify the changes.
- Push the changes to the remote branch (
git push origin my_branch). - Create a Pull Request on GitHub (how to create a pull request).
- After submitting the PR, you can find your PR through the Pull Request. Click on the corresponding link to see if the CI for your PR has passed. If it has passed, it will display "All checks have passed". Regardless of whether the CI passes or not, you can click "Show all checks" -> "Details" to view the detailed test case logs.
- After submitting the PR, if CI passes, you can find your PR on the codecov page to check the test coverage.