|author||chitralverma <firstname.lastname@example.org>||Tue Mar 09 14:33:02 2021 +0530|
|committer||chitralverma <email@example.com>||Tue Mar 09 14:33:02 2021 +0530|
[GRIFFIN-345] Support cross-version compilation for Scala and Spark dependencies **What changes were proposed in this pull request?** _This PR affects only the measure module._ In newer environments specially clouds, Griffin measure module may face compatibility issues due the old Scala and Spark versions. To remedy this following topics are covered in this ticket, - Cross-compilation across scala major versions (2.11, 2.12) - Update Spark Version (2.4+) - Create maven profiles to build different scala and spark versions - Changes to build strategy This process is also done is apache spark to build for different versions of Scala and Hadoop. **Does this PR introduce any user-facing change?** No **How was this patch tested?** Via maven build process. Closes #589 from chitralverma/cross-version-build. Authored-by: chitralverma <firstname.lastname@example.org> Signed-off-by: chitralverma <email@example.com>
The data quality (DQ) is a key criteria for many data consumers like IoT, machine learning etc., however, there is no standard agreement on how to determine “good” data. Apache Griffin is a model-driven data quality service platform where you can examine your data on-demand. It provides a standard process to define data quality measures, executions and reports, allowing those examinations across multiple data systems. When you don't trust your data, or concern that poorly controlled data can negatively impact critical decision, you can utilize Apache Griffin to ensure data quality.
You can try running Griffin in docker following the docker guide.
Follow Apache Griffin Development Environment Build Guide to set up development environment.
If you want to contribute codes to Griffin, please follow Apache Griffin Development Code Style Config Guide to keep consistent code style.
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