| commit | 3b77ccc018655b64ea12af5807f18f19dc642a17 | [log] [tgz] |
|---|---|---|
| author | Yu <yu.liu003@gmail.com> | Wed Mar 11 23:15:19 2020 +0800 |
| committer | William Guo <guoyp@apache.org> | Wed Mar 11 23:15:19 2020 +0800 |
| tree | 409f2f1e9ec2ae541fc10defaf603b13918d1431 | |
| parent | 24c270e016a9c7c42ec5f137672dadc7f7ef13f6 [diff] |
[GRIFFIN-316] Fix job exception handling **What changes were proposed in this pull request?** Currently we are using Try instance to represent the results of a DQ job, whether succeeded or failed. But as we are only wrapping the Boolean result by applying "Try" at the most outside level, the underlying failure would not be able to caught and it would always return "Success" even if exception got. This is to modify all the underlying execute/doExecute methods of a DQ job, by handling exception with "Try" instances so that it could be passed properly to users when things get wrong. **Does this PR introduce any user-facing change?** No. **How was this patch tested?** Griffin test suite. Author: Yu <yu.liu003@gmail.com> Closes #562 from PnPie/exception_catch.
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.
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