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MetricsRepository using Spark tables as the data source #518
MetricsRepository using Spark tables as the data source #518
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Hi @VenkataKarthikP, thank you for the PR! While we review the PR, could you please provide more details on the use case that this PR helps enable? An example snippet of code of how this feature can be used will be great, to both serve as motivation for the PR and for documentation going forward. |
@rdsharma26 updated PR description with more details, let me know if it looks good. |
src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/main/scala/com/amazon/deequ/repository/sparktable/SparkMetricsRepository.scala
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src/test/scala/com/amazon/deequ/repository/sparktable/SparkTableMetricsRepositoryTest.scala
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@rdsharma26 thanks for review, have addressed review comments, with some follow up questions. |
metricDF.write | ||
.mode(SaveMode.Append) | ||
.saveAsTable(tableName) |
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Hello @VenkataKarthikP, thanks a lot for the added feature!!!
Could we consider to let the user define the write options in some way?
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sure, I think it's great idea. let me check!
@rdsharma26 can we merge this PR. thanks |
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
* spark table repository * review comments --------- Co-authored-by: vpenikalapati <[email protected]>
Issue #, if available:
#502
Description of changes:
An implementation of MetricsRepository using Spark tables as the data source.
Currently, DQ heavily relies on spark for processing. But to save metrics to a table like Iceberg or Hive or other spark catalog based, we don't have an implementation. With this PR, users can save metrics to a table and read them offline as needed.
Example usage -
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.