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Merge pull request #2 from databrickslabs/0.1_release
Release 0.1
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CONTRIBUTING.md

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We happily welcome contributions to *Databricks Labs - Rules Engine*.
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We happily welcome contributions to *Databricks Labs - dataframe-rules-engine*.
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We use GitHub Issues to track community reported issues and GitHub Pull Requests for accepting changes.

LICENSE

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[Project Name]
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dataframe-rules-engine
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Copyright (2019) Databricks, Inc.
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NOTICE

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Databricks Labs - Rules Engine
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Copyright (2018) Databricks, Inc.
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This Software includes software developed at Databricks (https://www.databricks.com/) and its use is subject to the included LICENSE file.
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dataframe-rules-engine
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Copyright (2018) Databricks, Inc.
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This Software includes software developed at Databricks (https://www.databricks.com/) and its use is subject to the included LICENSE file.

README.md

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## Project Description
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As pipelines move from bronze to gold, it's very common that some level of governance be performed in
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Silver or at various places in the pipeline. The need for business rule validation is very common.
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Databricks recognizes this and as such is building Delta Pipelines with Expectations are coming soon
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and will likely reduce the need for a rules engine like this but it's possible that simple rules are needed
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where Delta Pipelines are a bit overkill or not in line with the overall workload. After the release
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of Delta Pipelines and Expectations the code base will be reviewed and adjusted appropriately. That may mean to
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extend Expectations, add a simplified wrapper, or both, or none. We'll have to wait and see what Delta
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Pipelines and Expectations looks like when it's released.
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Introducing Databricks Labs - Rules Engine, a simple solution for validating data in dataframes before you
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Databricks recognizes this and, as such, is building Delta Pipelines with Expectations.
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Upon release of Delta Pipelines, the need for this package will be re-evaluated and the code base will
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be adjusted appropriately. This is serves an immediate need and Delta Expectations is expected to be a more,
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full-fledged and robust example of this functionality.
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Introducing Databricks Labs - dataframe-rules-engine, a simple solution for validating data in dataframes before you
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move the data to production and/or in-line (coming soon).
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![Alt Text](images/Rules_arch.png)
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* Add a quarantine pattern
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* Enable a configuration to a Ruleset to identify records that didn't pass the validations and add
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them to a predefined quarantine zone.
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* Add logic to attempt to auto-handle certain types of failures based on common business patterns
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* Add logic to attempt to auto-handle certain types of failures based on common business patterns
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* When Delta Pipelines feature is release, simplify this package by wrapping the logic with pipelines.
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## Legal Information

build.sbt

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name := "Rules_Engine"
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name := "dataframe-rules-engine"
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organization := "com.databricks"
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