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https://issues.apache.org/jira/browse/FLINK-23959?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dong Lin updated FLINK-23959:
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Component/s: Library / Machine Learning
> FLIP-175: Add GraphBuilder to compose Estimator/Transformer/AlgoOperator from
> a DAG of stages
> ---------------------------------------------------------------------------------------------
>
> Key: FLINK-23959
> URL: https://issues.apache.org/jira/browse/FLINK-23959
> Project: Flink
> Issue Type: Improvement
> Components: Library / Machine Learning
> Reporter: Dong Lin
> Priority: Major
> Labels: pull-request-available
>
> The FLIP design doc can be found at
> https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=181311363.
> The existing Flink ML library allows users to compose an
> Estimator/Transformer from a pipeline (i.e. linear sequence) of
> Estimator/Transformer. Users only need to construct this Pipeline once and
> generate the corresponding PipelineModel, without having to explicitly
> construct the fitted PipelineModel as a linear sequence of stages. However,
> in order to train a DAG of Estimator/Transformer and uses the trained model
> for inference, users currently need to construct the DAG twice, once for the
> training logic and once for the inference logic. This experience is inferior
> to the experience of training and using a chain of Estimator/Transformer. In
> addition to requiring more work from users, this approach is more error prone
> because the DAG for the training logic may be inconsistent from the DAG for
> the inference logic.
> In order to address the issues described above, we propose to add several
> helper classes that allow users to compose Estimator/Transformer/AlgoOperator
> from a DAG of Estimator/Transformer/AlgoOperator.
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