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https://issues.apache.org/jira/browse/SPARK-22872?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Cyanny updated SPARK-22872:
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Attachment: jpmml-research.jpg
> Spark ML Pipeline Model Persistent Support Save Schema Info
> -----------------------------------------------------------
>
> Key: SPARK-22872
> URL: https://issues.apache.org/jira/browse/SPARK-22872
> Project: Spark
> Issue Type: IT Help
> Components: ML
> Affects Versions: 2.2.0
> Reporter: Cyanny
> Priority: Minor
> Attachments: jpmml-research.jpg
>
>
> Hi all,
> I recently did a research about pmml, and my project needs to transform many
> models with different type to pmml files.
> Moreover, JPMML(https://github.com/jpmml/jpmml-sparkml) has provided many
> tools to do that. I need to provide a uniform API for user, the API arguments
> are the less the better.
> I came with a issue that, sklearn, tensorflow, and lightgbm can produce only
> one model file, including schema info and model data info.
> but Spark PipelineModel only export a model file in parquet, there is no
> schema info in the model file. And JPMML-SPARK needs two arguments: Schema
> and PipelineModel
> *Can spark PipelineModel include input data schema when export to a file? *
> I found a solution, use dataframe API to export schema:
> ```dataframe.limit(1).write.format("parquet").save("./model.schema")```
> *Are there any solutions to get the PipelineModel input schema?*
> The situations about machine learning libraries to jpmml are as follows:
> !attachment-name.jpg|thumbnail!
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