[ https://issues.apache.org/jira/browse/SPARK-22872?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Cyanny updated SPARK-22872: --------------------------- Attachment: jpmml-research.jpg [^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: > !jpmml-research.jpg|thumbnail! -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org