[
https://issues.apache.org/jira/browse/SPARK-22872?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Cyanny updated SPARK-22872:
---------------------------
Description:
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:
was:
Hi all,
I recently did a research about pmml, and my project need to transform many
model types to pmml files.
Moreover, JPMML(https://github.com/jpmml/jpmml-sparkml) provides 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:
!http://i65.tinypic.com/2q1dxtd.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
>
> 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:
> 
--
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
