Luo Gen created FLINK-13167:
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Summary: Introduce FlinkML import/export framework
Key: FLINK-13167
URL: https://issues.apache.org/jira/browse/FLINK-13167
Project: Flink
Issue Type: Sub-task
Components: Library / Machine Learning
Reporter: Luo Gen
Assignee: Luo Gen
Import/export a trained model is an important part in machine learning
lifecycle, especially for serving purpose, hence it triggered a heatedly
discussion in the previous pull request for FlinkML basic interfaces. Some
thoughts about this are summarized in the following doc.
https://docs.google.com/document/d/1B84b-1CvOXtwWQ6_tQyiaHwnSeiRqh-V96Or8uHqCp8/edit?usp=sharing
The jira will introduce the import/export framework based on these discussion.
Import and export framework have almost the same structure so we take export
for example. Export framework has 3 basic components, including 2 interfaces
for exporter authors to implement, and one util class for end-users to acquire
an Exporter.
Interfaces:
- Exporter: Interface of model exporters. Implementations can export supported
models to a specific target model type, such as PMML.
- ExporterFactory: Interface of factories to create Exporters. Each
implementation supports only one model type. Typically an ExporterFactory is
given a model instance with a property map if needed, and returns an Exporter
that supports the model to export to target model type. ExporterFactories are
loaded with ServiceLoader framework of Java, and should be registered in the
file
"META-INF/services/org.apache.flink.ml.api.misc.exportation.ExporterFactory".
Utility:
- ExporterLoader: Loader to get an Exporter for a specific model format and a
model instance. Users would get Exporters via this class rather than directly
creating with constructors. This is a concrete util class and no one needs to
override it.
Besides, a new enumeration named ModelType is also introduced, listing all
types FlinkML may support. This would be extended when a new exporter support a
new type.
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