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From "Xiangrui Meng (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-4587) Model export/import
Date Sun, 01 Mar 2015 19:30:05 GMT

     [ https://issues.apache.org/jira/browse/SPARK-4587?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xiangrui Meng updated SPARK-4587:
---------------------------------
    Issue Type: Umbrella  (was: New Feature)

> Model export/import
> -------------------
>
>                 Key: SPARK-4587
>                 URL: https://issues.apache.org/jira/browse/SPARK-4587
>             Project: Spark
>          Issue Type: Umbrella
>          Components: ML, MLlib
>            Reporter: Xiangrui Meng
>            Assignee: Joseph K. Bradley
>            Priority: Critical
>
> This is an umbrella JIRA for one of the most requested features on the user mailing list.
Model export/import can be done via Java serialization. But it doesn't work for models stored
distributively, e.g., ALS and LDA. Ideally, we should provide save/load methods to every model.
PMML is an option but it has its limitations. There are couple things we need to discuss:
1) data format, 2) how to preserve partitioning, 3) data compatibility between versions and
language APIs, etc.
> UPDATE: [Design doc for model import/export | https://docs.google.com/document/d/1kABFz1ssKJxLGMkboreSl3-I2CdLAOjNh5IQCrnDN3g/edit?usp=sharing]
> This document sketches machine learning model import/export plans, including goals, an
API, and development plans.
> UPDATE: As in the design doc, we plan to support:
> * Our own Spark-specific format.
> ** This is needed to (a) support distributed models and (b) get model import/export support
into Spark quickly (while avoiding the complexity of PMML).
> * PMML
> ** This is needed since it is the most commonly used format in industry.
> This JIRA will be for the internal Spark-specific format described in the design doc.
Parallel JIRAs will cover PMML.



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