[jira] [Created] (SPARK-17048) ML model read for custom transformers in a pipeline does not work

["Taras Matyashovskyy (JIRA)" <ji...@apache.org>]

Taras Matyashovskyy created SPARK-17048:
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             Summary: ML model read for custom transformers in a pipeline does not work 
                 Key: SPARK-17048
                 URL: https://issues.apache.org/jira/browse/SPARK-17048
             Project: Spark
          Issue Type: Bug
          Components: ML
    Affects Versions: 2.0.0
         Environment: Spark 2.0.0
Java API

            Reporter: Taras Matyashovskyy


0. Use Java API :( 
1. Create any custom ML transformer
2. Make it MLReadable and MLWritable
3. Add to pipeline
4. Evaluate model, e.g. CrossValidationModel, and save results to disk
5. For custom transformer you can DefaultParamsReader and DefaultParamsWriter, for instance 
6. Load model from saved directory
7. All out-of-the-box objects are loaded successfully, e.g. Pipeline, Evaluator, etc.
8. Your custom transformer will fail with NPE

Reason:
ReadWrite.scala:447
cls.getMethod("read").invoke(null).asInstanceOf[MLReader[T]].load(path)

In Java this only works for static methods.
As we are implementing MLReadable or MLWritable, then this call should be instance method call. 






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