Nicholas Chammas created SPARK-17025:
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Summary: Cannot persist PySpark ML Pipeline model that includes
custom Transformer
Key: SPARK-17025
URL: https://issues.apache.org/jira/browse/SPARK-17025
Project: Spark
Issue Type: Bug
Components: ML, PySpark
Affects Versions: 2.0.0
Reporter: Nicholas Chammas
Priority: Minor
Following the example in [this Databricks blog
post|https://databricks.com/blog/2016/05/31/apache-spark-2-0-preview-machine-learning-model-persistence.html]
under "Python tuning", I'm trying to save an ML Pipeline model.
This pipeline, however, includes a custom transformer. When I try to save the
model, the operation fails because the custom transformer doesn't have a
{{_to_java}} attribute.
{code}
Traceback (most recent call last):
File ".../file.py", line 56, in <module>
model.bestModel.save('model')
File
"/usr/local/Cellar/apache-spark/2.0.0/libexec/python/lib/pyspark.zip/pyspark/ml/pipeline.py",
line 222, in save
File
"/usr/local/Cellar/apache-spark/2.0.0/libexec/python/lib/pyspark.zip/pyspark/ml/pipeline.py",
line 217, in write
File
"/usr/local/Cellar/apache-spark/2.0.0/libexec/python/lib/pyspark.zip/pyspark/ml/util.py",
line 93, in __init__
File
"/usr/local/Cellar/apache-spark/2.0.0/libexec/python/lib/pyspark.zip/pyspark/ml/pipeline.py",
line 254, in _to_java
AttributeError: 'PeoplePairFeaturizer' object has no attribute '_to_java'
{code}
Looking at the source code for
[ml/base.py|https://github.com/apache/spark/blob/acaf2a81ad5238fd1bc81e7be2c328f40c07e755/python/pyspark/ml/base.py],
I see that not even the base Transformer class has such an attribute.
I'm assuming this is missing functionality that is intended to be patched up
(i.e. [like
this|https://github.com/apache/spark/blob/acaf2a81ad5238fd1bc81e7be2c328f40c07e755/python/pyspark/ml/classification.py#L1421-L1433]).
I'm not sure if there is an existing JIRA for this (my searches didn't turn up
clear results).
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