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https://issues.apache.org/jira/browse/SPARK-23244?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tomas Nykodym updated SPARK-23244:
----------------------------------
Description:
Default values are not handled properly when serializing/deserializing python
trasnformers which are wrappers around scala objects. It looks like that after
deserialization the default values which were based on uid do not get properly
restored and values which were not set are set to their (original) default
values.
Here's a simple code example using Bucketizer:
{code:python}
>>> from pyspark.ml.feature import Bucketizer
>>> a = Bucketizer()
>>> a.save("bucketizer0")
>>> b = load("bucketizer0")
>>> a._defaultParamMap[a.outputCol]
u'Bucketizer_440bb49206c148989db7__output'
>>> b._defaultParamMap[b.outputCol]
u'Bucketizer_41cf9afbc559ca2bfc9a__output'
>>> a.isSet(a.outputCol)
False
>>> b.isSet(b.outputCol)
True
>>> a.getOutputCol()
u'Bucketizer_440bb49206c148989db7__output'
>>> b.getOutputCol()
u'Bucketizer_440bb49206c148989db7__output'
{code}
was:
Default values are not handled properly when serializing/deserializing python
trasnformers which are wrappers around scala objects. It looks like that after
deserialization the default values which were based on uid do not get properly
restored and values which were not set are set to their (original) default
values.
Here's a simple code example using Bucketizer:
```\{python}
{{from pyspark.ml.feature import Bucketizer }}
{{>>> a = Bucketizer() }}
{{>>> a.save("bucketizer0") }}
{{>>> b = load("bucketizer0") }}
{{>>> a._defaultParamMap[a.outputCol]}}
u'Bucketizer_440bb49206c148989db7__output'
{{>>> b._defaultParamMap[b.outputCol] }}
u'Bucketizer_41cf9afbc559ca2bfc9a__output'
{{>>> a.isSet(a.outputCol) }}
{{False }}
{{>>> b.isSet(b.outputCol) }}
{{True}}{{}}
>>> a.getOutputCol()
u'Bucketizer_440bb49206c148989db7__output'
>>> b.getOutputCol()
u'Bucketizer_440bb49206c148989db7__output'
```
> Incorrect handling of default values when deserializing python wrappers of
> scala transformers
> ---------------------------------------------------------------------------------------------
>
> Key: SPARK-23244
> URL: https://issues.apache.org/jira/browse/SPARK-23244
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 2.2.1
> Reporter: Tomas Nykodym
> Priority: Minor
>
> Default values are not handled properly when serializing/deserializing python
> trasnformers which are wrappers around scala objects. It looks like that
> after deserialization the default values which were based on uid do not get
> properly restored and values which were not set are set to their (original)
> default values.
> Here's a simple code example using Bucketizer:
> {code:python}
> >>> from pyspark.ml.feature import Bucketizer
> >>> a = Bucketizer()
> >>> a.save("bucketizer0")
> >>> b = load("bucketizer0")
> >>> a._defaultParamMap[a.outputCol]
> u'Bucketizer_440bb49206c148989db7__output'
> >>> b._defaultParamMap[b.outputCol]
> u'Bucketizer_41cf9afbc559ca2bfc9a__output'
> >>> a.isSet(a.outputCol)
> False
> >>> b.isSet(b.outputCol)
> True
> >>> a.getOutputCol()
> u'Bucketizer_440bb49206c148989db7__output'
> >>> b.getOutputCol()
> u'Bucketizer_440bb49206c148989db7__output'
> {code}
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