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Posted to issues@spark.apache.org by "Xiangrui Meng (JIRA)" <ji...@apache.org> on 2016/02/12 03:39:18 UTC
[jira] [Resolved] (SPARK-13153) PySpark ML persistence failed when
handle no default value parameter
[ https://issues.apache.org/jira/browse/SPARK-13153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiangrui Meng resolved SPARK-13153.
-----------------------------------
Resolution: Fixed
Fix Version/s: 1.6.1
2.0.0
Issue resolved by pull request 11043
[https://github.com/apache/spark/pull/11043]
> PySpark ML persistence failed when handle no default value parameter
> --------------------------------------------------------------------
>
> Key: SPARK-13153
> URL: https://issues.apache.org/jira/browse/SPARK-13153
> Project: Spark
> Issue Type: Bug
> Components: ML, PySpark
> Reporter: Tommy Yu
> Assignee: Tommy Yu
> Priority: Minor
> Fix For: 2.0.0, 1.6.1
>
>
> This defect find when implement task spark-13033. When add below code to doctest.
> It looks like _transfer_params_from_java did not consider the params which do not have default value and we should handle them.
> >>> import os, tempfile
> >>> path = tempfile.mkdtemp()
> >>> aftsr_path = path + "/aftsr"
> >>> aftsr.save(aftsr_path)
> >>> aftsr2 = AFTSurvivalRegression.load(aftsr_path)
> Exception detail.
> ir2 = IsotonicRegression.load(ir_path)
> Exception raised:
> Traceback (most recent call last):
> File "C:\Python27\lib\doctest.py", line 1289, in run
> compileflags, 1) in test.globs
> File "<doctest __main.IsotonicRegression[11]>", line 1, in
> ir2 = IsotonicRegression.load(ir_path)
> File "C:\aWorkFolder\spark\spark-1.6.0-bin-hadoop2.6\spark-1.6.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\ml\util.py", line 194, in load
> return cls.read().load(path)
> File "C:\aWorkFolder\spark\spark-1.6.0-bin-hadoop2.6\spark-1.6.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\ml\util.py", line 148, in load
> instance.transfer_params_from_java()
> File "C:\aWorkFolder\spark\spark-1.6.0-bin-hadoop2.6\spark-1.6.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\ml\wrapper.py", line 82, in tran
> fer_params_from_java
> value = _java2py(sc, self._java_obj.getOrDefault(java_param))
> File "C:\aWorkFolder\spark\spark-1.6.0-bin-hadoop2.6\spark-1.6.0-bin-hadoop2.6\python\lib\py4j-0.9-src.zip\py4j\java_gateway.py", line 813, in
> _call
> answer, self.gateway_client, self.target_id, self.name)
> File "C:\aWorkFolder\spark\spark-1.6.0-bin-hadoop2.6\spark-1.6.0-bin-hadoop2.6\python\lib\pyspark.zip\pyspark\sql\utils.py", line 45, in deco
> return f(a, *kw)
> File "C:\aWorkFolder\spark\spark-1.6.0-bin-hadoop2.6\spark-1.6.0-bin-hadoop2.6\python\lib\py4j-0.9-src.zip\py4j\protocol.py", line 308, in get_
> eturn_value
> format(target_id, ".", name), value)
> Py4JJavaError: An error occurred while calling o351.getOrDefault.
> : java.util.NoSuchElementException: Failed to find a default value for weightCol
> at org.apache.spark.ml.param.Params$$anonfun$getOrDefault$2.apply(params.scala:647)
> at org.apache.spark.ml.param.Params$$anonfun$getOrDefault$2.apply(params.scala:647)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.ml.param.Params$class.getOrDefault(params.scala:646)
> at org.apache.spark.ml.PipelineStage.getOrDefault(Pipeline.scala:43)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:483)
> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
> at py4j.Gateway.invoke(Gateway.java:259)
> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
> at py4j.commands.CallCommand.execute(CallCommand.java:79)
> at py4j.GatewayConnection.run(GatewayConnection.java:209)
> at java.lang.Thread.run(Thread.java:745)
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