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https://issues.apache.org/jira/browse/SPARK-13724?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15192718#comment-15192718
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senthil gandhi commented on SPARK-13724:
----------------------------------------
I was able to replicate this, here is the exception, how does one deal with
this from the python API?
---
py4j.protocol.Py4JJavaError: An error occurred while calling
o163.trainDecisionTreeModel.
: java.lang.IllegalArgumentException: requirement failed:
RandomForest/DecisionTree given maxMemoryInMB = 256, which is too small for the
given features. Minimum value = 446
at scala.Predef$.require(Predef.scala:233)
at org.apache.spark.mllib.tree.RandomForest.run(RandomForest.scala:186)
at org.apache.spark.mllib.tree.DecisionTree.run(DecisionTree.scala:60)
at
org.apache.spark.mllib.tree.DecisionTree$.train(DecisionTree.scala:86)
at
org.apache.spark.mllib.api.python.PythonMLLibAPI.trainDecisionTreeModel(PythonMLLibAPI.scala:748)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
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)
> Parameter maxMemoryInMB has gone missing in MlLib 1.6.0
> DecisionTree.trainClassifier()
> --------------------------------------------------------------------------------------
>
> Key: SPARK-13724
> URL: https://issues.apache.org/jira/browse/SPARK-13724
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.6.0
> Reporter: senthil gandhi
>
> DecisionTree.trainClassifier() reports that maxMemoryInMB is too small during
> training and stops. But when I try to set it, I found that in MLlib of spark
> 1.6.0 pyspark.mllib.tree.DecisionTree doesn't have this parameter in the
> named parameter list anymore.
> (Also not sure if this is the place for this issue, kindly educate!)
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