title: Py4JJavaError When using pyspark ml library
body: <p>I want to run a PCA using pyspark, but it gives this strange error. 
  I am using a MAC with python 3.6.3, and pyspark 2.3.1. I have tried using the virtual environment as well, the same error occurs. The same errors occurs when I am doing Random forest model fitting as well. Please let me know how to fix this !?</p>
  
  <pre><code>from pyspark.ml.feature import PCA
  from pyspark.mllib.linalg import Vectors
  from pyspark import SparkContext
  from pyspark import SQLContext
  
  sc = SparkContext()
  
  sqlContext = SQLContext(sc)
  data = [(Vectors.sparse(5, [(1,1.0), (3, 7.0)]),), 
      (Vectors.dense([2.0,0.0,3.0,4.0,5.0]),),
      (Vectors.dense([5.6,3.0,1.0,6.4,3.5]),),
      (Vectors.dense([3.4, 5.3, 0.0, 5.5, 6.6]),),
     (Vectors.dense([4.1,3.1,3.2,9.1,7.0]),),
     (Vectors.dense([3.6, 4.1, 4.2, 6.3, 7.0]),),]
  
  df = sqlContext.createDataFrame(data, ['features'])
  
  pca = PCA(k=3, inputCol='features', outputCol='pcaFeatures')
  # Error Occurs on this line
  modle = pca.fit(df)
  
  ERROR:
  ---------------------------------------------------------------------------
  Py4JJavaError                             Traceback (most recent call last)
  /usr/local/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
       62         try:
  ---&gt; 63             return f(*a, **kw)
       64         except py4j.protocol.Py4JJavaError as e:
  
  ~/anaconda3/lib/python3.6/site-packages/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
      327                     "An error occurred while calling {0}{1}{2}.\n".
  --&gt; 328                     format(target_id, ".", name), value)
      329             else:
  
  Py4JJavaError: An error occurred while calling o35.fit.
  : java.lang.IllegalArgumentException: requirement failed: Column features must be of type org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7 but was actually org.apache.spark.mllib.linalg.VectorUDT@f71b0bce.
      at scala.Predef$.require(Predef.scala:224)
      at org.apache.spark.ml.util.SchemaUtils$.checkColumnType(SchemaUtils.scala:42)
      at org.apache.spark.ml.feature.PCAParams$class.validateAndTransformSchema(PCA.scala:56)
      at org.apache.spark.ml.feature.PCA.validateAndTransformSchema(PCA.scala:70)
      at org.apache.spark.ml.feature.PCA.transformSchema(PCA.scala:105)
      at org.apache.spark.ml.PipelineStage.transformSchema(Pipeline.scala:74)
      at org.apache.spark.ml.feature.PCA.fit(PCA.scala:94)
      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:498)
      at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
      at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
      at py4j.Gateway.invoke(Gateway.java:282)
      at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
      at py4j.commands.CallCommand.execute(CallCommand.java:79)
      at py4j.GatewayConnection.run(GatewayConnection.java:238)
      at java.lang.Thread.run(Thread.java:748)
  
  
  During handling of the above exception, another exception occurred:
  
  IllegalArgumentException                  Traceback (most recent call last)
  &lt;ipython-input-11-cf9820b1adfc&gt; in &lt;module&gt;()
  ----&gt; 1 modle = pca.fit(df)
  
  /usr/local/spark/python/pyspark/ml/base.py in fit(self, dataset, params)
      130                 return self.copy(params)._fit(dataset)
      131             else:
  --&gt; 132                 return self._fit(dataset)
      133         else:
      134             raise ValueError("Params must be either a param map or a list/tuple of param maps, "
  
  /usr/local/spark/python/pyspark/ml/wrapper.py in _fit(self, dataset)
      286 
      287     def _fit(self, dataset):
  --&gt; 288         java_model = self._fit_java(dataset)
      289         model = self._create_model(java_model)
      290         return self._copyValues(model)
  
  /usr/local/spark/python/pyspark/ml/wrapper.py in _fit_java(self, dataset)
      283         """
      284         self._transfer_params_to_java()
  --&gt; 285         return self._java_obj.fit(dataset._jdf)
      286 
      287     def _fit(self, dataset):
  
  ~/anaconda3/lib/python3.6/site-packages/py4j/java_gateway.py in __call__(self, *args)
     1255         answer = self.gateway_client.send_command(command)
     1256         return_value = get_return_value(
  -&gt; 1257             answer, self.gateway_client, self.target_id, self.name)
     1258 
     1259         for temp_arg in temp_args:
  
  /usr/local/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
       77                 raise QueryExecutionException(s.split(': ', 1)[1], stackTrace)
       78             if s.startswith('java.lang.IllegalArgumentException: '):
  ---&gt; 79                 raise IllegalArgumentException(s.split(': ', 1)[1], stackTrace)
       80             raise
       81     return deco
  
  IllegalArgumentException: 'requirement failed: Column features must be of type org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7 but was actually org.apache.spark.mllib.linalg.VectorUDT@f71b0bce.'
  
  
  1
  sc.version
  '2.3.1'
  </code></pre>