title: How to convert ArrayType to DenseVector in PySpark DataFrame?
body: <p>I'm getting the following error trying to build a ML <code>Pipeline</code>:</p>
  
  <pre><code>pyspark.sql.utils.IllegalArgumentException: 'requirement failed: Column features must be of type org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7 but was actually ArrayType(DoubleType,true).'
  </code></pre>
  
  <p>My <code>features</code> column contains an array of floating point values. It sounds like I need to convert those to some type of vector (it's not sparse, so a DenseVector?). Is there a way to do this directly on the DataFrame or do I need to convert to an RDD?</p>