title: VectorType for StructType in Pyspark Schema
body: <p>I'm reading a parquet file that has the following schema:</p>
  
  <pre><code>df.printSchema()
  
  root
   |-- time: integer (nullable = true)
   |-- amountRange: integer (nullable = true)
   |-- label: integer (nullable = true)
   |-- pcaVector: vector (nullable = true)
  </code></pre>
  
  <p>Now I want to test Pyspark structured streaming and I want to use the same parquet files. The closest schema that I was able to create was using ArrayType, but it doesn't work:</p>
  
  <pre><code>schema = StructType(
      [
          StructField('time', IntegerType()),
          StructField('amountRange', IntegerType()),
          StructField('label', IntegerType()),
          StructField('pcaVector', ArrayType(FloatType()))
  
      ]
  )
  df_stream = spark.readStream\
      .format("parquet")\
      .schema(schema)\
      .load("/home/user/test_arch/data/fraud/")
  
  Caused by: java.lang.ClassCastException: Expected instance of group converter but got "org.apache.spark.sql.execution.datasources.parquet.ParquetPrimitiveConverter"
          at org.apache.parquet.io.api.Converter.asGroupConverter(Converter.java:37)
          at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter$RepeatedGroupConverter.&lt;init&gt;(ParquetRowConverter.scala:659)
          at org.apache.spark.sql.execution.datasources.parquet.ParquetRowConverter.org$apache$spark$sql$execution$datasources$parquet$ParquetRowConverter$$newConverter(ParquetRowConverter.scala:308)
  </code></pre>
  
  <p>How can I create a schema with VectorType, that seems to exist only for Scala, for the StructType in Pyspark?</p>