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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def cast(self, dataType):
 """ Convert the column into type ``dataType``. [Row(ages=u'2'), Row(ages=u'5')] [Row(ages=u'2'), Row(ages=u'5')] """

        if isinstance(dataType, basestring):
            jc = self._jc.cast(dataType)
        elif isinstance(dataType, DataType):
            from pyspark.sql import SparkSession
            spark = SparkSession.builder.getOrCreate()
            jdt = spark._jsparkSession.parseDataType(dataType.json())
            jc = self._jc.cast(jdt)
        else:
            raise TypeError("unexpected type: %s" % type(dataType))
        return Column(jc)