old_contents: from pyspark.ml import Pipeline
  from pyspark.ml.classification import DecisionTreeClassifier
  from pyspark.ml.feature import RFormula
  
  df = spark.read.csv("Iris.csv", header = True, inferSchema = True)
  
  formula = RFormula(formula = "Species ~ .")
  classifier = DecisionTreeClassifier()
  pipeline = Pipeline(stages = [formula, classifier])
  pipelineModel = pipeline.fit(df)
  
  from pyspark2pmml import PMMLBuilder
  
  pmmlBuilder = PMMLBuilder(sc, df, pipelineModel)
  
  pmmlBuilder.buildFile("DecisionTreeIris.pmml")
  
  
new_contents: from pyspark.sql import SparkSession
  from pyspark.ml import Pipeline
  from pyspark.ml.classification import DecisionTreeClassifier
  from pyspark.ml.feature import RFormula
  from pyspark2pmml import PMMLBuilder
  
  spark = SparkSession.builder.appName('SparkByExamples.com').getOrCreate()
  df = spark.read.csv("Iris.csv", header=True, inferSchema=True)
  
  formula = RFormula(formula="Species ~ .")
  classifier = DecisionTreeClassifier()
  pipeline = Pipeline(stages=[formula, classifier])
  pipelineModel = pipeline.fit(df)
  
  pmmlBuilder = PMMLBuilder(spark, df, pipelineModel)
  
  pmmlBuilder.buildFile("DecisionTreeIris.pmml")
  
subject: Fix python lint in the spark pmml example (#1567)