title: FPGrowth: Input data is not cached pyspark
body: <p>I am trying to run following example code. Even-though I have cached my data, I am getting "Input data is not cached pyspark" warning. Because of this issue, I am not able to use fp growth algorithm for large datasets.</p>
  
  <pre><code>from pyspark.ml.fpm import FPGrowth
  from pyspark.sql import SparkSession
  
  """
  An example demonstrating FPGrowth.
  Run with:
  bin/spark-submit examples/src/main/python/ml/fpgrowth_example.py
  """
  
  if __name__ == "__main__":
      spark = SparkSession\
          .builder\
          .appName("FPGrowthExample")\
          .getOrCreate()
  
      # $example on$
      df = spark.createDataFrame([
          (0, [1, 2, 5]),
          (1, [1, 2, 3, 5]),
          (2, [1, 2])
          ], ["id", "items"])
  
      df = df.cache()
  
      fpGrowth = FPGrowth(itemsCol="items", minSupport=0.5, minConfidence=0.6)
      model = fpGrowth.fit(df)
  
      # Display frequent itemsets.
      model.freqItemsets.show()
  
      # Display generated association rules.
      model.associationRules.show()
  
      # transform examines the input items against all the association rules and summarize the
      # consequents as prediction
      model.transform(df).show()
  
  
      spark.stop()
  </code></pre>