How to limit FPGrowth itemesets to just 2 or 3

问题

I am running the FPGrowth algorithm using pyspark in python3.6 using jupyter notebook. When I am trying to save the association rules output of rules generated is huge. So I want to limit the number of consequent. Here is the code which I have tried. I also changed the spark context parameters.

Maximum Pattern Length fpGrowth (Apache) PySpark

from pyspark.sql.functions import col, size
from pyspark.ml.fpm import FPGrowth
from pyspark.sql import Row
from pyspark.context import SparkContext
from pyspark.sql.session import SparkSession
from pyspark import SparkConf

conf = SparkConf().setAppName("App")
conf = (conf.setMaster('local[*]')
        .set('spark.executor.memory', '100G')
        .set('spark.driver.memory', '400G')
        .set('spark.driver.maxResultSize', '200G'))
sc = SparkContext.getOrCreate(conf=conf)
spark = SparkSession(sc)
R = Row('ID', 'items')
df=spark.createDataFrame([R(i, x) for i, x in enumerate(lol)])
fpGrowth = FPGrowth(itemsCol="items", minSupport=0.7, minConfidence=0.9)

model = fpGrowth.fit(df)
ar=model.associationRules.where(size(col('antecedent')) == 2).where(size(col('cosequent')) == 1)

ar.cache()
ar.toPandas().to_csv('output.csv')

     It gives an error


   TypeError Traceback (most recent call last)
   <ipython-input-1-f90c7a9f11ae> in <module>

   ---> 73 ar=model.associationRules.where(size(col('antecedent')) == 
  2).where(size(col('consequent')) == 1)
   TypeError: 'str' object is not callable

Can someone help me to solve the issue.

Here lol is list of list of transactions: [['a','b'],['c','a','e']....]

Python: 3.6.5 Pyspark Windows 10

回答1:

From the above discussion and following this link, it helped me to resolve the problem.

'str' object is not callable TypeError

   import pyspark.sql.functions as func
   model.associationRules.where(func.size(func.col('antecedent')) == 1).where(func.size(func.col('consequent')) == 1).show()

来源：https://stackoverflow.com/questions/56822443/how-to-limit-fpgrowth-itemesets-to-just-2-or-3

标签

pyspark

python-3.6