text: Title: Optimise Spearman Correlations according to Spark Docs
  Body: Overview : [Spark Development Strategy](https://github.com/pandas-profiling/pandas-profiling/wiki/Spark-Development-Plan)
  
  Branch : spark-branch
  
  Context : 
  
  Spearman correlations are a key part of pandas-profiling, and help elucidate rank based correlation statistics.
  
  Problem :
  
  Spark docs mentions that spearman correlations can be optimised through good use of caching due to requirements to do rank computations and RDD level manipulations. https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.ml.stat.Correlation.html
  
  Solution :
  
  We would need figure how to do the caching, and also measure out how fast the speed improvement is (to actually know if we have implemented the caching solution properly).
  