title: Sum big decimals in pyspark and see rhe entire number
body: <p>I have the following dataframe:</p>
  
  <pre><code>from pyspark.sql import functions as f
  from pyspark.sql import Window
  
  df = spark.createDataFrame(sc.parallelize([["gr1", "1663708559.71"], ["gr1", "123958300.14"],["gr2", "2006101145.31"]]), ["group_col", "numb"])
  </code></pre>
  
  <p>And i want to have a new column with the sum of values grouped by group col. But i don't have a readeble output.</p>
  
  <pre><code>df.withColumn("sum_gr", f.sum(df["numb"].cast("double"))).over(Window.partitionBy(df["group_col"]))).show(10, False)
  </code></pre>
  
  <p>After i calculate the sum i have to compare that big value with another big value and even if they are equals, i dont get a match.</p>
  
  <p>I have the followig result:
   For gr1: the sum is 1.7876668500001E9
  and i have to compare this value with lets say 1787666850000.143.</p>
  
  <p>What is the best approach when working with big float numbers in pyspark? How should i do to have the entire number with all decimals converted into a string?</p>