fix: Resolve the issue of conflicts between columns added during the analysis process and the original data columns in the Spark version.

[frelion]

#1476

In the Spark version, the program will add some auxiliary columns to the dataframe during runtime, such as Count, Std, etc.

If the original data to be analyzed already contains these columns, it may result in column name conflicts.

solution:
Before the program analysis, add the suffix "_customer" to all columns of the DataFrame.
Remove the suffix when displaying the results.

[PeterlitsZo]

Look good to me. It's OK. It can solve the problem.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 90.25%. Comparing base (2d9a24b) to head (925bcee).
Report is 25 commits behind head on develop.

❗ Current head 925bcee differs from pull request most recent head 2d7f8bb. Consider uploading reports for the commit 2d7f8bb to get more accurate results

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #1518      +/-   ##
===========================================
+ Coverage    90.08%   90.25%   +0.17%     
===========================================
  Files          195      195              
  Lines         6383     6383              
===========================================
+ Hits          5750     5761      +11     
+ Misses         633      622      -11     

Flag	Coverage Δ
py3.8-ubuntu-22.04-pandas	90.25% <ø> (+0.17%)	⬆️

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