yigal-rozenberg commented on issue #1582:
URL: 
https://github.com/apache/iceberg-python/issues/1582#issuecomment-2631515059

   Hi @Fokko,
   File encryption is an essential functionality that adds an immortal security 
layer to data integrity and security on a file level.
   Data Centric security addresses a different challenge in privacy and 
security of data.
   The idea is based on a concept where you protect and classify data during 
creation and carry the security properties across all systems without the need 
to re-encrypt and reclassify it.
   Traditional data security solutions rely on data discovery and 
classification based on the location of the data 
(server.db.schema.table.column), and the need to continuously track and 
re-identify data as it flows in the organization.
   Once the base protected data type is identified by the engine as protected 
and not just a structure or binary buffer, the engine layer can set min/max and 
even aggregation values in puffin files to further improve performance.
   Additionally these puffin fees can be extended to include bloom filters 
(based on the clear text values) and even inverted indexes to allow wild card 
and other operations over clear text data representation (this is where files 
encryption is important).
   
   I am still trying to understand the code base, and identify how and where I 
can implement supported operators according to the input data type to decipher 
the data and decode it to the original data type (e.g., binary->str, 
binary->date, etc.). 


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