chore: encapsulate column fields logic

[andre-sampaio]

Also fix a bug where push down joins would not work with compound row keys.

ReadRowConversions was kept in place to simplify this PR but will be removed in a subsequent cl.

[gemini-code-assist]

Summary of Changes

Hello @andre-sampaio, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly refactors the Bigtable Spark connector by encapsulating all Bigtable row conversion and mutation logic within the BigtableTableCatalog. This change streamlines the ReadRowConversions and WriteRowConversions APIs and resolves a critical issue affecting push-down joins when dealing with compound row keys.

Highlights

• Encapsulation of Column Logic: I've refactored the Bigtable row conversion logic (both reading and writing) by moving it into the BigtableTableCatalog class. This centralizes the handling of column fields and mutations, improving modularity.
• API Simplification: The ReadRowConversions.buildRow method now accepts a Seq[String] (column names) directly, simplifying its interface and removing the need for an intermediate Seq[Field] mapping.
• Bug Fix: Compound Row Keys in Joins: I've addressed a bug where push-down joins would not work correctly with compound row keys. This was fixed by ensuring the catalog.row.getBtRowKeyBytes method is used for accurate row key conversion during join operations.

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[gemini-code-assist]

Code Review

The pull request successfully encapsulates column fields logic into BigtableTableCatalog, significantly improving modularity and maintainability for both read and write operations. It also addresses a bug related to push-down joins with compound row keys by correctly handling row key byte conversion. A critical issue was identified where a necessary import is missing in BigtableTableCatalog.scala, which will cause a compilation failure.