feat(table): add support for merge-on-read delete

[alexandre-normand]

This adds support for merge-on-read deletes. It offers an alternative to the copy-on-write to generate position delete files instead of rewriting existing data files.

I'm not very confident in the elegance of my solution as I'm still new to the internals of iceberg-go but the high-level is:

• Reuse the classification code from the existing delete implementation to get the list of files of dropped files vs files with partial deletes
• Reuse the arrow scanning facilities to filter records from the data files with partial deletes and emit position delete records with file path and position.
  • This is done by reusing the pipeline code and function and making the first stage in the pipeline one to enrich the RecordBatch with the file Path and position before the original position is lost due to filtering.
  • After filtering, the RecordBatch is projected to the position delete schema (i.e. the original schema fields are dropped)
• Once we have filtered PositionDelete records that need to be emitted, we reuse the record to file writing to generate position delete files.

Testing

Integration tests were added to exercise the partitioned and unpartitioned paths and the data is such that it's meant to actually produce a position delete file rather than just go through the quick path that drops an entire file because all records are gone.

Indirect fixes

While working on this change and adding the testing for the partitioned table deletions, I realized that the manifest evaluation when the filter affected a field that was part of a partition spec was not built correctly. It needed to use similar code as what's done during scanning to build projections and build a manifest evaluator per partition id. This is fixed in this PR but this technically also applies to copy-on-write and overwrite paths so the fix goes beyond the scope of the merge-on-read.

[alexandre-normand]

The spec says that pos is a long so I updated this to be Int64 rather than Int32.