datalake_fdw: Iceberg name mapping for data files without field ids

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#1,989 aperta il 12/9/2026 0 commenti 0 reazioni 1 assegnatario Vedi su GitHub

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Dal 13/9/2026.

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Descrizione

datalake

Summary

Since #1951 the Parquet reader in contrib/datalake_fdw matches a table's columns to a file's by Iceberg field id (PARQUET:field_id in the Parquet schema). A file whose columns carry no field id can never be matched: every projected column reads as NULL. That is correct per spec for a file the table never wrote, and wrong for the one case the spec covers: tables created over existing Parquet data (add_files, migrated Hive tables), whose files predate the ids.

What the spec says

Iceberg resolves such files through the table property schema.name-mapping.default: a JSON mapping from field ids to the column names to look for in the file, including nested names and multiple names per id (for renamed columns). A reader applies it only to columns that have no field id.

What has to happen

The metadata engine has to surface the property to the access method.
ProjectionSet (format/format.h) needs a way to hand the reader a name mapping alongside the field ids -- a second array of names per id, or a pointer to a parsed mapping.
parquet_read.cpp's parquet_project() matches by id first and falls back to the mapping for id-less columns. Nothing changes in the decoder.
A file with neither ids nor a mapping match stays NULL, as now.

Deferred from #1951 on purpose: the framework there is settled, and the property needs the metadata engine, which is a later PR.

Lingua principale: C
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