datalake_fdw: timestamp columns in units other than microseconds

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#1,990 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

The Parquet reader in contrib/datalake_fdw (#1951) reads only microsecond timestamps (tsu:), which is what Iceberg defines and what this module writes. Files written by other systems carry other units, and today every one of them is refused with a column stored as Arrow type "tsm:..." cannot be read as timestamp.

Cases

Millisecond columns (TIMESTAMP_MILLIS): common in Parquet written by Spark with spark.sql.parquet.outputTimestampType=TIMESTAMP_MILLIS, by Hive, and by many ETL tools. Multiplying by 1000 loses nothing. The question is whether a lake table should read a file whose type is not the table's type; Iceberg's spec says data files carry the table's types, so accepting them is a lenience, not a requirement.
Nanosecond columns (TIMESTAMP_NANOS, Iceberg v3 timestamp_ns): dividing by 1000 truncates. Refuse, or truncate and say so.
INT96 is already handled by coercing to microseconds. One caveat, Arrow's rather than ours (reproduced with pyarrow 21 and the same setting): Arrow's microsecond conversion assumes the nanos-of-day half is non-negative, which Spark/Hive/Impala guarantee; pyarrow's deprecated INT96 writer stores a negative one for instants before 1970 and those read wrong. Coercing to nanoseconds instead would fix that one case and break every date outside 1677..2262, including the 9999-12-31 sentinels warehouses keep. Worth an upstream report.

Where

format/arrow_decode.c: dl_arrow_decode_check() decides what a timestamp column accepts, dl_arrow_decode_value() converts. The TIMESTAMP/TIMESTAMPTZ case already distinguishes zoned from unzoned by whether the format string names a zone.

Deferred from #1951 on purpose.

Lingua principale: C
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