No type coercion between time values with different units (`Time64(µs) = Time64(ns)` fails)

Abierto
#27,359 0 comentarios 1 reacción 1 asignado Ver en GitHub

Los mantenedores suelen responder en 1 día

@sdf-jkl ya está trabajando en esto.

Desde el 12/11/2026.

  • #27377 de @sdf-jkl — abierto

Evaluación

Este issue todavía no se ha evaluado.

Descripción

Describe the bug

DataFusion has no type coercion between Arrow time types with different units (Time32(Second), Time32(Millisecond), Time64(Microsecond), Time64(Nanosecond)). Comparisons, IN lists, join keys, UNION, and coalesce that mix two of them fail during planning:

Cannot infer common argument type for comparison operation Time64(µs) = Time64(ns)

A common way to hit this is comparing a Parquet TIME(MICROS) column, which is read as Time64(µs), with a SQL TIME value, which is Time64(ns). pyarrow writes Python datetime.time values as TIME(MICROS) by default.

@kumarUjjawal found this while reviewing #27316: https://github.com/apache/datafusion/pull/27316#discussion_r4533709191

To Reproduce

Write a file with pyarrow defaults:

import datetime
import pyarrow as pa
import pyarrow.parquet as pq

pq.write_table(pa.table({"t": [datetime.time(12, 0), datetime.time(13, 30)]}), "times.parquet")

Then run:

CREATE EXTERNAL TABLE pq STORED AS PARQUET LOCATION 'times.parquet';
SELECT arrow_typeof(t) FROM pq LIMIT 1; -- Time64(µs)

SELECT t FROM pq WHERE t = '12:00:00'; -- works, the string is cast to Time64(µs)

SELECT t FROM pq WHERE t = TIME '12:00:00';
SELECT t FROM pq WHERE t < TIME '13:00:00';
SELECT t FROM pq WHERE t IN (TIME '12:00:00', TIME '13:30:00');

CREATE TABLE schedule(s TIME) AS VALUES (TIME '12:00:00');
SELECT * FROM pq JOIN schedule ON t = s;
SELECT t FROM pq UNION ALL SELECT s FROM schedule;
SELECT coalesce(t, TIME '00:00:00') FROM pq;

Every query after the string comparison fails:

Query Error
t = TIME '12:00:00' Cannot infer common argument type for comparison operation Time64(µs) = Time64(ns)
t < TIME '13:00:00' Cannot infer common argument type for comparison operation Time64(µs) < Time64(ns)
t IN (...) Can not find compatible types to compare Time64(µs) with [Time64(ns), Time64(ns)]
JOIN ... ON t = s Cannot infer common argument type for comparison operation Time64(µs) = Time64(ns)
UNION ALL Incompatible inputs for Union: Previous inputs were of type Time64(µs), but got incompatible type Time64(ns) on column 's'
coalesce No function matches the given name and argument types 'coalesce(Time64(µs), Time64(ns))'

Any two different units fail the same way, for example arrow_cast('12:00:00', 'Time32(Millisecond)') = arrow_cast('12:00:00', 'Time32(Second)').

Expected behavior

Time values with different units coerce to the finer unit, as timestamps already do (CAST('2024-01-01 12:00:00' AS TIMESTAMP(0)) = CAST('2024-01-01 12:00:00' AS TIMESTAMP) returns true). All the queries above plan and return results.

Additional context

temporal_coercion pairs Time32/Time64 with Date32/Date64 but has no rule for two time types. Timestamps avoid the problem because temporal_coercion_nonstrict_timezone unifies their units with timeunit_coercion. Comparison, IN, UNION, and coalesce coercion all reach temporal_coercion, so a matching time rule there would fix every query above. Time - Time already works across units through temporal_math_coercion and would not change.

#27316 (support TIME(p)) also makes this reachable from SQL type names alone, since CAST(x AS TIME(6)) or a column declared TIME(0) cannot be compared with plain TIME. @alamb suggested tracking it separately: https://github.com/apache/datafusion/pull/27316#discussion_r4538803450

Reproduced on main at 64c29642d. branch-56 and 55.2.0 have no time rule in temporal_coercion either. #27316 has been requested for 56, so it would help to backport this fix with it.

Willingness to contribute

I plan to contribute a fix for this bug independently

Lenguaje dominante
Rust
Estrellas
9.6k
Forks
2.6k
Merge medio
3 d 4 h
PR fusionados (30 d)
345

Preparar el entorno

Abrir en Codespaces

Inicia el contenedor de desarrollo del proyecto en tu navegador, con tu propia cuenta de GitHub.

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Más de apache/datafusion

Todos los issues de apache/datafusion

Issues similares

Más issues de Rust

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.