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ComputeError: caught exception during execution of a Python source

Abierto
  • ¿Algo no está bien?
#128 2 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
38/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Estancado
Stack tecnológico
python
Área
databases

Línea de trabajo

Empieza ejecutando la reproducción proporcionada de DuckDB Python con dos Lazy DataFrames y el join; después inspecciona la salida de LazyFrame.explain(optimized=True) y la ruta de integración de Python .pl(lazy=True). Se considera completado cuando el join y collect terminan correctamente sin el error de resultado de consulta pendiente cerrado; los datasets confidenciales pueden limitar la validación.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

needs triage
What happens?

First of all nice, feature with the lazy DataFrame. I have a problem with this new feature in duckdb v1.4.1 also tested with 1.4.0 and polars version 1.34.0, but also tested with versions earlier than this.
Mostly the first loading and filtering ... with pl(lazy = True) works but e.g. joins with other tables are not working and results in this Error:

ComputeError: caught exception during execution of a Python source, exception: InvalidInputException: Invalid Input Error: Attempting to execute an unsuccessful or closed pending query result.

Full Trace:

File ~/.venv/lib/python3.9/site-packages/polars/_utils/deprecation.py:97, in deprecate_streaming_parameter.<locals>.decorate.<locals>.wrapper(*args, **kwargs)
     93         kwargs["engine"] = "in-memory"
     95     del kwargs["streaming"]
---> [97](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a225468726f6d626f7365227d.vscode-resource.vscode-cdn.net/home/cdsw/notebooks/~/.venv/lib/python3.9/site-packages/polars/_utils/deprecation.py:97) return function(*args, **kwargs)

File ~/.venv/lib/python3.9/site-packages/polars/lazyframe/opt_flags.py:328, in forward_old_opt_flags.<locals>.decorate.<locals>.wrapper(*args, **kwargs)
    325         optflags = cb(optflags, kwargs.pop(key))  # type: ignore[no-untyped-call,unused-ignore]
    327 kwargs["optimizations"] = optflags
--> [328](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a225468726f6d626f7365227d.vscode-resource.vscode-cdn.net/home/cdsw/notebooks/~/.venv/lib/python3.9/site-packages/polars/lazyframe/opt_flags.py:328) return function(*args, **kwargs)

File ~/.venv/lib/python3.9/site-packages/polars/lazyframe/frame.py:2415, in LazyFrame.collect(self, type_coercion, predicate_pushdown, projection_pushdown, simplify_expression, slice_pushdown, comm_subplan_elim, comm_subexpr_elim, cluster_with_columns, collapse_joins, no_optimization, engine, background, optimizations, **_kwargs)
   2413 # Only for testing purposes
   2414 callback = _kwargs.get("post_opt_callback", callback)
-> [2415](https://vscode-remote+ssh-002dremote-002b7b22686f73744e616d65223a225468726f6d626f7365227d.vscode-resource.vscode-cdn.net/home/cdsw/notebooks/~/.venv/lib/python3.9/site-packages/polars/lazyframe/frame.py:2415) return wrap_df(ldf.collect(engine, callback))
To Reproduce
con = duckdb.connect(db.db_path, read_only= True)
df_lab = con.sql("SELECT * FROM data1").pl(lazy = True)
df_main = con.sql("SELECT * FROM data2").pl(lazy = True)
df_lab.join(df_main, on = "account_id").collect()

this would be the LazyFrame:

naive plan: (run LazyFrame.explain(optimized=True) to see the optimized plan)
INNER JOIN:
LEFT PLAN ON: [col("account_id")]
PYTHON SCAN []
PROJECT */10 COLUMNS
RIGHT PLAN ON: [col("account_id")]
PYTHON SCAN []
PROJECT */70 COLUMNS
END INNER JOIN

OS:

linux

DuckDB Version:

1.41.0

DuckDB Client:

Python

Hardware:

No response

Full Name:

Maximilian Zeidler

Affiliation:

Helios

What is the latest build you tested with? If possible, we recommend testing with the latest nightly build.

I have tested with a stable release

Did you include all relevant data sets for reproducing the issue?

No - I cannot share the data sets because they are confidential

Did you include all code required to reproduce the issue?
  • Yes, I have
Did you include all relevant configuration (e.g., CPU architecture, Python version, Linux distribution) to reproduce the issue?
  • Yes, I have
Lenguaje dominante
Python
Estrellas
189
Forks
117
Merge medio
1 d 58 min
PR fusionados (30 d)
15

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