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ComputeError: caught exception during execution of a Python source

Aperta
  • Qualcosa non va?
#128 2 commenti 0 reazioni 0 assegnatari Vedi su GitHub

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Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
38/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Ferma
Stack tecnologico
python
Ambito
databases

Direzione di ricerca

Inizia eseguendo la riproduzione DuckDB Python fornita con due Lazy DataFrames e il join, quindi ispeziona l’output di LazyFrame.explain(optimized=True) e il percorso di integrazione Python .pl(lazy=True). Il lavoro è completato quando il join e collect terminano correttamente senza l’errore relativo al risultato della query in sospeso chiuso; i datasets riservati possono limitare la convalida.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

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
Lingua principale
Python
Stelle
189
Fork
117
Merge medio
1g 58m
PR unite (30g)
15

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