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max_temp_directory_size in connect config is reported but not enforced

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評価

難易度
4/5
見積もり時間
3〜5日
初心者へのやさしさ
30/100
issue の種類
バグ
明瞭さ
明確に書かれている
活発さ
活発
技術スタック
python
領域
databases

調査の方向性

Run the reproduction script first to confirm the two runs differ: the apply_set=False run should succeed while the apply_set=True run raises OutOfMemoryException. Then trace how the max_temp_directory_size key in the config= mapping passed to duckdb.connect is applied during connection initialization, and compare that with the path SET max_temp_directory_size takes. Done means the connect-time 1-byte cap rejects the spill just as the SET run does, and the same script passes both cases.

索引モデルが issue の本文から書いたものです。

説明

What happens?

Passing max_temp_directory_size through duckdb.connect(config=...) makes current_setting('max_temp_directory_size') report the requested value, but spilling is not bounded by it. Executing the same value with SET max_temp_directory_size after the connection is created enforces the cap.

This can silently let a Python process consume the filesystem space that the connect-time configuration was intended to reserve.

To Reproduce

This self-contained script generates its own Parquet input and runs the same external sort twice:

import tempfile
from pathlib import Path

import duckdb


def run(apply_set: bool) -> None:
    root = Path(tempfile.mkdtemp())
    source = root / "source.parquet"
    output = root / "output.parquet"

    with duckdb.connect() as connection:
        connection.sql(
            """
            SELECT
                i AS row_id,
                i % 17 AS group_id,
                repeat(md5(i::VARCHAR), 32) AS payload
            FROM range(49152) t(i)
            """
        ).write_parquet(str(source), row_group_size=2048)

    with duckdb.connect(
        str(root / "test.duckdb"),
        config={
            "memory_limit": "64MB",
            "threads": 2,
            "temp_directory": str(root / "tmp"),
            "preserve_insertion_order": False,
            "max_temp_directory_size": "1B",
        },
    ) as connection:
        if apply_set:
            connection.execute("SET max_temp_directory_size = '1B'")

        print("apply_set", apply_set)
        print(
            "setting",
            connection.execute(
                "SELECT current_setting('max_temp_directory_size')"
            ).fetchone(),
        )

        try:
            connection.read_parquet(str(source)).order(
                "group_id, payload, row_id"
            ).write_parquet(str(output), row_group_size=2048)
            print("sort succeeded")
        except Exception as error:
            print(type(error).__name__, str(error).splitlines()[0])


run(apply_set=False)
run(apply_set=True)

Output with DuckDB 1.5.6:

apply_set False
setting ('1 byte',)
sort succeeded
apply_set True
setting ('1 byte',)
OutOfMemoryException Out of Memory Error: failed to offload data block of size 32.0 KiB (0 bytes/1 byte used).

Expected: both runs reject the spill at the 1-byte cap.

The behavior also reproduces with DuckDB 1.5.2. This is specific to initialization through the Python config mapping, so there is no equivalent plain-SQL/CLI connect-time reproduction; the post-connect SQL SET is the working comparison.

Environment
  • OS: macOS 27.0, arm64
  • DuckDB Package Version: 1.5.6 (latest stable; also 1.5.2)
  • Python Version: 3.13.14
  • Full Name: Simon Thelin
  • Affiliation: Odyssey
  • Latest build tested: stable release
  • Data set: not applicable; the reproduction generates its input
  • All code and relevant configuration are included
主要言語
Python
スター
191
フォーク
120
平均マージ
14時間 1分
マージ済み PR（30日）
23

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