Allow DuckDB to read tables from S3 in cudf_polars benchmark runner - #24139
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WalkthroughThe benchmark utilities now accept string or ChangesRemote dataset support
Priority: ⬇️ Low Estimated code review effort: 3 (Moderate) | ~20 minutes Change: Feature Merge Risk: 🔵 Low · up to Most supported remote and local paths remain usable, but a path containing an apostrophe can still make the benchmark fail during DuckDB view registration. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Inline comments:
In `@python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py`:
- Around line 1979-1984: Add unit tests covering local registration, remote-path
httpfs installation/loading and S3 credential-chain secret setup, plus rejection
in cold mode. Add a unit benchmark that exercises remote DuckDB view
registration through the branch guarded by is_remote_path and validates the
resulting view behavior.
- Line 1990: Update _duckdb_register_views to escape every single quote in
pattern by doubling it before interpolating the value into the DuckDB
parquet_scan SQL literal, while preserving unchanged paths and existing view
registration behavior.
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python/cudf_polars/cudf_polars/streaming/benchmarks/utils.py
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| def is_remote_path(path: os.PathLike | str) -> bool: |
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This also picks up things like file:///path/to/data, which is maybe fine.
In cudf-polars, we use kvikio's remote URL detection. But I don't think we should rely on kvikio here.
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2 participants
Description
(From an agent investigation)
We execute the following SQL query with DuckDB (in
execute_duckdb_query)by building
patternusingpathlibmanipulation of the inputdataset_path, butpathlibisn't be able to handle remote s3 path correctly.This PR just manipulates the paths as strings and loads necessary packages to connect to S3. This work will allow us to more easily generate validation parquet datasets for PDS-DS from our DuckDB queries by writing directly to S3.
Additionally, an agent spotted that it might not make sense to drop the file caches during a cold run when the data source is remote and to raise an error in this case
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