Comments (2)
This seems unrelated to caching to me. This query generates a large result set - .fetchall()
fetches the entire result as Python objects which is slow. Try fetching the result using e.g. .arrow()
instead.
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Ah fantastic, that produces consistent behavior with the CLI for single-threaded. Not quite for multi-threaded (e.g. it's 0.341s on average), but that discrepancy seems likely to be Python overheads. Thank you!
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Related Issues (20)
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- Illegal Predicate Pushdown leads to Casting error HOT 1
- Wrong result/data loss when using Filter Pushdown and Union_By_Name HOT 3
- Query unnesting with grouping sets results in wrong output HOT 1
- IN/OR operator removes completely Parquet Filter Pushdown on other filters HOT 2
- Exporting to Pandas has incorrect column type for BOOLEAN and BIGINT when some entries are NA/NULL HOT 4
- hive_partitioning=True can interpret empty string values in directory as NULL
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- Parquet read : Invalid decimal encoding in Parquet file HOT 2
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- v1.0.0 jdbc connector: TransactionContext Error on DBeaver
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- performance of lateral join on timestamp fields
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