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    <title>Window Functions on 每日拍拍</title>
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      <title>DuckDB Window Functions 實戰：排名、移動平均與分組分析</title>
      <link>https://dailypypy.org/learn/duckdb-window-functions/</link>
      <pubDate>Thu, 17 Sep 2026 11:57:00 +0800</pubDate>
      
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dedup note: Planned 2026-09-17 topic `duckdb-window-functions` passed a strict 164-post inventory and current-source scan. ../python-duckdb/ teaches general CSV/Parquet querying and Python integration; ../streamlit-duckdb-dashboard/ and ../textual-duckdb-dashboard/ focus on UI workflows; ../python-polars/ contains only a short `over()` subsection. This focused follow-up instead teaches analytical SQL with partitions, deterministic peer ordering, ranking, LAG/LEAD, explicit ROWS/RANGE/GROUPS frames, rolling metrics, QUALIFY, named windows, null handling, and execution-plan checks. It cross-links the adjacent posts without repeating ingestion or dashboard setup.
source check: Reviewed against the current official DuckDB Window Functions, WINDOW clause, QUALIFY, SELECT-order, EXPLAIN ANALYZE, and workload-tuning documentation on 2026-09-17. Core ranking, LAG/LEAD, ROWS/RANGE/GROUPS, named-window, QUALIFY, null-handling, and assertion examples passed a DuckDB 1.5.5 runtime smoke test. Examples make ordering, peer rows, default-frame behavior, blocking-operator memory cost, and QUALIFY placement explicit.
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