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Jack Ye
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SELECT and Enterprise SQL sat apart in Query while documenting the same engine. They are now one SQL group: overview, Select, Aggregation, Join, Window, Sampling, Functions -- one page per construct, with the Enterprise client-setup and FTS pages merged in rather than parallel to them. Sampling is new. TABLESAMPLE is implemented and was undocumented: BERNOULLI picks rows, SYSTEM picks Lance fragments, REPEATABLE fixes the draw so a sample works as a stable evaluation set. Its refusals are documented too -- a percentage over 100, a fractional row count, BUCKET, the SAMPLE spelling and the OFFSET modifier are all errors, because a sampling clause that were read and not applied would be a wrong answer rather than a missing feature. Schema & Data Types is one page again, with the multimodal content merged into its blob section rather than sitting beside it. Agentic Skills stops being a tab. Both its pages are tutorials, so they join the Tutorials tab; the Basics page that introduces them stays.
91 lines
2.7 KiB
Plaintext
91 lines
2.7 KiB
Plaintext
---
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title: "Window functions"
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sidebarTitle: "Window"
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description: "Compute over a set of rows related to the current one, without collapsing them."
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icon: chart-simple
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keywords: ["window", "over", "partition by", "row_number", "rank", "lag", "lead"]
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---
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<Badge color="red">Enterprise</Badge> [SQL runs on a deployment.](/sql)
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A window function computes across a set of rows related to the current one and
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returns a value **per row**. That is the difference from
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[aggregation](/sql/aggregation), which collapses the rows it covers.
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```sql
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SELECT
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title,
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score,
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row_number() OVER (PARTITION BY category ORDER BY score DESC) AS rank
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FROM documents
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```
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Every row survives; each one gains its rank within its category.
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## The window {#window}
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```sql
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OVER (
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[PARTITION BY expr [, ...]]
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[ORDER BY expr [, ...]]
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[ROWS | RANGE BETWEEN frame_start AND frame_end]
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)
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```
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`PARTITION BY` splits the rows into independent groups. `ORDER BY` orders them
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inside each partition -- required by the ranking functions, since a rank without
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an order is meaningless. The frame clause narrows the window further, which is
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how running totals and moving averages are expressed:
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```sql
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SELECT
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created_at,
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sum(amount) OVER (ORDER BY created_at ROWS UNBOUNDED PRECEDING) AS running_total,
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avg(amount) OVER (ORDER BY created_at ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS trailing_7
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FROM transactions
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```
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A `WINDOW` clause names a definition when several functions share one:
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```sql
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SELECT
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row_number() OVER w,
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lag(score) OVER w
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FROM documents
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WINDOW w AS (PARTITION BY category ORDER BY score DESC)
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```
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## The functions {#functions}
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| Kind | Functions |
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| --- | --- |
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| Ranking | `row_number`, `rank`, `dense_rank`, `percent_rank`, `ntile`, `cume_dist` |
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| Offset | `lag`, `lead`, `first_value`, `last_value`, `nth_value` |
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| Aggregate | any [aggregate](/sql/aggregation) used with `OVER` |
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The full set is DataFusion's
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[window function reference](https://datafusion.apache.org/user-guide/sql/window_functions.html).
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## Deduplicating with a window {#dedup}
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The common practical use: keep one row per key, chosen by some ordering. A
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window ranks, and an outer query filters:
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```sql
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WITH ranked AS (
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SELECT *, row_number() OVER (PARTITION BY doc_id ORDER BY version DESC) AS rn
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FROM revisions
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)
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SELECT * FROM ranked WHERE rn = 1
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```
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The outer query is needed because a window function cannot appear in `WHERE` --
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windows are computed after filtering, so the predicate would have nothing to
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read.
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<Note>
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Window functions sort within each partition, so on a large table they are among
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the more expensive things you can ask for. Filter first, and check the cost with
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[Explain Analyze](/search/explain-analyze).
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</Note>
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