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update doc
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@ -23,7 +23,7 @@ ClickHouse supports the standard grammar for defining windows and window functio
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| `GROUPS` frame | ❌ |
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| Calculating aggregate functions over a frame (`sum(value) over (order by time)`) | ✅ (All aggregate functions are supported) |
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| `rank()`, `dense_rank()`, `row_number()` | ✅ |
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| `percent_rank()` | ✅ equal to `ifNull((rank() OVER(PARTITION BY x order by y) - 1) / nullif(count(1) OVER(PARTITION BY x) -1, 0), 0)`, but more efficient|
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| `percent_rank()` | ✅ Efficiently computes the relative standing of a value within a partition in a dataset. This function effectively replaces the more verbose and computationally intensive manual SQL calculation expressed as `ifNull((rank() OVER(PARTITION BY x ORDER BY y) - 1) / nullif(count(1) OVER(PARTITION BY x) - 1, 0), 0)`|
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| `lag/lead(value, offset)` | ❌ <br/> You can use one of the following workarounds:<br/> 1) `any(value) over (.... rows between <offset> preceding and <offset> preceding)`, or `following` for `lead` <br/> 2) `lagInFrame/leadInFrame`, which are analogous, but respect the window frame. To get behavior identical to `lag/lead`, use `rows between unbounded preceding and unbounded following` |
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| ntile(buckets) | ✅ <br/> Specify window like, (partition by x order by y rows between unbounded preceding and unrounded following). |
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