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docs: clarify that histogram_avg/count/sum/stddev/stdvar are native-histogram-only

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The docs for these functions previously described them as acting on
"each histogram sample," which was ambiguous. Add "native" to clarify
they only operate on native histogram samples, not classic histograms.
This distinction was originally documented but lost when the
experimental feature warnings were removed.

Signed-off-by: Jeremy Rickards <jeremy.rickards@sap.com>
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Jeremy Rickards 2026-03-19 14:28:18 +01:00
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docs/querying/functions.md
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@ -219,7 +219,7 @@ to their original value. Histogram samples in the input vector are ignored silen
## `histogram_avg()`
`histogram_avg(v instant-vector)` returns the arithmetic average of observed
values stored in each histogram sample in `v`. Float samples are ignored and do
values stored in each native histogram sample in `v`. Float samples are ignored and do
not show up in the returned vector.
Use `histogram_avg` as demonstrated below to compute the average request duration
@ -236,11 +236,11 @@ Which is equivalent to the following query:
## `histogram_count()` and `histogram_sum()`
`histogram_count(v instant-vector)` returns the count of observations stored in
each histogram sample in `v`. Float samples are ignored and do not show up in
each native histogram sample in `v`. Float samples are ignored and do not show up in
the returned vector.
Similarly, `histogram_sum(v instant-vector)` returns the sum of observations
stored in each histogram sample.
stored in each native histogram sample.
Use `histogram_count` in the following way to calculate a rate of observations
(in this case corresponding to “requests per second”) from a series of
@ -453,14 +453,14 @@ histogram_quantiles(sum(rate(foo[1m])), "quantile", 0.9, 0.99)
## `histogram_stddev()` and `histogram_stdvar()`
`histogram_stddev(v instant-vector)` returns the estimated standard deviation
of observations for each histogram sample in `v`. For this estimation, all observations
of observations for each native histogram sample in `v`. For this estimation, all observations
in a bucket are assumed to have the value of the mean of the bucket boundaries. For
the zero bucket and for buckets with custom boundaries, the arithmetic mean is used.
For the usual exponential buckets, the geometric mean is used. Float samples are ignored
and do not show up in the returned vector.
Similarly, `histogram_stdvar(v instant-vector)` returns the estimated standard
variance of observations for each histogram sample in `v`.
variance of observations for each native histogram sample in `v`.
## `hour()`