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docs: t...over_time functions return fractional seconds (#5715)

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* docs: t...over_time functions return fractional seconds

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Co-authored-by: Aliaksandr Valialkin <valyala@gmail.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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@ -810,7 +810,7 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
#### timestamp
`timestamp(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds for the last raw sample
`timestamp(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
@ -819,7 +819,7 @@ This function is supported by PromQL. See also [timestamp_with_name](#timestamp_
#### timestamp_with_name
`timestamp_with_name(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds for the last raw sample
`timestamp_with_name(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last raw sample
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
Metric names are preserved in the resulting rollups.
@ -828,7 +828,7 @@ See also [timestamp](#timestamp).
#### tfirst_over_time
`tfirst_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds for the first raw sample
`tfirst_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the first raw sample
on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
@ -837,7 +837,7 @@ See also [first_over_time](#first_over_time).
#### tlast_change_over_time
`tlast_change_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds for the last change
`tlast_change_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the last change
per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) on the given lookbehind window `d`.
Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
@ -852,7 +852,7 @@ See also [tlast_change_over_time](#tlast_change_over_time).
#### tmax_over_time
`tmax_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds for the raw sample
`tmax_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
with the maximum value on the given lookbehind window `d`. It is calculated independently per each time series returned
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
@ -862,7 +862,7 @@ See also [max_over_time](#max_over_time).
#### tmin_over_time
`tmin_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds for the raw sample
`tmin_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the timestamp in seconds with millisecond precision for the raw sample
with the minimum value on the given lookbehind window `d`. It is calculated independently per each time series returned
from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).