…pure/delta (#8052)

`doInternal` has adaptive staleness detection mechanism. It is
calculated using timestamp distance between samples in selected list of
samples. It is dynamic because VM can store signals from many sources
with different samples resolution. And while it works for most of cases,
there are edge cases for rollup functions that are comparing values
between windows: increase, increase_pure, delta.

The edge case 1.
There was a gap between series because of the missed scrape or two. In
this case staleness will trigger and increase-like functions will assume
the value they need to compare with is 0. In result, this could produce
spikes for a flappy data - see
#894 This
problem was solved by introducing a `realPrevValue` field -
1f19c16.
It stores the closest real sample value on selected interval and is used
for comparison when samples start after the gap.

The edge case 2.
`realPrevValue` doesn't respect staleness interval. In result, even if
gap between samples is huge (hours), the increase-like functions will
not consider it as a new series that started from 0. See
#8002.

Covering both edge cases is tricky, because `realPrevValue` has to
respect and not respect the staleness interval in the same time. In
other words, it should be able to ignore periodic missing gaps, but
reset if the gap is too big. While "too big gap" can't be figured out
empirically, I suggest using `-search.maxStalenessInterval` for this
purpose. If `-search.maxStalenessInterval` is set to 0 (default), then
`realPrevValue` ignores staleness interval. If
`-search.maxStalenessInterval` is > 0, then `realPrevValue` respects it
as a staleness interval.

### Checklist

The following checks are **mandatory**:

- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).

---------

Signed-off-by: hagen1778 <roman@victoriametrics.com>
(cherry picked from commit 7d2a676)