[chore] [deltatocumulative]: linear histograms

[sh0rez]

Description

Finishes work started in #35048

That PR only partially introduced a less complex processor architecture by only using it for Sums.
Back then I was not sure of the best way to do it for multiple datatypes, as generics seemed to introduce a lot of complexity regardless of usage.

I since then did of a lot of perf analysis and due to the way Go works (see gcshapes), we do not really gain anything at runtime from using generics, given method calls are still dynamic.

This implementation uses regular Go interfaces and a good old type switch in the hot path (ConsumeMetrics), which lowers mental complexity quite a lot imo.

The value of the new architecture is backed up by the following benchmark:

goos: linux
goarch: arm64
pkg: github.com/open-telemetry/opentelemetry-collector-contrib/processor/deltatocumulativeprocessor
                 │ sums.nested │             sums.linear             │
                 │   sec/op    │   sec/op     vs base                │
Processor/sums-8   56.35µ ± 1%   39.99µ ± 1%  -29.04% (p=0.000 n=10)

                 │  sums.nested  │             sums.linear              │
                 │     B/op      │     B/op      vs base                │
Processor/sums-8   11.520Ki ± 0%   3.683Ki ± 0%  -68.03% (p=0.000 n=10)

                 │ sums.nested │            sums.linear             │
                 │  allocs/op  │ allocs/op   vs base                │
Processor/sums-8    365.0 ± 0%   260.0 ± 0%  -28.77% (p=0.000 n=10)

Testing

This is a refactor, existing tests pass unaltered.

Documentation

not needed