MQE: add support for timestamp

[charleskorn]

What this PR does

This PR adds support for the timestamp function to MQE.

Compared to Prometheus' engine, timestamp runs up to 60% faster in MQE in our benchmarks:

goos: darwin
goarch: arm64
pkg: github.com/grafana/mimir/pkg/streamingpromql/benchmarks
cpu: Apple M1 Pro
                                                        │  Prometheus  │               Mimir                │
                                                        │    sec/op    │   sec/op     vs base               │
Query/timestamp(a_1),_instant_query-10                     142.5µ ± 2%   139.4µ ± 1%   -2.16% (p=0.002 n=6)
Query/timestamp(a_1),_range_query_with_100_steps-10        163.6µ ± 1%   146.2µ ± 1%  -10.67% (p=0.002 n=6)
Query/timestamp(a_1),_range_query_with_1000_steps-10       361.5µ ± 4%   193.7µ ± 1%  -46.41% (p=0.002 n=6)
Query/timestamp(a_100),_instant_query-10                   931.7µ ± 1%   775.5µ ± 6%  -16.76% (p=0.002 n=6)
Query/timestamp(a_100),_range_query_with_100_steps-10      2.111m ± 1%   1.269m ± 0%  -39.91% (p=0.002 n=6)
Query/timestamp(a_100),_range_query_with_1000_steps-10    12.139m ± 0%   5.401m ± 0%  -55.51% (p=0.002 n=6)
Query/timestamp(a_2000),_instant_query-10                  12.37m ± 1%   10.48m ± 2%  -15.31% (p=0.002 n=6)
Query/timestamp(a_2000),_range_query_with_100_steps-10     36.39m ± 1%   19.30m ± 1%  -46.98% (p=0.002 n=6)
Query/timestamp(a_2000),_range_query_with_1000_steps-10   238.41m ± 0%   95.11m ± 1%  -60.11% (p=0.002 n=6)
geomean                                                    3.031m        1.948m       -35.74%

Compared to main, the changes to InstantVectorSelector do introduce some additional latency, but the absolute differences are small and would likely be noise in the context of a more complex query:

goos: darwin
goarch: arm64
pkg: github.com/grafana/mimir/pkg/streamingpromql/benchmarks
cpu: Apple M1 Pro
                                                                                      │   main.txt   │             after.txt              │
                                                                                      │    sec/op    │    sec/op     vs base              │
Query/a_1,_instant_query/engine=Mimir-10                                                138.6µ ±  5%   147.5µ ±  8%  +6.38% (p=0.004 n=6)
Query/a_1,_range_query_with_100_steps/engine=Mimir-10                                   147.6µ ± 12%   152.2µ ±  2%       ~ (p=0.394 n=6)
Query/a_1,_range_query_with_1000_steps/engine=Mimir-10                                  191.5µ ± 11%   203.7µ ±  2%       ~ (p=0.065 n=6)
Query/a_100,_instant_query/engine=Mimir-10                                              777.4µ ±  4%   794.4µ ±  1%       ~ (p=0.394 n=6)
Query/a_100,_range_query_with_100_steps/engine=Mimir-10                                 1.288m ±  4%   1.310m ±  3%       ~ (p=0.180 n=6)
Query/a_100,_range_query_with_1000_steps/engine=Mimir-10                                5.378m ±  0%   5.618m ±  3%  +4.45% (p=0.002 n=6)
Query/a_2000,_instant_query/engine=Mimir-10                                             10.39m ±  1%   10.53m ±  1%  +1.27% (p=0.002 n=6)
Query/a_2000,_range_query_with_100_steps/engine=Mimir-10                                19.23m ±  1%   19.48m ±  2%  +1.30% (p=0.002 n=6)
Query/a_2000,_range_query_with_1000_steps/engine=Mimir-10                               94.38m ±  1%   95.71m ±  1%  +1.41% (p=0.002 n=6)
Query/nh_1,_instant_query/engine=Mimir-10                                               180.3µ ± 10%   190.8µ ±  4%  +5.82% (p=0.041 n=6)
Query/nh_1,_range_query_with_100_steps/engine=Mimir-10                                  225.6µ ±  5%   242.4µ ±  7%  +7.45% (p=0.004 n=6)
Query/nh_1,_range_query_with_1000_steps/engine=Mimir-10                                 722.4µ ±  8%   728.2µ ±  7%       ~ (p=0.589 n=6)
Query/nh_100,_instant_query/engine=Mimir-10                                             4.681m ±  7%   4.824m ±  5%       ~ (p=0.310 n=6)
Query/nh_100,_range_query_with_100_steps/engine=Mimir-10                                8.680m ±  1%   8.836m ±  4%  +1.80% (p=0.004 n=6)
Query/nh_100,_range_query_with_1000_steps/engine=Mimir-10                               46.19m ±  1%   46.43m ±  3%       ~ (p=0.180 n=6)
Query/nh_2000,_instant_query/engine=Mimir-10                                            84.42m ±  1%   84.68m ±  4%  +0.31% (p=0.041 n=6)
Query/nh_2000,_range_query_with_100_steps/engine=Mimir-10                               153.6m ±  1%   154.1m ±  1%       ~ (p=0.818 n=6)
Query/nh_2000,_range_query_with_1000_steps/engine=Mimir-10                              802.4m ±  2%   812.3m ±  2%       ~ (p=0.310 n=6)

There are no noticeable changes to peak memory utilisation in our benchmarks.

Which issue(s) this PR fixes or relates to

Part of #10067

Checklist

• Tests updated.
• [n/a] Documentation added.
• [covered by Mimir Query Engine #10067] CHANGELOG.md updated - the order of entries should be [CHANGE], [FEATURE], [ENHANCEMENT], [BUGFIX].
• [n/a] about-versioning.md updated with experimental features.