This commit adds a function to `KeySpace` which updates a key key space
by removing all overlaps with a second key space. This can involve
splitting or removing of existing ranges.
The implementation is not particularly efficient: O(M * N * log(N))
where N is the number of ranges in the current key space and M is the
number of ranges in the key space we are checking against. In practice,
this shouldn't matter much since, in the short term, the only caller of
this function will be the vectored read path and the number of key
spaces invovled will be small. This follows from the upper bound placed
on the number of keys accepted by the vectored read path.
A couple other small utility functions are added. They'll be used by the
vectored search path as well.
1. Introduce a naive `Timeline::get_vectored` implementation
The return type is intended to be flexible enough for various types of
callers. We return the pages in a map keyed by `Key` such that the
caller doesn't have to map back to the key if it needs to know it. Some
callers can ignore errors
for specific pages, so we return a separate `Result<Bytes,
PageReconstructError>` for each page and an overarching
`GetVectoredError` for API misuse. The overhead of the mapping will be
small and bounded since we enforce a maximum key count for the
operation.
2. Use the `get_vectored` API for SLRU segment reconstruction and image
layer creation.
PR #6266 broke the getpage_latest_lsn benchmark.
Before this patch, we'd fail with
```
not implemented: split up range
```
because `r.start = rel size key` and `r.end = rel size key + 1`.
The filtering of the key ranges in that loop is a bit ugly, but,
I measured:
* setup with 180k layer files (20k tenants * 9 layers).
* total physical size is 463GiB
* 5k tenants, the range filtering takes `0.6 seconds` on an
i3en.3xlarge.
That's a tiny fraction of the overall time it takes for pagebench to get
ready to send requests. So, this is good enough for now / there are
other bottlenecks that are bigger.
