In some local tests w/ a slowed down filesystem, this massively cut down
on the time to clean up a repository by ~3x, bringing a total 'publish
update' time from ~16s to ~13s.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>

When merging reflists with ignoreConflicting set to true and
overrideMatching set to false, the individual ref components are never
examined, but the refs are still split anyway. Avoiding the split when
we never use the components brings a massive speedup: on my system, the
included benchmark goes from ~1500 us/it to ~180 us/it.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>

The cleanup phase needs to list out all the files in each component in
order to determine what's still in use. When there's a large number of
sources (e.g. from having many snapshots), the time spent just loading
the package information becomes substantial. However, in many cases,
most of the packages being loaded are actually shared across the
sources; if you're taking frequent snapshots, for instance, most of the
packages in each snapshot will be the same as other snapshots. In these
cases, re-reading the packages repeatedly is just a waste of time.

To improve this, we maintain a list of refs that we know were processed
for each component. When listing the refs from a source, only the ones
that have not yet been processed will be examined. Some tests were also
added specifically to check listing the files in a component.

With this change, listing the files in components on a copy of our
production database went from >10 minutes to ~10 seconds, and the newly
added benchmark went from ~300ms to ~43ms.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>

Reflists are basically stored as arrays of strings, which are quite
space-efficient in MessagePack. Thus, using zero-copy decoding results
in nice performance and memory savings, because the overhead of separate
allocations ends up far exceeding the overhead of the original slice.

With the included benchmark run for 20s with -benchmem, the runtime,
memory usage, and allocations go from ~740us/op, ~192KiB/op, and 4100
allocs/op to ~240us/op, ~97KiB/op, and 13 allocs/op, respectively.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>

The output doesn't actually depend on the reflists, and loading them for
every published repo starts to take substantial time and memory.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>

The previous reflist logic would early-exit the loop body if one of the
lists was empty, but that skips the compacting logic entirely.

Instead of doing the early-exit, we can leave a list's ref as nil when
the list end is reached and then flip the comparison result, which will
essentially treat it as being greater than all others. This should
preserve the general behavior without omitting the compaction.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>

In current aptly, each repository and snapshot has its own reflist in
the database. This brings a few problems with it:

- Given a sufficiently large repositories and snapshots, these lists can
  get enormous, reaching >1MB. This is a problem for LevelDB's overall
  performance, as it tends to prefer values around the confiruged block
  size (defaults to just 4KiB).
- When you take these large repositories and snapshot them, you have a
  full, new copy of the reflist, even if only a few packages changed.
  This means that having a lot of snapshots with a few changes causes
  the database to basically be full of largely duplicate reflists.
- All the duplication also means that many of the same refs are being
  loaded repeatedly, which can cause some slowdown but, more notably,
  eats up huge amounts of memory.
- Adding on more and more new repositories and snapshots will cause the
  time and memory spent on things like cleanup and publishing to grow
  roughly linearly.

At the core, there are two problems here:

- Reflists get very big because there are just a lot of packages.
- Different reflists can tend to duplicate much of the same contents.

*Split reflists* aim at solving this by separating reflists into 64
*buckets*. Package refs are sorted into individual buckets according to
the following system:

- Take the first 3 letters of the package name, after dropping a `lib`
  prefix. (Using only the first 3 letters will cause packages with
  similar prefixes to end up in the same bucket, under the assumption
  that packages with similar names tend to be updated together.)
- Take the 64-bit xxhash of these letters. (xxhash was chosen because it
  relatively good distribution across the individual bits, which is
  important for the next step.)
- Use the first 6 bits of the hash (range [0:63]) as an index into the
  buckets.

Once refs are placed in buckets, a sha256 digest of all the refs in the
bucket is taken. These buckets are then stored in the database, split
into roughly block-sized segments, and all the repositories and
snapshots simply store an array of bucket digests.

This approach means that *repositories and snapshots can share their
reflist buckets*. If a snapshot is taken of a repository, it will have
the same contents, so its split reflist will point to the same buckets
as the base repository, and only one copy of each bucket is stored in
the database. When some packages in the repository change, only the
buckets containing those packages will be modified; all the other
buckets will remain unchanged, and thus their contents will still be
shared. Later on, when these reflists are loaded, each bucket is only
loaded once, short-cutting loaded many megabytes of data. In effect,
split reflists are essentially copy-on-write, with only the changed
buckets stored individually.

Changing the disk format means that a migration needs to take place, so
that task is moved into the database cleanup step, which will migrate
reflists over to split reflists, as well as delete any unused reflist
buckets.

All the reflist tests are also changed to additionally test out split
reflists; although the internal logic is all shared (since buckets are,
themselves, just normal reflists), some special additions are needed to
have native versions of the various reflist helper methods.

In our tests, we've observed the following improvements:

- Memory usage during publish and database cleanup, with
  `GOMEMLIMIT=2GiB`, goes down from ~3.2GiB (larger than the memory
  limit!) to ~0.7GiB, a decrease of ~4.5x.
- Database size decreases from 1.3GB to 367MB.

*In my local tests*, publish times had also decreased down to mere
seconds but the same effect wasn't observed on the server, with the
times staying around the same. My suspicions are that this is due to I/O
performance: my local system is an M1 MBP, which almost certainly has
much faster disk speeds than our DigitalOcean block volumes. Split
reflists include a side effect of requiring more random accesses from
reading all the buckets by their keys, so if your random I/O
performance is slower, it might cancel out the benefits. That being
said, even in that case, the memory usage and database size advantages
still persist.

Signed-off-by: Ryan Gonzalez <ryan.gonzalez@collabora.com>