In some rare cases files could be created which contain null IDs (all
zero) in their content list. This was caused by a race condition between
growing the `Content` slice and inserting the blob IDs into it. In some
cases the blob ID was written to the old slice, which a short time
afterwards was replaced with a larger copy, that did not yet contain the
blob ID.
We previously checked whether the set of snapshots might have changed
based only on their number, which fails when as many snapshots are
forgotten as are added. Check for the SHA-256 of their id's instead.
The status bar got stuck once the first error was reported, the scanner
completed or some file was backed up. Either case sets a flag that the
scanner has started.
This flag is used to hide the progress bar until the flag is set. Due to
an inverted condition, the opposite happened and the status stopped
refreshing once the flag was set.
In addition, the scannerStarted flag was not set when the scanner just
reported progress information.
As the FileSaver is asynchronously waiting for all blobs of a file to be
stored, the number of active files is higher than the number of files
from which restic is reading concurrently. Thus to not confuse users,
only display files in the status from which restic is currently reading.
After reading and chunking all data in a file, the FutureFile still has
to wait until the FutureBlobs are completed. This was done synchronously
which results in blocking the file saver and prevents the next file from
being read.
By replacing the FutureBlob with a callback, it becomes possible to
complete the FutureFile asynchronously.
We always need both values, except in a test, so we don't need to lock
twice and risk scheduling in between.
Also, removed the resetting in Done. This copied a mutex, which isn't
allowed. Static analyzers tend to trip over that.
The channel-based algorithm had grown quite complicated. This is easier
to reason about and likely to be more performant with very many
CompleteBlob calls.
As long as only a small fraction of the data in a repository is
rewritten, the keepBlobs set will be rather small after cleaning it up.
As golang maps do not shrink their memory usage, just copy the contents
over to a new map. However, only copy the map if the cleanup removed at
least half the entries.
The set covers necessary, existing and duplicate blobs. This removes the
duplicate sets used to track whether all necessary blobs also exist.
This reduces the memory usage of prune by about 20-30%.
