Sparse files contain large regions containing only zero bytes. Checking
that a blob only contains zeros is possible with over 100GB/s for modern
x86 CPUs. Calculating sha256 hashes is only possible with 500MB/s (or
2GB/s using hardware acceleration). Thus we can speed up the hash
calculation for all zero blobs (which always have length
chunker.MinSize) by checking for zero bytes and then using the
precomputed hash.
The all zeros check is only performed for blobs with the minimal chunk
size, and thus should add no overhead most of the time. For chunks which
are not all zero but have the minimal chunks size, the overhead will be
below 2% based on the above performance numbers.
This allows reading sparse sections of files as fast as the kernel can
return data to us. On my system using BTRFS this resulted in about
4GB/s.
We can either preallocate storage for a file or sparsify it. This
detects a pack file as sparse if it contains an all zero block or
consists of only one block. As the file sparsification is just an
approximation, hide it behind a `--sparse` parameter.
Use runtime.GOMAXPROCS(0) as worker count for CPU-bound tasks,
repo.Connections() for IO-bound task and a combination if a task can be
both. Streaming packs is treated as IO-bound as adding more worker
cannot provide a speedup.
Typical IO-bound tasks are download / uploading / deleting files.
Decoding / Encoding / Verifying are usually CPU-bound. Several tasks are
a combination of both, e.g. for combined download and decode functions.
In the latter case add both limits together. As the backends have their
own concurrency limits restic still won't download more than
repo.Connections() files in parallel, but the additional workers can
decode already downloaded data in parallel.
Failed pack/blob downloads should be retried. For blobs that fail
decryption assume that the pack file is really damaged and try to
restore the remaining blobs.
Much simpler implementation that guarantees each required pack
is downloaded only once (and hence does not need to manage
pack cache). Also improves large file restore performance.
Signed-off-by: Igor Fedorenko <igor@ifedorenko.com>
don't create fileInfo structs for empty files. this saves memory.
this also avoids extra serial scan of all fileInfo, which should
make restore faster and more consistent.
Signed-off-by: Igor Fedorenko <igor@ifedorenko.com>
* uses less memory as common prefix is only stored once
* stepping stone for simpler error callback api, which
will allow further memory footprint reduction
Signed-off-by: Igor Fedorenko <igor@ifedorenko.com>
