The benchmark shows that the database access is quite fast indeed!
And, it scales linearly to the number of keys, with one exception,
getAssociatedKey.
Based on this benchmark, I don't think I need worry about optimising
for cases where all files are locked and the database is mostly empty.
In those cases, database access will be misses, and according to this
benchmark, should add only 50 milliseconds to runtime.
(NB: There may be some overhead to getting the database opened and locking
the handle that this benchmark doesn't see.)
joey@darkstar:~/src/git-annex>./git-annex benchmark
setting up database with 1000
setting up database with 10000
benchmarking keys database/getAssociatedFiles from 1000 (hit)
time 62.77 μs (62.70 μs .. 62.85 μs)
1.000 R² (1.000 R² .. 1.000 R²)
mean 62.81 μs (62.76 μs .. 62.88 μs)
std dev 201.6 ns (157.5 ns .. 259.5 ns)
benchmarking keys database/getAssociatedFiles from 1000 (miss)
time 50.02 μs (49.97 μs .. 50.07 μs)
1.000 R² (1.000 R² .. 1.000 R²)
mean 50.09 μs (50.04 μs .. 50.17 μs)
std dev 206.7 ns (133.8 ns .. 295.3 ns)
benchmarking keys database/getAssociatedKey from 1000 (hit)
time 211.2 μs (210.5 μs .. 212.3 μs)
1.000 R² (0.999 R² .. 1.000 R²)
mean 211.0 μs (210.7 μs .. 212.0 μs)
std dev 1.685 μs (334.4 ns .. 3.517 μs)
benchmarking keys database/getAssociatedKey from 1000 (miss)
time 173.5 μs (172.7 μs .. 174.2 μs)
1.000 R² (0.999 R² .. 1.000 R²)
mean 173.7 μs (173.0 μs .. 175.5 μs)
std dev 3.833 μs (1.858 μs .. 6.617 μs)
variance introduced by outliers: 16% (moderately inflated)
benchmarking keys database/getAssociatedFiles from 10000 (hit)
time 64.01 μs (63.84 μs .. 64.18 μs)
1.000 R² (1.000 R² .. 1.000 R²)
mean 64.85 μs (64.34 μs .. 66.02 μs)
std dev 2.433 μs (547.6 ns .. 4.652 μs)
variance introduced by outliers: 40% (moderately inflated)
benchmarking keys database/getAssociatedFiles from 10000 (miss)
time 50.33 μs (50.28 μs .. 50.39 μs)
1.000 R² (1.000 R² .. 1.000 R²)
mean 50.32 μs (50.26 μs .. 50.38 μs)
std dev 202.7 ns (167.6 ns .. 252.0 ns)
benchmarking keys database/getAssociatedKey from 10000 (hit)
time 1.142 ms (1.139 ms .. 1.146 ms)
1.000 R² (1.000 R² .. 1.000 R²)
mean 1.142 ms (1.140 ms .. 1.144 ms)
std dev 7.142 μs (4.994 μs .. 10.98 μs)
benchmarking keys database/getAssociatedKey from 10000 (miss)
time 1.094 ms (1.092 ms .. 1.096 ms)
1.000 R² (1.000 R² .. 1.000 R²)
mean 1.095 ms (1.095 ms .. 1.097 ms)
std dev 4.277 μs (2.591 μs .. 7.228 μs)
The repo path is typically relative, not absolute, so
providing it to absPathFrom doesn't yield an absolute path.
This is not a bug, just unclear documentation.
Indeed, there seem to be no reason to simplifyPath here, which absPathFrom
does, so instead just combine the repo path and the TopFilePath.
Also, removed an export of the TopFilePath constructor; asTopFilePath
is provided to construct one as-is.
Fixes several bugs with updates of pointer files. When eg, running
git annex drop --from localremote
it was updating the pointer file in the local repository, not the remote.
Also, fixes drop ../foo when run in a subdir, and probably lots of other
problems. Test suite drops from ~30 to 11 failures now.
TopFilePath is used to force thinking about what the filepath is relative
to.
The data stored in the sqlite db is still just a plain string, and
TopFilePath is a newtype, so there's no overhead involved in using it in
DataBase.Keys.
Writes are optimised by queueing up multiple writes when possible.
The queue is flushed after the Annex monad action finishes. That makes it
happen on program termination, and also whenever a nested Annex monad action
finishes.
Reads are optimised by checking once (per AnnexState) if the database
exists. If the database doesn't exist yet, all reads return mempty.
Reads also cause queued writes to be flushed, so reads will always be
consistent with writes (as long as they're made inside the same Annex monad).
A future optimisation path would be to determine when that's not necessary,
which is probably most of the time, and avoid flushing unncessarily.
Design notes for this commit:
- separate reads from writes
- reuse a handle which is left open until program
exit or until the MVar goes out of scope (and autoclosed then)
- writes are queued
- queue is flushed periodically
- immediate queue flush before any read
- auto-flush queue when database handle is garbage collected
- flush queue on exit from Annex monad
(Note that this may happen repeatedly for a single database connection;
or a connection may be reused for multiple Annex monad actions,
possibly even concurrent ones.)
- if database does not exist (or is empty) the handle
is not opened by reads; reads instead return empty results
- writes open the handle if it was not open previously
Fsck can use the queue for efficiency since it is write-heavy, and only
reads a value before writing it. But, the queue is not suited to the Keys
database.
The problem is that shutdown is not always called, particularly in the test
suite. So, a database connection would be opened, possibly some changes
queued, and then not shut down.
One way this can happen is when using Annex.eval or Annex.run with a new
state. A better fix might be to make both of them call Keys.shutdown
(and be sure to do it even if the annex action threw an error).
Complication: Sometimes they're run reusing an existing state, so shutting
down a database connection could cause problems for other users of that
same state. I think this would need a MVar holding the database handle,
so it could be emptied once shut down, and another user of the database
connection could then start up a new one if it got shut down. But, what if
2 threads were concurrently using the same database handle and one shut it
down while the other was writing to it? Urgh.
Might have to go that route eventually to get the database access to run
fast enough. For now, a quick fix to get the test suite happier, at the
expense of speed.
The Keys database can hold multiple inode caches for a given key. One for
the annex object, and one for each pointer file, which may not be hard
linked to it.
Inode caches for a key are recorded when its content is added to the annex,
but only if it has known pointer files. This is to avoid the overhead of
maintaining the database when not needed.
When the smudge filter outputs a file's content, the inode cache is not
updated, because git's smudge interface doesn't let us write the file. So,
dropping will fall back to doing an expensive verification then. Ideally,
git's interface would be improved, and then the inode cache could be
updated then too.
Renamed the db to keys, since it is various info about a Keys.
Dropping a key will update its pointer files, as long as their content can
be verified to be unmodified. This falls back to checksum verification, but
I want it to use an InodeCache of the key, for speed. But, I have not made
anything populate that cache yet.
2015-12-09 17:00:37 -04:00
Renamed from Database/AssociatedFiles.hs (Browse further)
