Commit graph

256 commits

Author SHA1 Message Date
Joey Hess
49215d68ae
devblog 2016-02-14 18:01:35 -04:00
Joey Hess
cf260d9a15
Fix storing of filenames of v6 unlocked files when the filename is not representable in the current locale.
This is a mostly backwards compatable change. I broke backwards
compatability in the case where a filename starts with double-quote.
That seems likely to be very rare, and v6 unlocked files are a new feature
anyway, and fsck needs to fix missing associated file mappings anyway. So,
I decided that is good enough.

The encoding used is to just show the String when it contains a problem
character. While that adds some overhead to addAssociatedFile and
removeAssociatedFile, those are not called very often. This approach has
minimal decode overhead, because most filenames won't be encoded that way,
and it only has to look for the leading double-quote to skip the expensive
read. So, getAssociatedFiles remains fast.

I did consider using ByteString instead, but getting a FilePath converted
with all chars intact, even surrigates, is difficult, and it looks like
instance PersistField ByteString uses Text, which I don't trust for problem
encoded data. It would probably be slower too, and it would make the
database less easy to inspect manually.
2016-02-14 16:37:25 -04:00
Joey Hess
9df13e73ae
if keys database cannot be opened due to permissions, ignore
This lets readonly repos be used. If a repo is readonly, we can ignore the
keys database, because nothing that we can do will change the state of the
repo anyway.
2016-02-12 14:16:35 -04:00
Joey Hess
737e45156e
remove 163 lines of code without changing anything except imports 2016-01-20 16:36:33 -04:00
Joey Hess
927e1a067e
fix import warnings 2016-01-14 10:30:54 -04:00
Joey Hess
fd3d866dec
another fix for old ghc 2016-01-13 12:32:57 -04:00
Joey Hess
423fffcd41
change keys database to use IKey type with more efficient serialization
This breaks any existing keys database!

IKey serializes more efficiently than SKey, although this limits the
use of its Read/Show instances.

This makes the keys database use less disk space, and so should be a win.

Updated benchmark:

benchmarking keys database/getAssociatedFiles from 1000 (hit)
time                 64.04 μs   (63.95 μs .. 64.13 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 64.02 μs   (63.96 μs .. 64.08 μs)
std dev              218.2 ns   (172.5 ns .. 299.3 ns)

benchmarking keys database/getAssociatedFiles from 1000 (miss)
time                 52.53 μs   (52.18 μs .. 53.21 μs)
                     0.999 R²   (0.998 R² .. 1.000 R²)
mean                 52.31 μs   (52.18 μs .. 52.91 μs)
std dev              734.6 ns   (206.2 ns .. 1.623 μs)

benchmarking keys database/getAssociatedKey from 1000 (hit)
time                 64.60 μs   (64.46 μs .. 64.77 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 64.74 μs   (64.57 μs .. 65.20 μs)
std dev              900.2 ns   (389.7 ns .. 1.733 μs)

benchmarking keys database/getAssociatedKey from 1000 (miss)
time                 52.46 μs   (52.29 μs .. 52.68 μs)
                     1.000 R²   (0.999 R² .. 1.000 R²)
mean                 52.63 μs   (52.35 μs .. 53.37 μs)
std dev              1.362 μs   (562.7 ns .. 2.608 μs)
variance introduced by outliers: 24% (moderately inflated)

benchmarking keys database/addAssociatedFile to 1000 (old)
time                 487.3 μs   (484.7 μs .. 490.1 μs)
                     1.000 R²   (0.999 R² .. 1.000 R²)
mean                 490.9 μs   (487.8 μs .. 496.5 μs)
std dev              13.95 μs   (6.841 μs .. 22.03 μs)
variance introduced by outliers: 20% (moderately inflated)

benchmarking keys database/addAssociatedFile to 1000 (new)
time                 6.633 ms   (5.741 ms .. 7.751 ms)
                     0.905 R²   (0.850 R² .. 0.965 R²)
mean                 8.252 ms   (7.803 ms .. 8.602 ms)
std dev              1.126 ms   (900.3 μs .. 1.430 ms)
variance introduced by outliers: 72% (severely inflated)

benchmarking keys database/getAssociatedFiles from 10000 (hit)
time                 65.36 μs   (64.71 μs .. 66.37 μs)
                     0.998 R²   (0.995 R² .. 1.000 R²)
mean                 65.28 μs   (64.72 μs .. 66.45 μs)
std dev              2.576 μs   (920.8 ns .. 4.122 μs)
variance introduced by outliers: 42% (moderately inflated)

benchmarking keys database/getAssociatedFiles from 10000 (miss)
time                 52.34 μs   (52.25 μs .. 52.45 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 52.49 μs   (52.42 μs .. 52.59 μs)
std dev              255.4 ns   (205.8 ns .. 312.9 ns)

benchmarking keys database/getAssociatedKey from 10000 (hit)
time                 64.76 μs   (64.67 μs .. 64.84 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 64.67 μs   (64.62 μs .. 64.72 μs)
std dev              177.3 ns   (148.1 ns .. 217.1 ns)

benchmarking keys database/getAssociatedKey from 10000 (miss)
time                 52.75 μs   (52.66 μs .. 52.82 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 52.69 μs   (52.63 μs .. 52.75 μs)
std dev              210.6 ns   (173.7 ns .. 265.9 ns)

benchmarking keys database/addAssociatedFile to 10000 (old)
time                 489.7 μs   (488.7 μs .. 490.7 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 490.4 μs   (489.6 μs .. 492.2 μs)
std dev              3.990 μs   (2.435 μs .. 7.604 μs)

benchmarking keys database/addAssociatedFile to 10000 (new)
time                 9.994 ms   (9.186 ms .. 10.74 ms)
                     0.959 R²   (0.928 R² .. 0.979 R²)
mean                 9.906 ms   (9.343 ms .. 10.40 ms)
std dev              1.384 ms   (1.051 ms .. 2.100 ms)
variance introduced by outliers: 69% (severely inflated)
2016-01-12 14:01:50 -04:00
Joey Hess
75f61df323
cleanup 2016-01-12 13:31:13 -04:00
Joey Hess
ca2a527e93
add FileKeyIndex to Keys db to optimize getAssociatedKey
This is a schema change so will break any existing keys databases. But,
it's not been released yet, so I'm still able to make such changes.

This speeds up the benchmark quite nicely:

benchmarking keys database/getAssociatedKey from 1000 (hit)
time                 91.65 μs   (91.48 μs .. 91.81 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 91.78 μs   (91.66 μs .. 91.94 μs)
std dev              468.3 ns   (353.1 ns .. 624.3 ns)

benchmarking keys database/getAssociatedKey from 1000 (miss)
time                 53.33 μs   (53.23 μs .. 53.40 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 53.43 μs   (53.36 μs .. 53.53 μs)
std dev              274.2 ns   (211.7 ns .. 361.5 ns)

benchmarking keys database/getAssociatedKey from 10000 (hit)
time                 92.99 μs   (92.74 μs .. 93.27 μs)
                     1.000 R²   (1.000 R² .. 1.000 R²)
mean                 92.90 μs   (92.76 μs .. 93.16 μs)
std dev              608.7 ns   (404.1 ns .. 963.5 ns)

benchmarking keys database/getAssociatedKey from 10000 (miss)
time                 53.12 μs   (52.91 μs .. 53.39 μs)
                     1.000 R²   (0.999 R² .. 1.000 R²)
mean                 52.84 μs   (52.68 μs .. 53.16 μs)
std dev              715.4 ns   (400.4 ns .. 1.370 μs)
2016-01-12 13:07:14 -04:00
Joey Hess
f9c5aa84e0
add database benchmark
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)
2016-01-12 13:07:03 -04:00
Joey Hess
8111eb21e6
split out raw sql interface 2016-01-11 15:52:11 -04:00
Joey Hess
b1a1b40a15
fix inverted logic in old associated files cleanup 2016-01-07 15:54:10 -04:00
Joey Hess
aa4f353e5d
clarify absPathFrom
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.
2016-01-05 17:33:48 -04:00
Joey Hess
b3d60ca285
use TopFilePath for associated files
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.
2016-01-05 17:22:19 -04:00
Joey Hess
ec28151722
improve data type 2016-01-01 15:56:24 -04:00
Joey Hess
f7256842cc
wait for git lstree to exit 2016-01-01 15:51:29 -04:00
Joey Hess
9b99595473
only do scan when there's a branch, not in freshly created new repo 2016-01-01 15:16:16 -04:00
Joey Hess
f36f24197a
scan for unlocked files on init/upgrade of v6 repo 2016-01-01 15:09:42 -04:00
Joey Hess
bcdc6db2c3
fix build with pre-AMP ghc 2015-12-28 17:21:26 -04:00
Joey Hess
b61575516b
fix build with pre-AMP GHC 2015-12-28 12:41:47 -04:00
Joey Hess
9d3474ef1b
unused import 2015-12-24 13:07:42 -04:00
Joey Hess
c21567dfd3
typo 2015-12-24 13:06:03 -04:00
Joey Hess
4224fae71f
optimise read and write for Keys database (untested)
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
2015-12-23 19:18:52 -04:00
Joey Hess
959b060e26
allow flushDbQueue to be run repeatedly 2015-12-23 16:36:08 -04:00
Joey Hess
d43ac8056b
auto-close database connections when MVar is GCed 2015-12-23 16:11:36 -04:00
Joey Hess
6d38f54db4
split out Database.Queue from Database.Handle
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.
2015-12-23 14:59:58 -04:00
Joey Hess
38a23928e9
temporarily remove cached keys database connection
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.
2015-12-16 14:05:26 -04:00
Joey Hess
622da992f8
reorder database shutdown to be concurrency safe
If a DbHandle is in use by another thread, it could be queueing changes
while shutdown is running. So, wait for the worker to finish before
flushing the queue, so that any last-minute writes are included. Before
this fix, they would be silently dropped.

Of course, if the other thread continues to try to use a DbHandle once it's
closed, it will block forever as the worker is no longer reading from the
jobs MVar. So, that would crash with
"thread blocked indefinitely in an MVar operation".
2015-12-16 13:52:43 -04:00
Joey Hess
1a051f4300
comment 2015-12-16 13:24:45 -04:00
Joey Hess
0a7a2dae4e
add getAssociatedKey
I guess this is just as efficient as the getAssociatedFiles query, but I
have not tried to optimise the database yet.
2015-12-15 13:05:23 -04:00
Joey Hess
ce73a96e4e
use InodeCache when dropping a key to see if a pointer file can be safely reset
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.
2015-12-09 17:54:54 -04:00
Joey Hess
5e8c628d2e
add inode cache to the db
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
Joey Hess
05b598a057
stash DbHandle in Annex state 2015-12-09 14:55:47 -04:00
Joey Hess
a6e5ee0d0e
associated files database 2015-12-07 14:35:37 -04:00
Joey Hess
5072c62932
avoid ugly error about MVar if the sqlite worker thread crashes 2015-10-12 13:00:22 -04:00
Joey Hess
4ed82e5328 fsck: Work around bug in persistent that broke display of problematically encoded filenames on stderr when using --incremental. 2015-09-09 17:02:00 -04:00
Joey Hess
bc4129cc77 fsck: Commit incremental fsck database after every 1000 files fscked, or every 5 minutes, whichever comes first.
Previously, commits were made every 1000 files fscked.

Also, improve docs
2015-07-31 16:42:15 -04:00
Joey Hess
ecb0d5c087 use lock pools throughout git-annex
The one exception is in Utility.Daemon. As long as a process only
daemonizes once, which seems reasonable, and as long as it avoids calling
checkDaemon once it's already running as a daemon, the fcntl locking
gotchas won't be a problem there.

Annex.LockFile has it's own separate lock pool layer, which has been
renamed to LockCache. This is a persistent cache of locks that persist
until closed.

This is not quite done; lockContent stil needs to be converted.
2015-05-19 14:09:52 -04:00
Joey Hess
ec267aa1ea rejigger imports for clean build with ghc 7.10's AMP changes
The explict import Prelude after import Control.Applicative is a trick
to avoid a warning.
2015-05-10 16:20:30 -04:00
Joey Hess
addc82dab7 removed all uses of undefined from code base
It's a code smell, can lead to hard to diagnose error messages.
2015-04-19 00:38:29 -04:00
Joey Hess
5d974b26fc generated TH uses forall 2015-02-22 16:57:19 -04:00
Joey Hess
e143d5e7d1 avoid closing db handle when reconnecting to do a write 2015-02-22 14:21:39 -04:00
Joey Hess
bf80a16c2e complete work around for sqlite SELECT ErrorBusy on new connection bug 2015-02-22 14:08:26 -04:00
Joey Hess
b541a5e38b WIP 2015-02-18 17:46:58 -04:00
Joey Hess
a01285ff33 more extensions needed by newer version of persistent 2015-02-18 17:30:07 -04:00
Joey Hess
80683871ee deal with rare SELECT ErrorBusy failures
I think they might be a sqlite bug. In discussions with sqlite devs.
2015-02-18 16:56:52 -04:00
Joey Hess
af254615b2 use WAL mode to ensure read from db always works, even when it's being written to
Also, moved the database to a subdir, as there are multiple files.

This seems to work well with concurrent fscks, although they still do
redundant work due to the commit granularity. Occasionally two writes will
conflict, and one is then deferred and happens later.

Except, with 3 concurrent fscks, I got failures:

git-annex: user error (SQLite3 returned ErrorBusy while attempting to perform prepare "SELECT \"fscked\".\"key\"\nFROM \"fscked\"\nWHERE \"fscked\".\"key\" = ?\n": database is locked)

Argh!!!
2015-02-18 15:54:24 -04:00
Joey Hess
17cb219231 more robust handling of deferred commits
Still not robust enough. I have 3 fscks running concurrently, and am
seeing:

("commit deferred",user error (SQLite3 returned ErrorBusy while attempting
to perform step.))

and

git-annex: user error (SQLite3 returned ErrorBusy while attempting to perform prepare "SELECT \"fscked\".\"key\"\nFROM \"fscked\"\nWHERE \"fscked\".\"key\" = ?\n": database is locked)
2015-02-18 14:11:27 -04:00
Joey Hess
3414229354 fsck: Multiple incremental fscks of different repos (some remote) can now be in progress at the same time in the same repo without it getting confused about which files have been checked for which remotes. 2015-02-17 17:08:11 -04:00
Joey Hess
a3370ac459 allow for concurrent incremental fsck processes again (sorta)
Sqlite doesn't support multiple concurrent writers
at all. One of them will fail to write. It's not even possible to have two
processes building up separate transactions at the same time. Before using
sqlite, incremental fsck could work perfectly well with multiple fsck
processes running concurrently. I'd like to keep that working.

My partial solution, so far, is to make git-annex buffer writes, and every
so often send them all to sqlite at once, in a transaction. So most of the
time, nothing is writing to the database. (And if it gets unlucky and
a write fails due to a collision with another writer, it can just wait and
retry the write later.) This lets multiple processes write to the database
successfully.

But, for the purposes of concurrent, incremental fsck, it's not ideal.
Each process doesn't immediately learn of files that another process has
checked. So they'll tend to do redundant work.

Only way I can see to improve this is to use some other mechanism for
short-term IPC between the fsck processes. Not yet done.

----

Also, make addDb check if an item is in the database already, and not try
to re-add it. That fixes an intermittent crash with
"SQLite3 returned ErrorConstraint while attempting to perform step."

I am not 100% sure why; it only started happening when I moved write
buffering into the queue. It seemed to generally happen on the same file
each time, so could just be due to multiple files having the same key.
However, I doubt my sound repo has many duplicate keys, and I suspect
something else is going on.

----

Updated benchmark, with the 1000 item queue: 6m33.808s
2015-02-17 16:56:12 -04:00
Joey Hess
afb3e3e472 avoid crash when starting fsck --incremental when one is already running
Turns out sqlite does not like having its database deleted out from
underneath it. It might suffice to empty the table, but I would rather
start each fsck over with a new database, so I added a lock file, and
running incremental fscks use a shared lock.

This leaves one concurrency bug left; running two concurrent fsck --more
will lead to: "SQLite3 returned ErrorBusy while attempting to perform step."
and one or both will fail. This is a concurrent writers problem.
2015-02-17 13:30:24 -04:00
Joey Hess
ea76d04e15 show error when sqlite crashes worker thread
Better than "blocked indefinitely in MVar"..
2015-02-17 13:03:57 -04:00
Joey Hess
99a1287f4f avoid fromIntegral overhead 2015-02-16 17:22:00 -04:00
Joey Hess
7d36e7d18d commit new transaction after 60 seconds
Database.Handle can now be given a CommitPolicy, making it easy to specify
transaction granularity.

Benchmarking the old git-annex incremental fsck that flips sticky bits
to the new that uses sqlite, running in a repo with 37000 annexed files,
both from cold cache:

old: 6m6.906s
new: 6m26.913s

This commit was sponsored by TasLUG.
2015-02-16 17:05:42 -04:00
Joey Hess
d2766df914 commit more transactions when fscking
This makes interrupt and resume work, robustly.

But, incremental fsck is slowed down by all those transactions..
2015-02-16 16:07:36 -04:00
Joey Hess
91e9146d1b convert incremental fsck to using sqlite database
Did not keep backwards compat for sticky bit records. An incremental fsck
that is already in progress will start over on upgrade to this version.

This is not yet ready for merging. The autobuilders need to have sqlite
installed.

Also, interrupting a fsck --incremental does not commit the database.
So, resuming with fsck --more restarts from beginning.

Memory: Constant during a fsck of tens of thousands of files.
(But, it does seem to buffer whole transation in memory, so
may really scale with number of files.)

CPU: ?
2015-02-16 15:35:26 -04:00