7:51 a.m.
Moving to the new list...
I'm not seeing how that patch can have caused this, as an entry should
have already been removed from the LRU before hitting the changes in the
patch. I'll run some tests, though, and see what I can work out.
Daniel
On 1/28/19 1:49 PM, Kropelin, Adam via Nfs-ganesha-devel wrote:
This list has been deprecated. Please subscribe to the new devel list
at lists.nfs-ganesha.org.
After applying https://review.gerrithub.io/c/ffilz/nfs-ganesha/+/441566
our long-running test is showing continually increasing memory usage.
Eventually ganesha.nfsd consumes all memory in the box and we OOM.
Looking at a core, it appears that the mdcache lru contains far more
entries than the high water mark would normally allow.
We have…
CacheInode {
Dir_Chunk = 500000;
Entries_HWMark = 500000;
}
…and after we run for a while, we observe from a core (obtained at
runtime using gcore)...
(gdb) print lru_state
$8 = {entries_hiwat = 500000, entries_used = 2437134, chunks_hiwat =
100000, chunks_used = 2002, fds_system_imposed = 400000, fds_hard_limit
= 396000, fds_hiwat = 360000, fds_lowat = 200000, futility = 0,
per_lane_work = 50, biggest_window = 160000, prev_fd_count = 160,
prev_time = 1548692973, fd_state = 0}
So we have 2.4M entries with a high water mark of 500K. The difference
appears to account for the unexpected memory usage.
This seems to be new behavior after applying the above patch, although
it’s hard to be certain because earlier we hit the core with entries
being freed twice before running into the high memory usage.
Some more info from the core:
(gdb) print LRU
$2 = {{L1 = {q = {next = 0xe4788210, prev = 0x23a701f0}, id =
LRU_ENTRY_L1, size = 147689}, L2 = {q = {
next = 0x23a8b7b0, prev = 0xe478ef80}, id = LRU_ENTRY_L2, size
= 150}, cleanup = {q = {next = 0xcca1ff70,
prev = 0x139e2bf0}, id = LRU_ENTRY_CLEANUP, size = 748}, mtx =
{__data = {__lock = 0, __count = 0,
__owner = 0, __nusers = 0, __kind = 0, __spins = 0, __list =
{__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x1dd98360,
prev = 0x1100cc30}, id = LRU_ENTRY_L1,
size = 143935}, L2 = {q = {next = 0xfa204e0, prev = 0x1e26a0a0},
id = LRU_ENTRY_L2, size = 145}, cleanup = {
q = {next = 0xb26f8720, prev = 0x18f1810}, id =
LRU_ENTRY_CLEANUP, size = 811}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x4903dc0,
prev = 0x96cb4320}, id = LRU_ENTRY_L1,
size = 141362}, L2 = {q = {next = 0x2eea11f0, prev = 0x48fd050},
id = LRU_ENTRY_L2, size = 147}, cleanup = {
q = {next = 0xdc74e5b0, prev = 0xca6f990}, id =
LRU_ENTRY_CLEANUP, size = 817}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x79dcf850,
prev = 0x7d9445d0}, id = LRU_ENTRY_L1,
size = 122171}, L2 = {q = {next = 0x7e823b30, prev = 0x79dcfc90},
id = LRU_ENTRY_L2, size = 146}, cleanup = {
q = {next = 0x3245ddb0, prev = 0x1121e510}, id =
LRU_ENTRY_CLEANUP, size = 761}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x1a94af70,
prev = 0xec32de0}, id = LRU_ENTRY_L1,
size = 142951}, L2 = {q = {next = 0xec25300, prev = 0x1a944200},
id = LRU_ENTRY_L2, size = 150}, cleanup = {
q = {next = 0xcf8eada0, prev = 0xba9afd0}, id =
LRU_ENTRY_CLEANUP, size = 759}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x49b54c90,
prev = 0x1896b90}, id = LRU_ENTRY_L1,
size = 133691}, L2 = {q = {next = 0x413dbca0, prev = 0x66d15ce0},
id = LRU_ENTRY_L2, size = 142}, cleanup = {
q = {next = 0xe249dcb0, prev = 0x135e9ae0}, id =
LRU_ENTRY_CLEANUP, size = 804}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x25eba620,
prev = 0x96783780}, id = LRU_ENTRY_L1,
---Type <return> to continue, or q <return> to quit---
size = 146051}, L2 = {q = {next = 0x1d179420, prev = 0x25eb38b0},
id = LRU_ENTRY_L2, size = 150}, cleanup = {
q = {next = 0xab572d30, prev = 0x11a0d550}, id =
LRU_ENTRY_CLEANUP, size = 765}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x15bc6d50,
prev = 0x3c292070}, id = LRU_ENTRY_L1,
size = 135767}, L2 = {q = {next = 0x5d1fad10, prev = 0x15bbffe0},
id = LRU_ENTRY_L2, size = 148}, cleanup = {
q = {next = 0x5b5c1490, prev = 0x88016f0}, id =
LRU_ENTRY_CLEANUP, size = 720}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x67772f0,
prev = 0x964eb1b0}, id = LRU_ENTRY_L1,
size = 140729}, L2 = {q = {next = 0x30d68c80, prev = 0x6770580},
id = LRU_ENTRY_L2, size = 147}, cleanup = {
q = {next = 0xc4710dd0, prev = 0x874dc10}, id =
LRU_ENTRY_CLEANUP, size = 791}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x5d1c210,
prev = 0x302682d0}, id = LRU_ENTRY_L1,
size = 140670}, L2 = {q = {next = 0x3026f040, prev = 0x5d154a0},
id = LRU_ENTRY_L2, size = 147}, cleanup = {
q = {next = 0xcb5487f0, prev = 0xc679490}, id =
LRU_ENTRY_CLEANUP, size = 794}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0xe2791600,
prev = 0x96252be0}, id = LRU_ENTRY_L1,
size = 148189}, L2 = {q = {next = 0xec06a870, prev = 0xe2798370},
id = LRU_ENTRY_L2, size = 145}, cleanup = {
q = {next = 0xa4dec380, prev = 0xb29dc50}, id =
LRU_ENTRY_CLEANUP, size = 746}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0xe5dff590,
prev = 0x23d43b90}, id = LRU_ENTRY_L1,
size = 147297}, L2 = {q = {next = 0x23de7e10, prev = 0xe5e06300},
id = LRU_ENTRY_L2, size = 141}, cleanup = {
q = {next = 0xa6b8d390, prev = 0x10229cb0}, id =
LRU_ENTRY_CLEANUP, size = 744}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x1cc790a0,
prev = 0x4ba049f0}, id = LRU_ENTRY_L1,
size = 143750}, L2 = {q = {next = 0xf39d9d0, prev = 0x1cc72330},
id = LRU_ENTRY_L2, size = 147}, cleanup = {
---Type <return> to continue, or q <return> to quit---
q = {next = 0xd37ff620, prev = 0x13b47010}, id =
LRU_ENTRY_CLEANUP, size = 780}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0xeaf4fd00,
prev = 0x25ab91d0}, id = LRU_ENTRY_L1,
size = 146505}, L2 = {q = {next = 0x25aa4980, prev = 0xeaf56a70},
id = LRU_ENTRY_L2, size = 150}, cleanup = {
q = {next = 0x23c6c110, prev = 0x11e02670}, id =
LRU_ENTRY_CLEANUP, size = 788}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0xe3dea010,
prev = 0x2831da50}, id = LRU_ENTRY_L1,
size = 148717}, L2 = {q = {next = 0x283247c0, prev = 0xe3df0d80},
id = LRU_ENTRY_L2, size = 149}, cleanup = {
q = {next = 0xb84809e0, prev = 0x87cee00}, id =
LRU_ENTRY_CLEANUP, size = 850}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0xce3ced10,
prev = 0xd5f2db20}, id = LRU_ENTRY_L1,
size = 153934}, L2 = {q = {next = 0xd5f12560, prev = 0xce3d5a80},
id = LRU_ENTRY_L2, size = 149}, cleanup = {
q = {next = 0xca840ac0, prev = 0xda6b170}, id =
LRU_ENTRY_CLEANUP, size = 779}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}, {L1 = {q = {next = 0x2d292f90,
prev = 0x17851300}, id = LRU_ENTRY_L1,
size = 138008}, L2 = {q = {next = 0x1786c8c0, prev = 0x2d2854b0},
id = LRU_ENTRY_L2, size = 147}, cleanup = {
q = {next = 0xc7c1e980, prev = 0xb2a3820}, id =
LRU_ENTRY_CLEANUP, size = 761}, mtx = {__data = {__lock = 0,
__count = 0, __owner = 0, __nusers = 0, __kind = 0, __spins =
0, __list = {__prev = 0x0, __next = 0x0}},
__size = '\000' <repeats 39 times>, __align = 0}, iter = {active
= false, glist = 0x0, glistn = 0x0},
__pad0 = '\000' <repeats 63 times>}}
(gdb)
(gdb) print *(struct mdcache_lru__ *)0xe4788210
$3 = {q = {next = 0xe47814a0, prev = 0x7e0620 <LRU>}, qid =
LRU_ENTRY_L1, refcnt = 1, flags = 0, lane = 0, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xe47814a0
$5 = {q = {next = 0xe477a730, prev = 0xe4788210}, qid = LRU_ENTRY_L1,
refcnt = 1, flags = 0, lane = 0, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xe477a730
$6 = {q = {next = 0xe47739c0, prev = 0xe47814a0}, qid = LRU_ENTRY_L1,
refcnt = 1, flags = 0, lane = 0, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xe47739c0
$7 = {q = {next = 0xe476cc50, prev = 0xe477a730}, qid = LRU_ENTRY_L1,
refcnt = 1, flags = 0, lane = 0, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xb84809e0
$8 = {q = {next = 0xaa559720, prev = 0x7e12a0 <LRU+3200>}, qid =
LRU_ENTRY_CLEANUP, refcnt = 3, flags = 3,
lane = 14, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xaa559720
$9 = {q = {next = 0xd9754930, prev = 0xb84809e0}, qid =
LRU_ENTRY_CLEANUP, refcnt = 3, flags = 3, lane = 14, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xd9754930
$10 = {q = {next = 0xa94e7f40, prev = 0xaa559720}, qid =
LRU_ENTRY_CLEANUP, refcnt = 2, flags = 3, lane = 14, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xa94e7f40
$11 = {q = {next = 0x185aa7d0, prev = 0xd9754930}, qid =
LRU_ENTRY_CLEANUP, refcnt = 3, flags = 3, lane = 14, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0x185aa7d0
$12 = {q = {next = 0xcb912a30, prev = 0xa94e7f40}, qid =
LRU_ENTRY_CLEANUP, refcnt = 1, flags = 3, lane = 14, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xcb912a30
$13 = {q = {next = 0xc7727370, prev = 0x185aa7d0}, qid =
LRU_ENTRY_CLEANUP, refcnt = 2, flags = 3, lane = 14, cf = 0}
(gdb)
$14 = {q = {next = 0xc7727370, prev = 0x185aa7d0}, qid =
LRU_ENTRY_CLEANUP, refcnt = 2, flags = 3, lane = 14, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xf39d9d0
$15 = {q = {next = 0xf3a4740, prev = 0x7e10c0 <LRU+2720>}, qid =
LRU_ENTRY_L2, refcnt = 1, flags = 0, lane = 12,
cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xf3a4740
$16 = {q = {next = 0xf3ab4b0, prev = 0xf39d9d0}, qid = LRU_ENTRY_L2,
refcnt = 1, flags = 0, lane = 12, cf = 0}
(gdb) print *(struct mdcache_lru__ *)0xf3ab4b0
$17 = {q = {next = 0xf3b2220, prev = 0xf3a4740}, qid = LRU_ENTRY_L2,
refcnt = 1, flags = 0, lane = 12, cf = 0}
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3:12 p.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
The issue is very reproducible. Just takes a few hours. If there is any debug info you
would like turned on, I'd be glad to enable it and re-run the test.
The test workload that causes this:
Concurrent access from multiple threads. 1 thread continuously (in a loop) running python
os.walk (i.e., readdir) of the entire filesystem, roughly ~5M files total. 5 more threads
are writing a few thousand files each. When the writes complete, a single thread verifies
written content, then deletes it. Then the writes repeat again.
I did see about 97,000 of the following messages in a few minutes of enabling debug:
LogDebugAlt(COMPONENT_NFS_READDIR, COMPONENT_CACHE_INODE,
"Already existent when inserting new dirent on entry=%p
name=%s",
entry, v->name);
LogFullDebugAlt(COMPONENT_NFS_READDIR, COMPONENT_CACHE_INODE,
"Duplicate insert of %s v->chunk=%p
v2->chunk=%p",
v->name, v->chunk, v2->chunk);
7:58 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
So, this is interesting, since it means that entries are being reaped.
There are dirents for entries that don't exist, so re-adding the entry
is colliding with the existing dirent.
If you stop the load and wait a while, does the number of entries go down?
On Tue, Jan 29, 2019 at 4:13 PM <vrungta(a)amazon.com> wrote:
>
> The issue is very reproducible. Just takes a few hours. If there is any debug info
you would like turned on, I'd be glad to enable it and re-run the test.
>
> The test workload that causes this:
> Concurrent access from multiple threads. 1 thread continuously (in a loop) running
python
> os.walk (i.e., readdir) of the entire filesystem, roughly ~5M files total. 5 more
threads
> are writing a few thousand files each. When the writes complete, a single thread
verifies
> written content, then deletes it. Then the writes repeat again.
>
> I did see about 97,000 of the following messages in a few minutes of enabling debug:
> LogDebugAlt(COMPONENT_NFS_READDIR, COMPONENT_CACHE_INODE,
> "Already existent when inserting new dirent on entry=%p
name=%s",
> entry, v->name);
> LogFullDebugAlt(COMPONENT_NFS_READDIR, COMPONENT_CACHE_INODE,
> "Duplicate insert of %s v->chunk=%p
v2->chunk=%p",
> v->name, v->chunk, v2->chunk);
> _______________________________________________
> Devel mailing list -- devel(a)lists.nfs-ganesha.org
> To unsubscribe send an email to devel-leave(a)lists.nfs-ganesha.org
11:03 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
I stopped the tests and waited 90 minutes. The number of entries did not go down at all.
Few minutes before stopping the tests:
(gdb) print lru_state
$1 = {entries_hiwat = 500000, entries_used = 954943, chunks_hiwat = 100000, chunks_used =
1742,
fds_system_imposed = 400000, fds_hard_limit = 396000, fds_hiwat = 360000, fds_lowat =
200000,
futility = 0, per_lane_work = 50, biggest_window = 160000, prev_fd_count = 0,
prev_time = 1548862024, fd_state = 0}
30 minutes after stopping the tests:
(gdb) print lru_state
$1 = {entries_hiwat = 500000, entries_used = 954944, chunks_hiwat = 100000, chunks_used =
1742,
fds_system_imposed = 400000, fds_hard_limit = 396000, fds_hiwat = 360000, fds_lowat =
200000,
futility = 0, per_lane_work = 50, biggest_window = 160000, prev_fd_count = 0,
prev_time = 1548863824, fd_state = 0}
90 minutes after stopping the tests:
(gdb) print lru_state
$1 = {entries_hiwat = 500000, entries_used = 954944, chunks_hiwat = 100000, chunks_used =
1742,
fds_system_imposed = 400000, fds_hard_limit = 396000, fds_hiwat = 360000, fds_lowat =
200000,
futility = 0, per_lane_work = 50, biggest_window = 160000, prev_fd_count = 0,
prev_time = 1548867350, fd_state = 0}
11:22 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
Okay, we're leaking a ref somewhere. I'll see if I can track it down.
On Wed, Jan 30, 2019 at 12:03 PM <vrungta(a)amazon.com> wrote:
>
> I stopped the tests and waited 90 minutes. The number of entries did not go down at
all.
>
> Few minutes before stopping the tests:
>
> (gdb) print lru_state
> $1 = {entries_hiwat = 500000, entries_used = 954943, chunks_hiwat = 100000,
chunks_used = 1742,
> fds_system_imposed = 400000, fds_hard_limit = 396000, fds_hiwat = 360000, fds_lowat
= 200000,
> futility = 0, per_lane_work = 50, biggest_window = 160000, prev_fd_count = 0,
> prev_time = 1548862024, fd_state = 0}
>
> 30 minutes after stopping the tests:
> (gdb) print lru_state
> $1 = {entries_hiwat = 500000, entries_used = 954944, chunks_hiwat = 100000,
chunks_used = 1742,
> fds_system_imposed = 400000, fds_hard_limit = 396000, fds_hiwat = 360000, fds_lowat
= 200000,
> futility = 0, per_lane_work = 50, biggest_window = 160000, prev_fd_count = 0,
> prev_time = 1548863824, fd_state = 0}
>
> 90 minutes after stopping the tests:
> (gdb) print lru_state
> $1 = {entries_hiwat = 500000, entries_used = 954944, chunks_hiwat = 100000,
chunks_used = 1742,
> fds_system_imposed = 400000, fds_hard_limit = 396000, fds_hiwat = 360000, fds_lowat
= 200000,
> futility = 0, per_lane_work = 50, biggest_window = 160000, prev_fd_count = 0,
> prev_time = 1548867350, fd_state = 0}
> _______________________________________________
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7:35 p.m.
New subject: Metadata sync for create/update operations.
Hello,
I noticed that ganesha does not do metadata sync after operations like
create, remove, setattr etc., (with FSAL_VFS). According to NFSv3 RFC:
"The following data modifying procedures are
synchronous: WRITE (with stable flag set to FILE_SYNC), CREATE,
MKDIR, SYMLINK, MKNOD, REMOVE, RMDIR, RENAME, LINK, and COMMIT.
Kernel NFS calls commit_metadata() to sync - see create procedure below:
https://elixir.bootlin.com/linux/latest/source/fs/nfsd/vfs.c#L1460
Is this to improve performance or a bug?
Thanks,
Pradeep
10:18 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
In case it helps -- As an experiment I set Dir_Chunk = 0 and ran the same test load. I
was not able to reproduce the issue. LRU entries stayed at the HW mark.
1:24 p.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
So, I've been unable so far to reproduce this with the workloads I'm
using. I'll have to try to replicate your workload more closely. I
don't suppose you can share the test program you're running?
On Thu, Jan 31, 2019 at 11:18 AM <vrungta(a)amazon.com> wrote:
>
> In case it helps -- As an experiment I set Dir_Chunk = 0 and ran the same test load.
I was not able to reproduce the issue. LRU entries stayed at the HW mark.
> _______________________________________________
> Devel mailing list -- devel(a)lists.nfs-ganesha.org
> To unsubscribe send an email to devel-leave(a)lists.nfs-ganesha.org
6:47 p.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
Our test programs are very tightly coupled to our test environment. We'll try to see
if we can eliminate the dependencies and get something useful
Meanwhile here's complete details on our workload.
Pre condition:
Create a subdirectory with 2000 subdirectories and 2500 1K files in each subdir for a
total of 5 million files.
One thread doing a python (os.walk) readdir of the entire share (pre-populated subdir as
well as the 2nd subdir where files are being created, deleted, recreated). This thread
continues for the duration of test.
One test run is 6 hours.
N files/dir, M dirs, S file size
Files to create are submitted to the thread pool in the following order:
Dir1/file1, Dir2/file1, DirM/file1, Dir1/file2, Dir2/file2..
5 threads will pull work from the thread pool and create files.
Once the writes are complete, one thread will read the files, verify MD5 and then delete
them. The process repeats. N,M,S stay constant for the test run.
The names of the files in the 2nd iteration are the same as the first iteration.
After 6 hours the test run is repeated with a different set of N,M,S and the readdir
thread is restarted.
N is one of 10, 50, 100, 500, 1000
M is from 1 to 10
S is one if 1K, 5K, 10K, 50K, 100K, 500K, 1M, 5M, 10M, 50M
One other thought:
The new code in cih_get_by_key_latch will now return not found even though it is still in
the hash with a refcount of 0. mdcache_new_entry will go through oentry=NULL and will add
the new entry to the hash (avltree?). Can this result in collisions between the oentry
that still exists and the new entry being added?
8:33 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
Thanks. I'll see what I can whip up quickly.
Daniel
On 1/31/19 7:47 PM, vrungta(a)amazon.com wrote:
Our test programs are very tightly coupled to our test environment.
We'll try to see if we can eliminate the dependencies and get something useful
Meanwhile here's complete details on our workload.
Pre condition:
Create a subdirectory with 2000 subdirectories and 2500 1K files in each subdir for a
total of 5 million files.
One thread doing a python (os.walk) readdir of the entire share (pre-populated subdir as
well as the 2nd subdir where files are being created, deleted, recreated). This thread
continues for the duration of test.
One test run is 6 hours.
N files/dir, M dirs, S file size
Files to create are submitted to the thread pool in the following order:
Dir1/file1, Dir2/file1, DirM/file1, Dir1/file2, Dir2/file2..
5 threads will pull work from the thread pool and create files.
Once the writes are complete, one thread will read the files, verify MD5 and then delete
them. The process repeats. N,M,S stay constant for the test run.
The names of the files in the 2nd iteration are the same as the first iteration.
After 6 hours the test run is repeated with a different set of N,M,S and the readdir
thread is restarted.
N is one of 10, 50, 100, 500, 1000
M is from 1 to 10
S is one if 1K, 5K, 10K, 50K, 100K, 500K, 1M, 5M, 10M, 50M
One other thought:
The new code in cih_get_by_key_latch will now return not found even though it is still in
the hash with a refcount of 0. mdcache_new_entry will go through oentry=NULL and will add
the new entry to the hash (avltree?). Can this result in collisions between the oentry
that still exists and the new entry being added?
_______________________________________________
Devel mailing list -- devel(a)lists.nfs-ganesha.org
To unsubscribe send an email to devel-leave(a)lists.nfs-ganesha.org
10:48 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
Okay, I'm able to reproduce this. But, more importantly, I'm able to
reproduce is on stock 2.7.1, so it's not caused by the recent changes.
I haven't yet checked next, I'll do that, well, next.
Daniel
On 2/1/19 9:33 AM, Daniel Gryniewicz wrote:
Thanks. I'll see what I can whip up quickly.
Daniel
On 1/31/19 7:47 PM, vrungta(a)amazon.com wrote:
> Our test programs are very tightly coupled to our test environment.
> We'll try to see if we can eliminate the dependencies and get
> something useful
> Meanwhile here's complete details on our workload.
> Pre condition:
> Create a subdirectory with 2000 subdirectories and 2500 1K files in
> each subdir for a total of 5 million files.
> One thread doing a python (os.walk) readdir of the entire share
> (pre-populated subdir as well as the 2nd subdir where files are being
> created, deleted, recreated). This thread continues for the duration
> of test.
> One test run is 6 hours.
> N files/dir, M dirs, S file size
> Files to create are submitted to the thread pool in the following order:
> Dir1/file1, Dir2/file1, DirM/file1, Dir1/file2, Dir2/file2..
> 5 threads will pull work from the thread pool and create files.
> Once the writes are complete, one thread will read the files, verify
> MD5 and then delete them. The process repeats. N,M,S stay constant
> for the test run.
> The names of the files in the 2nd iteration are the same as the first
> iteration.
> After 6 hours the test run is repeated with a different set of N,M,S
> and the readdir thread is restarted.
> N is one of 10, 50, 100, 500, 1000
> M is from 1 to 10
> S is one if 1K, 5K, 10K, 50K, 100K, 500K, 1M, 5M, 10M, 50M
> One other thought:
> The new code in cih_get_by_key_latch will now return not found even
> though it is still in the hash with a refcount of 0.
> mdcache_new_entry will go through oentry=NULL and will add the new
> entry to the hash (avltree?). Can this result in collisions between
> the oentry that still exists and the new entry being added?
> _______________________________________________
> Devel mailing list -- devel(a)lists.nfs-ganesha.org
> To unsubscribe send an email to devel-leave(a)lists.nfs-ganesha.org
>
9:19 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
This fixes it for me:
https://review.gerrithub.io/c/ffilz/nfs-ganesha/+/443260
I'm delaying 2.7.2 long enough to get this in, so it will likely come
out next Monday. I'll also include
25320e6544f6c5a045f20c51446f57c9dc036412 MDCACHE - Don't return dead
entries from hashtable
Daniel
On 2/1/19 11:48 AM, Daniel Gryniewicz wrote:
Okay, I'm able to reproduce this. But, more importantly, I'm
able to
reproduce is on stock 2.7.1, so it's not caused by the recent changes. I
haven't yet checked next, I'll do that, well, next.
Daniel
On 2/1/19 9:33 AM, Daniel Gryniewicz wrote:
> Thanks. I'll see what I can whip up quickly.
>
> Daniel
>
> On 1/31/19 7:47 PM, vrungta(a)amazon.com wrote:
>> Our test programs are very tightly coupled to our test environment.
>> We'll try to see if we can eliminate the dependencies and get
>> something useful
>> Meanwhile here's complete details on our workload.
>> Pre condition:
>> Create a subdirectory with 2000 subdirectories and 2500 1K files
>> in each subdir for a total of 5 million files.
>> One thread doing a python (os.walk) readdir of the entire share
>> (pre-populated subdir as well as the 2nd subdir where files are being
>> created, deleted, recreated). This thread continues for the duration
>> of test.
>> One test run is 6 hours.
>> N files/dir, M dirs, S file size
>> Files to create are submitted to the thread pool in the following order:
>> Dir1/file1, Dir2/file1, DirM/file1, Dir1/file2, Dir2/file2..
>> 5 threads will pull work from the thread pool and create files.
>> Once the writes are complete, one thread will read the files, verify
>> MD5 and then delete them. The process repeats. N,M,S stay constant
>> for the test run.
>> The names of the files in the 2nd iteration are the same as the first
>> iteration.
>> After 6 hours the test run is repeated with a different set of N,M,S
>> and the readdir thread is restarted.
>> N is one of 10, 50, 100, 500, 1000
>> M is from 1 to 10
>> S is one if 1K, 5K, 10K, 50K, 100K, 500K, 1M, 5M, 10M, 50M
>> One other thought:
>> The new code in cih_get_by_key_latch will now return not found even
>> though it is still in the hash with a refcount of 0.
>> mdcache_new_entry will go through oentry=NULL and will add the new
>> entry to the hash (avltree?). Can this result in collisions between
>> the oentry that still exists and the new entry being added?
>> _______________________________________________
>> Devel mailing list -- devel(a)lists.nfs-ganesha.org
>> To unsubscribe send an email to devel-leave(a)lists.nfs-ganesha.org
>>
>
10:18 a.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
Thanks Daniel. I will test with the fix and report back.
Vandana
7:28 p.m.
New subject: [Nfs-ganesha-devel] Memory growth in mdcache with entries_used >> entries_hiwat
The memory fix looks good. Thank you.
I continue to hit the crash I reported earlier in
https://lists.nfs-ganesha.org/archives/list/devel@lists.nfs-ganesha.org/t...
I will post additional details in that thread.
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vrungta＠amazon.com