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5578f58bdc
Useful when looking for the info on ZFS/SPL related memory consumption. Signed-off-by: Boris Protopopov <boris.protopopov@actifio.com> Signed-off-by: Brian Behlendorf <behlendorf1@llnl.gov> Closes #460
203 lines
5.4 KiB
Python
Executable File
203 lines
5.4 KiB
Python
Executable File
#!/usr/bin/python
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import sys
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import time
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import getopt
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import re
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import signal
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from collections import defaultdict
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class Stat:
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# flag definitions based on the kmem.h
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NOTOUCH = 1
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NODEBUG = 2
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KMEM = 32
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VMEM = 64
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SLAB = 128
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OFFSLAB = 256
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NOEMERGENCY = 512
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DEADLOCKED = 16384
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GROWING = 32768
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REAPING = 65536
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DESTROY = 131072
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fdefs = {
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NOTOUCH : "NTCH",
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NODEBUG : "NDBG",
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KMEM : "KMEM",
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VMEM : "VMEM",
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SLAB : "SLAB",
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OFFSLAB : "OFSL",
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NOEMERGENCY : "NEMG",
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DEADLOCKED : "DDLK",
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GROWING : "GROW",
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REAPING : "REAP",
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DESTROY : "DSTR"
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}
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def __init__(self, name, flags, size, alloc, slabsize, objsize):
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self._name = name
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self._flags = self.f2str(flags)
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self._size = size
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self._alloc = alloc
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self._slabsize = slabsize
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self._objsize = objsize
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def f2str(self, flags):
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fstring = ''
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for k in Stat.fdefs.keys():
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if flags & k:
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fstring = fstring + Stat.fdefs[k] + '|'
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fstring = fstring[:-1]
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return fstring
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class CumulativeStat:
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def __init__(self, skey="a"):
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self._size = 0
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self._alloc = 0
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self._pct = 0
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self._skey = skey
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self._regexp = \
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re.compile('(\w+)\s+(\w+)\s+(\w+)\s+(\w+)\s+(\w+)\s+(\w+)\s+');
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self._stats = defaultdict(list)
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# Add another stat to the dictionary and re-calculate the totals
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def add(self, s):
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key = 0
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if self._skey == "a":
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key = s._alloc
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else:
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key = s._size
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self._stats[key].append(s)
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self._size = self._size + s._size
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self._alloc = self._alloc + s._alloc
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if self._size:
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self._pct = self._alloc * 100 / self._size
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else:
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self._pct = 0
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# Parse the slab info in the procfs
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# Calculate cumulative stats
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def slab_update(self):
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k = [line.strip() for line in open('/proc/spl/kmem/slab')]
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if not k:
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sys.stderr.write("No SPL slab stats found\n")
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sys.exit(1)
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del k[0:2]
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for s in k:
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if not s:
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continue
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m = self._regexp.match(s)
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if m:
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self.add(Stat(m.group(1), int(m.group(2),16), int(m.group(3)),
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int(m.group(4)), int(m.group(5)), int(m.group(6))))
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else:
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sys.stderr.write("Error: unexpected input format\n" % s)
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exit(-1)
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def show_header(self):
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sys.stdout.write("\n%25s %20s %15s %15s %15s %15s\n\n" % \
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("cache name", "flags", "size", "alloc", "slabsize", "objsize"))
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# Show up to the number of 'rows' of output sorted in descending order
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# by the key specified earlier; if rows == 0, all rows are shown
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def show(self, rows):
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self.show_header()
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i = 1
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done = False
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for k in reversed(sorted(self._stats.keys())):
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for s in self._stats[k]:
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sys.stdout.write("%25s %20s %15d %15d %15d %15d\n" % \
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(s._name, s._flags, s._size, s._alloc, \
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s._slabsize, s._objsize))
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i = i + 1
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if rows != 0 and i > rows:
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done = True
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break
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if done:
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break
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sys.stdout.write("%25s %36d %15d (%d%%)\n\n" % \
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("Totals:", self._size, self._alloc, self._pct))
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def usage():
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cmd = "Usage: splslab.py [-n|--num-rows] number [-s|--sort-by] " + \
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"[interval] [count]";
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sys.stderr.write("%s\n" % cmd)
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sys.stderr.write("\t-h : print help\n")
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sys.stderr.write("\t-n : --num-rows N : limit output to N top " +
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"largest slabs (default: all)\n")
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sys.stderr.write("\t-s : --sort-by key : sort output in descending " +
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"order by total size (s)\n\t\tor allocated size (a) " +
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"(default: a)\n")
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sys.stderr.write("\tinterval : repeat every interval seconds\n")
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sys.stderr.write("\tcount : output statistics count times and exit\n")
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def main():
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rows = 0
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count = 0
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skey = "a"
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interval = 1
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signal.signal(signal.SIGINT, signal.SIG_DFL)
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try:
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opts, args = getopt.getopt(
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sys.argv[1:],
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"n:s:h",
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[
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"num-rows",
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"sort-by",
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"help"
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]
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)
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except getopt.error as e:
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sys.stderr.write("Error: %s\n" % e.msg)
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usage()
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exit(-1)
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i = 1
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for opt, arg in opts:
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if opt in ('-n', '--num-rows'):
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rows = int(arg)
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i = i + 2
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elif opt in ('-s', '--sort-by'):
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if arg != "s" and arg != "a":
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sys.stderr.write("Error: invalid sorting key \"%s\"\n" % arg)
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usage()
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exit(-1)
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skey = arg
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i = i + 2
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elif opt in ('-h', '--help'):
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usage()
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exit(0)
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else:
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break
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args = sys.argv[i:]
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interval = int(args[0]) if len(args) else interval
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count = int(args[1]) if len(args) > 1 else count
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i = 0
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while True:
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cs = CumulativeStat(skey)
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cs.slab_update()
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cs.show(rows)
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i = i + 1
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if count and i >= count:
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break
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time.sleep(interval)
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return 0
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if __name__ == '__main__':
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main()
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