extras/profiler/glusterfs-profiler: Add graphing tool.
glusterfs-profiler is a Python tool that can graphically display the profiling information printed in the process state dump. Signed-off-by: Vikas Gorur <vikas@gluster.com> Signed-off-by: Anand V. Avati <avati@dev.gluster.com> BUG: 268 (Add timing instrumentation code) URL: http://bugs.gluster.com/cgi-bin/bugzilla3/show_bug.cgi?id=268
This commit is contained in:
Vikas Gorur
Anand V. Avati
parent
d9b34f3f2c
commit
9c2bfa8a44
267
extras/profiler/glusterfs-profiler
Executable file
267
extras/profiler/glusterfs-profiler
Executable file
@ -0,0 +1,267 @@
|
||||
#!/usr/bin/env python
|
||||
|
||||
# Copyright (c) 2010 Gluster, Inc. <http://www.gluster.com>
|
||||
# This file is part of GlusterFS.
|
||||
|
||||
# GlusterFS is free software; you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published
|
||||
# by the Free Software Foundation; either version 3 of the License,
|
||||
# or (at your option) any later version.
|
||||
|
||||
# GlusterFS is distributed in the hope that it will be useful, but
|
||||
# WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
||||
# General Public License for more details.
|
||||
|
||||
# You should have received a copy of the GNU General Public License
|
||||
# along with this program. If not, see
|
||||
# <http://www.gnu.org/licenses/>.
|
||||
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
import re
|
||||
import sys
|
||||
|
||||
from optparse import OptionParser
|
||||
|
||||
# Global dict-of-dict holding the latency data
|
||||
# latency[xlator-name][op-name]
|
||||
|
||||
latencies = {}
|
||||
counts = {}
|
||||
totals = {}
|
||||
|
||||
def collect_data (f):
|
||||
"""Collect latency data from the file object f and store it in
|
||||
the global variable @latencies"""
|
||||
|
||||
# example dump file line:
|
||||
# fuse.latency.TRUNCATE=3147.000,4
|
||||
|
||||
for line in f:
|
||||
m = re.search ("(\w+)\.\w+.(\w+)=(\w+\.\w+),(\w+),(\w+.\w+)", line)
|
||||
if m and float(m.group(3)) != 0:
|
||||
xlator = m.group(1)
|
||||
op = m.group(2)
|
||||
time = m.group(3)
|
||||
count = m.group(4)
|
||||
total = m.group(5)
|
||||
|
||||
if not xlator in latencies.keys():
|
||||
latencies[xlator] = dict()
|
||||
|
||||
if not xlator in counts.keys():
|
||||
counts[xlator] = dict()
|
||||
|
||||
if not xlator in totals.keys():
|
||||
totals[xlator] = dict()
|
||||
|
||||
latencies[xlator][op] = time
|
||||
counts[xlator][op] = count
|
||||
totals[xlator][op] = total
|
||||
|
||||
|
||||
def calc_latency_heights (xlator_order):
|
||||
heights = map (lambda x: [], xlator_order)
|
||||
|
||||
N = len (xlator_order)
|
||||
for i in range (N):
|
||||
xl = xlator_order[i]
|
||||
|
||||
k = latencies[xl].keys()
|
||||
k.sort()
|
||||
|
||||
if i == len (xlator_order) - 1:
|
||||
# bottom-most xlator
|
||||
heights[i] = [float (latencies[xl][key]) for key in k]
|
||||
|
||||
else:
|
||||
next_xl = xlator_order[i+1]
|
||||
this_xl_time = [latencies[xl][key] for key in k]
|
||||
next_xl_time = [latencies[next_xl][key] for key in k]
|
||||
|
||||
heights[i] = map (lambda x, y: float (x) - float (y),
|
||||
this_xl_time, next_xl_time)
|
||||
return heights
|
||||
|
||||
# have sufficient number of colors
|
||||
colors = ["violet", "blue", "green", "yellow", "orange", "red"]
|
||||
|
||||
def latency_profile (title, xlator_order):
|
||||
heights = calc_latency_heights (xlator_order)
|
||||
|
||||
N = len (latencies[xlator_order[0]].keys())
|
||||
Nxl = len (xlator_order)
|
||||
ind = np.arange (N)
|
||||
width = 0.35
|
||||
|
||||
pieces = map (lambda x: [], xlator_order)
|
||||
bottoms = map (lambda x: [], xlator_order)
|
||||
|
||||
bottoms[Nxl-1] = map (lambda x: 0, latencies[xlator_order[0]].keys())
|
||||
|
||||
for i in range (Nxl-1):
|
||||
xl = xlator_order[i+1]
|
||||
k = latencies[xl].keys()
|
||||
k.sort()
|
||||
|
||||
bottoms[i] = [float(latencies[xl][key]) for key in k]
|
||||
|
||||
for i in range(Nxl):
|
||||
pieces[i] = plt.bar (ind, heights[i], width, color=colors[i],
|
||||
bottom=bottoms[i])
|
||||
|
||||
plt.ylabel ("Average Latency (microseconds)")
|
||||
plt.title ("Latency Profile for '%s'" % title)
|
||||
k = latencies[xlator_order[0]].keys()
|
||||
k.sort ()
|
||||
plt.xticks (ind+width/2., k)
|
||||
|
||||
m = round (max(map (float, latencies[xlator_order[0]].values())), -2)
|
||||
plt.yticks (np.arange(0, m + m*0.1, m/10))
|
||||
plt.legend (map (lambda p: p[0], pieces), xlator_order)
|
||||
|
||||
plt.show ()
|
||||
|
||||
def fop_distribution (title, xlator_order):
|
||||
plt.ylabel ("Percentage of calls")
|
||||
plt.title ("FOP distribution for '%s'" % title)
|
||||
k = counts[xlator_order[0]].keys()
|
||||
k.sort ()
|
||||
|
||||
N = len (latencies[xlator_order[0]].keys())
|
||||
ind = np.arange(N)
|
||||
width = 0.35
|
||||
|
||||
total = 0
|
||||
top_xl = xlator_order[0]
|
||||
for op in k:
|
||||
total += int(counts[top_xl][op])
|
||||
|
||||
heights = []
|
||||
|
||||
for op in k:
|
||||
heights.append (float(counts[top_xl][op])/total * 100)
|
||||
|
||||
bars = plt.bar (ind, heights, width, color="red")
|
||||
|
||||
for bar in bars:
|
||||
height = bar.get_height()
|
||||
plt.text (bar.get_x()+bar.get_width()/2., 1.05*height,
|
||||
"%d%%" % int(height))
|
||||
|
||||
plt.xticks(ind+width/2., k)
|
||||
plt.yticks(np.arange (0, 110, 10))
|
||||
|
||||
plt.show()
|
||||
|
||||
def calc_workload_heights (xlator_order, scaling):
|
||||
workload_heights = map (lambda x: [], xlator_order)
|
||||
|
||||
top_xl = xlator_order[0]
|
||||
|
||||
N = len (xlator_order)
|
||||
for i in range (N):
|
||||
xl = xlator_order[i]
|
||||
|
||||
k = totals[xl].keys()
|
||||
k.sort()
|
||||
|
||||
if i == len (xlator_order) - 1:
|
||||
# bottom-most xlator
|
||||
workload_heights[i] = [float (totals[xl][key]) / float(totals[top_xl][key]) * scaling[k.index(key)] for key in k]
|
||||
|
||||
else:
|
||||
next_xl = xlator_order[i+1]
|
||||
this_xl_time = [float(totals[xl][key]) / float(totals[top_xl][key]) * scaling[k.index(key)] for key in k]
|
||||
next_xl_time = [float(totals[next_xl][key]) / float(totals[top_xl][key]) * scaling[k.index(key)] for key in k]
|
||||
|
||||
workload_heights[i] = map (lambda x, y: (float (x) - float (y)),
|
||||
this_xl_time, next_xl_time)
|
||||
|
||||
return workload_heights
|
||||
|
||||
def workload_profile(title, xlator_order):
|
||||
plt.ylabel ("Percentage of Total Time")
|
||||
plt.title ("Workload Profile for '%s'" % title)
|
||||
k = totals[xlator_order[0]].keys()
|
||||
k.sort ()
|
||||
|
||||
N = len(totals[xlator_order[0]].keys())
|
||||
Nxl = len(xlator_order)
|
||||
ind = np.arange(N)
|
||||
width = 0.35
|
||||
|
||||
total = 0
|
||||
top_xl = xlator_order[0]
|
||||
for op in k:
|
||||
total += float(totals[top_xl][op])
|
||||
|
||||
p_heights = []
|
||||
|
||||
for op in k:
|
||||
p_heights.append (float(totals[top_xl][op])/total * 100)
|
||||
|
||||
heights = calc_workload_heights (xlator_order, p_heights)
|
||||
|
||||
pieces = map (lambda x: [], xlator_order)
|
||||
bottoms = map (lambda x: [], xlator_order)
|
||||
|
||||
bottoms[Nxl-1] = map (lambda x: 0, totals[xlator_order[0]].keys())
|
||||
|
||||
for i in range (Nxl-1):
|
||||
xl = xlator_order[i+1]
|
||||
k = totals[xl].keys()
|
||||
k.sort()
|
||||
|
||||
bottoms[i] = [float(totals[xl][key]) / float(totals[top_xl][key]) * p_heights[k.index(key)] for key in k]
|
||||
|
||||
for i in range(Nxl):
|
||||
pieces[i] = plt.bar (ind, heights[i], width, color=colors[i],
|
||||
bottom=bottoms[i])
|
||||
|
||||
for key in k:
|
||||
bar = pieces[Nxl-1][k.index(key)]
|
||||
plt.text (bar.get_x() + bar.get_width()/2., 1.05*p_heights[k.index(key)],
|
||||
"%d%%" % int(p_heights[k.index(key)]))
|
||||
|
||||
plt.xticks(ind+width/2., k)
|
||||
plt.yticks(np.arange (0, 110, 10))
|
||||
plt.legend (map (lambda p: p[0], pieces), xlator_order)
|
||||
|
||||
plt.show()
|
||||
|
||||
def main ():
|
||||
parser = OptionParser(usage="usage: %prog [-l | -d | -w] -x <xlator order> <state dump file>")
|
||||
parser.add_option("-l", "--latency", dest="latency", action="store_true",
|
||||
help="Produce latency profile")
|
||||
parser.add_option("-d", "--distribution", dest="distribution", action="store_true",
|
||||
help="Produce distribution of FOPs")
|
||||
parser.add_option("-w", "--workload", dest="workload", action="store_true",
|
||||
help="Produce workload profile")
|
||||
parser.add_option("-t", "--title", dest="title", help="Set the title of the graph")
|
||||
parser.add_option("-x", "--xlator-order", dest="xlator_order", help="Specify the order of xlators")
|
||||
|
||||
(options, args) = parser.parse_args()
|
||||
|
||||
if len(args) != 1:
|
||||
parser.error("Incorrect number of arguments")
|
||||
|
||||
if (options.xlator_order):
|
||||
xlator_order = options.xlator_order.split()
|
||||
else:
|
||||
print "xlator order must be specified"
|
||||
sys.exit(1)
|
||||
|
||||
collect_data(file (args[0], 'r'))
|
||||
|
||||
if (options.latency):
|
||||
latency_profile (options.title, xlator_order)
|
||||
|
||||
if (options.distribution):
|
||||
fop_distribution(options.title, xlator_order)
|
||||
|
||||
if (options.workload):
|
||||
workload_profile(options.title, xlator_order)
|
||||
|
||||
main ()
|
||||
Loading…
x
Reference in New Issue
Block a user