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-rwxr-xr-xshow-blocks325
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+#!/usr/bin/env python
+#
+# Copyright (C) 2007 Oracle. All rights reserved.
+#
+# This program is free software; you can redistribute it and/or
+# modify it under the terms of the GNU General Public
+# License v2 as published by the Free Software Foundation.
+#
+# This program 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, write to the
+# Free Software Foundation, Inc., 59 Temple Place - Suite 330,
+# Boston, MA 021110-1307, USA.
+#
+import sys, os, signal, time, commands, tempfile, random
+
+# numpy seems to override random() with something else. Instantiate our
+# own here
+randgen = random.Random()
+randgen.seed(50)
+
+from optparse import OptionParser
+from matplotlib import rcParams
+from matplotlib.font_manager import fontManager, FontProperties
+import numpy
+
+rcParams['numerix'] = 'numpy'
+rcParams['backend'] = 'Agg'
+rcParams['interactive'] = 'False'
+from pylab import *
+
+class AnnoteFinder:
+ """
+ callback for matplotlib to display an annotation when points are clicked on. The
+ point which is closest to the click and within xtol and ytol is identified.
+
+ Register this function like this:
+
+ scatter(xdata, ydata)
+ af = AnnoteFinder(xdata, ydata, annotes)
+ connect('button_press_event', af)
+ """
+
+ def __init__(self, axis=None):
+ if axis is None:
+ self.axis = gca()
+ else:
+ self.axis= axis
+ self.drawnAnnotations = {}
+ self.links = []
+
+ def clear(self):
+ for k in self.drawnAnnotations.keys():
+ self.drawnAnnotations[k].set_visible(False)
+
+ def __call__(self, event):
+ if event.inaxes:
+ if event.button != 1:
+ self.clear()
+ draw()
+ return
+ clickX = event.xdata
+ clickY = event.ydata
+ if (self.axis is None) or (self.axis==event.inaxes):
+ self.drawAnnote(event.inaxes, clickX, clickY)
+
+ def drawAnnote(self, axis, x, y):
+ """
+ Draw the annotation on the plot
+ """
+ if self.drawnAnnotations.has_key((x,y)):
+ markers = self.drawnAnnotations[(x,y)]
+ markers.set_visible(not markers.get_visible())
+ draw()
+ else:
+ t = axis.text(x,y, "(%3.2f, %3.2f)"%(x,y), bbox=dict(facecolor='red',
+ alpha=0.8))
+ self.drawnAnnotations[(x,y)] = t
+ draw()
+
+def loaddata(fh,delimiter=None, converters=None):
+
+ #14413824 8192 extent back ref root 5 gen 10 owner 282 num_refs 1
+ def iter(fh, delimiter, converters):
+ global total_data
+ global total_metadata
+ for i,line in enumerate(fh):
+ line = line.split(' ')
+ start = float(line[0])
+ len = float(line[1])
+ owner = float(line[10])
+ root = float(line[6])
+ if owner <= 255:
+ total_metadata += int(len)
+ else:
+ total_data += int(len)
+ if start < zoommin or (zoommax != 0 and start > zoommax):
+ continue
+ yield start
+ yield len
+ yield owner
+ yield root
+ X = numpy.fromiter(iter(fh, delimiter, converters), dtype=float)
+ return X
+
+def run_debug_tree(device):
+ p = os.popen('btrfs-debug-tree -e ' + device)
+ data = loaddata(p)
+ return data
+
+def shapeit(X):
+ lines = len(X) / 4
+ X.shape = (lines, 4)
+
+def line_picker(line, mouseevent):
+ if mouseevent.xdata is None: return False, dict()
+ print "%d %d\n", mouseevent.xdata, mouseevent.ydata
+ return False, dict()
+
+def xycalc(byte):
+ byte = byte / bytes_per_cell
+ yval = floor(byte / num_cells)
+ xval = byte % num_cells
+ return (xval, yval + 1)
+
+# record the color used for each root the first time we find it
+root_colors = {}
+# there are lots of good colormaps to choose from
+# http://www.scipy.org/Cookbook/Matplotlib/Show_colormaps
+#
+meta_cmap = get_cmap("gist_ncar")
+data_done = False
+
+def plotone(a, xvals, yvals, owner, root, lines, labels):
+ global data_done
+ add_label = False
+
+ if owner:
+ if options.meta_only:
+ return
+ color = "blue"
+ label = "Data"
+ if not data_done:
+ add_label = True
+ data_done = True
+ else:
+ if options.data_only:
+ return
+ if root not in root_colors:
+ color = meta_cmap(randgen.random())
+ label = "Meta %d" % int(root)
+ root_colors[root] = (color, label)
+ add_label = True
+ else:
+ color, label = root_colors[root]
+
+ plotlines = a.plot(xvals, yvals, 's', color=color, mfc=color, mec=color,
+ markersize=.23, label=label)
+ if add_label:
+ lines += plotlines
+ labels.append(label)
+ print "add label %s" % label
+
+def parse_zoom():
+ def parse_num(s):
+ mult = 1
+ c = s.lower()[-1]
+ if c == 't':
+ mult = 1024 * 1024 * 1024 * 1024
+ elif c == 'g':
+ mult = 1024 * 1024 * 1024
+ elif c == 'm':
+ mult = 1024 * 1024
+ elif c == 'k':
+ mult = 1024
+ else:
+ c = None
+ if c:
+ num = int(s[:-1]) * mult
+ else:
+ num = int(s)
+ return num
+
+ if not options.zoom:
+ return (0, 0)
+
+ vals = options.zoom.split(':')
+ if len(vals) != 2:
+ sys.stderr.write("warning: unable to parse zoom %s\n" % options.zoom)
+ return (0, 0)
+ zoommin = parse_num(vals[0])
+ zoommax = parse_num(vals[1])
+ return (zoommin, zoommax)
+
+usage = "usage: %prog [options]"
+parser = OptionParser(usage=usage)
+parser.add_option("-d", "--device", help="Btrfs device", default="")
+parser.add_option("-i", "--input-file", help="debug-tree data", default="")
+parser.add_option("-o", "--output", help="Output file", default="blocks.png")
+parser.add_option("-z", "--zoom", help="Zoom", default=None)
+parser.add_option("", "--data-only", help="Only print data blocks",
+ default=False, action="store_true")
+parser.add_option("", "--meta-only", help="Only print metadata blocks",
+ default=False, action="store_true")
+
+(options,args) = parser.parse_args()
+
+if not options.device and not options.input_file:
+ parser.print_help()
+ sys.exit(1)
+
+zoommin, zoommax = parse_zoom()
+total_data = 0
+total_metadata = 0
+
+if options.device:
+ data = run_debug_tree(options.device)
+elif options.input_file:
+ data = loaddata(file(options.input_file))
+shapeit(data)
+
+# try to drop out the least common data points by creating
+# a histogram of the sectors seen.
+sectors = data[:,0]
+sizes = data[:,1]
+datalen = len(data)
+sectormax = numpy.max(sectors)
+sectormin = 0
+num_cells = 800
+total_cells = num_cells * num_cells
+byte_range = sectormax - sectormin
+bytes_per_cell = byte_range / total_cells
+
+f = figure(figsize=(8,6))
+
+# Throughput goes at the bottom
+a = subplot(1, 1, 1)
+subplots_adjust(right=0.7)
+datai = 0
+xvals = []
+yvals = []
+last_owner = 0
+last_root = 0
+lines = []
+labels = []
+while datai < datalen:
+ row = data[datai]
+ datai += 1
+ byte = row[0]
+ size = row[1]
+ owner = row[2]
+ root = row[3]
+
+ if owner <= 255:
+ owner = 0
+ else:
+ owner = 1
+
+ if len(xvals) and (owner != last_owner or last_root != root):
+ plotone(a, xvals, yvals, last_owner, last_root, lines, labels)
+ xvals = []
+ yvals = []
+ cell = 0
+ while cell < size:
+ xy = xycalc(byte)
+ byte += bytes_per_cell
+ cell += bytes_per_cell
+ if xy:
+ xvals.append(xy[0])
+ yvals.append(xy[1])
+ last_owner = owner
+ last_root = root
+
+if xvals:
+ plotone(a, xvals, yvals, last_owner, last_root, lines, labels)
+
+# make sure the final second goes on the x axes
+ticks = []
+a.set_xticks(ticks)
+ticks = a.get_yticks()
+
+first_tick = ticks[1] * bytes_per_cell * num_cells
+if first_tick > 1024 * 1024 * 1024 * 1024:
+ scale = 1024 * 1024 * 1024 * 1024;
+ scalestr = "TB"
+elif first_tick > 1024 * 1024 * 1024:
+ scale = 1024 * 1024 * 1024;
+ scalestr = "GB"
+elif first_tick > 1024 * 1024:
+ scale = 1024 * 1024;
+ scalestr = "MB"
+elif first_tick > 1024:
+ scale = 1024;
+ scalestr = "KB"
+else:
+ scalestr = "Bytes"
+ scale = 1
+
+ylabels = [ str(int((x * bytes_per_cell * num_cells) / scale)) for x in ticks ]
+a.set_yticklabels(ylabels)
+a.set_ylabel('Disk offset (%s)' % scalestr)
+a.set_xlim(0, num_cells)
+a.set_title('Blocks')
+
+a.legend(lines, labels, loc=(1.05, 0.8), shadow=True, pad=0.1, numpoints=1,
+ handletextsep = 0.005,
+ labelsep = 0.01,
+ markerscale=10,
+ prop=FontProperties(size='x-small') )
+
+if total_data == 0:
+ percent_meta = 100
+else:
+ percent_meta = (float(total_metadata) / float(total_data)) * 100
+
+print "Total metadata bytes %d data %d ratio %.3f" % (total_metadata,
+ total_data, percent_meta)
+print "saving graph to %s" % options.output
+savefig(options.output, orientation='landscape')
+show()
+