289 lines
7.9 KiB
Python
Executable File
289 lines
7.9 KiB
Python
Executable File
#! /usr/bin/env python
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import sys
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import os
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import time
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import calendar
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up_time_quanta = 500
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f = open(sys.argv[1])
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announce_histogram = {}
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#TODO: make this histogram into a CDF
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node_uptime_histogram = {}
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counter = 0;
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# maps search_id to a list of events. Each event is a dict containing:
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# t: timestamp
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# d: distance (from target)
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# o: outstanding searches
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# e: event (NEW, COMPLETED, ADD, INVOKE, TIMEOUT)
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# i: node-id
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# a: IP address and port
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# s: source node-id (only for ADD events)
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outstanding_searches = {}
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# list of completed searches
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searches = []
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def convert_timestamp(t):
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parts = t.split('.')
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posix = time.strptime(parts[0], '%H:%M:%S')
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return (posix.tm_hour * 3600 + posix.tm_min * 60 + posix.tm_sec) * 1000 + int(parts[1])
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last_incoming = ''
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our_node_id = ''
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for line in f:
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counter += 1
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# if counter % 1000 == 0:
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# print '\r%d' % counter,
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try:
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l = line.split(' ')
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if 'starting DHT tracker with node id:' in line:
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our_node_id = l[l.index('id:') + 1].strip()
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if 'announce-distance:' in line:
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idx = l.index('announce-distance:')
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d = int(l[idx+1].strip())
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if not d in announce_histogram: announce_histogram[d] = 0
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announce_histogram[d] += 1
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if 'NODE FAILED' in line:
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idx = l.index('fails:')
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if int(l[idx+1].strip()) != 1: continue;
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idx = l.index('up-time:')
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d = int(l[idx+1].strip())
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# quantize
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d = d - (d % up_time_quanta)
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if not d in node_uptime_histogram: node_uptime_histogram[d] = 0
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node_uptime_histogram[d] += 1
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search_id = l[2]
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ts = l[0]
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event = l[3]
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if event == 'RESPONSE':
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outstanding = int(l[l.index('invoke-count:')+1])
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nid = l[l.index('id:')+1]
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addr = l[l.index('addr:')+1]
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last_response = addr
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outstanding_searches[search_id].append({ 't': ts, 'd': distance,
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'o': outstanding + 1, 'a':addr, 'e': event,'i':nid, 's':source})
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elif event == 'NEW':
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nid = l[l.index('target:')+1]
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outstanding_searches[search_id] = [{ 't': ts, 'd': 0, 'o': 0, \
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'e': event, 'abstime': ts, 'i': nid}]
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last_response = ''
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elif event == 'INVOKE' or event == 'ADD' or event == '1ST_TIMEOUT' or \
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event == 'TIMEOUT' or event == 'PEERS':
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if not search_id in outstanding_searches:
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print 'orphaned event: %s' % line
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else:
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outstanding = int(l[l.index('invoke-count:')+1])
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distance = int(l[l.index('distance:')+1])
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nid = l[l.index('id:')+1]
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addr = l[l.index('addr:')+1]
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source = ''
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if event == 'ADD':
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if last_response == '': continue
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source = last_response
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outstanding_searches[search_id].append({ 't': ts, 'd': distance,
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'o': outstanding + 1, 'a':addr, 'e': event,'i':nid, 's':source})
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elif event == 'ABORTED':
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outstanding_searches[search_id].append({ 't': ts, 'e': event})
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elif event == 'COMPLETED':
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distance = int(l[l.index('distance:')+1])
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lookup_type = l[l.index('type:')+1].strip()
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outstanding_searches[search_id].append({ 't': ts, 'd': distance,
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'o': 0, 'e': event,'i':''})
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outstanding_searches[search_id][0]['type'] = lookup_type
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s = outstanding_searches[search_id]
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try:
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start_time = convert_timestamp(s[0]['t'])
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for i in range(len(s)):
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s[i]['t'] = convert_timestamp(s[i]['t']) - start_time
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except:
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pass
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searches.append(s)
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del outstanding_searches[search_id]
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except Exception, e:
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print e
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print line.split(' ')
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lookup_times_min = []
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lookup_times_max = []
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# these are the timestamps for lookups crossing distance
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# to target boundaries
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lookup_distance = []
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for i in range(0, 15):
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lookup_distance.append([])
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for s in searches:
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for i in s:
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if not 'last_dist' in i:
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i['last_dist'] = -1
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cur_dist = 160 - i['d']
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last_dist = i['last_dist']
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if cur_dist > last_dist:
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for j in range(last_dist + 1, cur_dist + 1):
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if j >= len(lookup_distance): break
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lookup_distance[j].append(i['t'])
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i['last_dist'] = cur_dist
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if i['e'] != 'PEERS': continue
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lookup_times_min.append(i['t'])
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break
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for i in reversed(s):
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if i['e'] != 'PEERS': continue
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lookup_times_max.append(i['t'])
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break
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lookup_times_min.sort()
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lookup_times_max.sort()
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out = open('dht_lookup_times_cdf.txt', 'w+')
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counter = 0
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for i in range(len(lookup_times_min)):
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counter += 1
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print >>out, '%d\t%d\t%f' % (lookup_times_min[i], lookup_times_max[i], counter / float(len(lookup_times_min)))
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out.close()
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for i in lookup_distance:
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i.sort()
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dist = 0
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for i in lookup_distance:
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out = open('dht_lookup_distance_%d.txt' % dist, 'w+')
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dist += 1
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counter = 0
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for j in i:
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counter += 1
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print >>out, '%d\t%f' % (j, counter / float(len(i)))
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out.close()
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out = open('dht_lookups.txt', 'w+')
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for s in searches:
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for i in s:
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if i['e'] == 'INVOKE':
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print >>out, ' ->', i['t'], 160 - i['d'], i['i'], i['a']
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elif i['e'] == '1ST_TIMEOUT':
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print >>out, ' x ', i['t'], 160 - i['d'], i['i'], i['a']
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elif i['e'] == 'TIMEOUT':
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print >>out, ' X ', i['t'], 160 - i['d'], i['i'], i['a']
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elif i['e'] == 'ADD':
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print >>out, ' + ', i['t'], 160 - i['d'], i['i'], i['a'], i['s']
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elif i['e'] == 'RESPONSE':
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print >>out, ' <-', i['t'], 160 - i['d'], i['i'], i['a']
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elif i['e'] == 'PEERS':
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print >>out, ' <-', i['t'], 160 - i['d'], i['i'], i['a']
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elif i['e'] == 'ABORTED':
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print >>out, 'abort'
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elif i['e'] == 'COMPLETED':
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print >>out, '***', i['t'], 160 - i['d'], '\n'
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elif i['e'] == 'NEW':
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print >>out, '===', i['abstime'], i['type'], '==='
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print >>out, '<> ', 0, our_node_id, i['i']
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out.close()
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out = open('dht_announce_distribution.dat', 'w+')
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print 'announce distribution items: %d' % len(announce_histogram)
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for k,v in announce_histogram.items():
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print >>out, '%d %d' % (k, v)
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print '%d %d' % (k, v)
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out.close()
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out = open('dht_node_uptime_cdf.txt', 'w+')
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s = 0
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total_uptime_nodes = 0
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for k,v in node_uptime_histogram.items():
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total_uptime_nodes += v
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for k,v in sorted(node_uptime_histogram.items()):
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s += v
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print >>out, '%f %f' % (k / float(60), s / float(total_uptime_nodes))
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print '%f %f' % (k / float(60), s / float(total_uptime_nodes))
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out.close()
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out = open('dht.gnuplot', 'w+')
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out.write('''
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set term png size 1200,700 small
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set output "dht_lookup_times_cdf.png"
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set title "portion of lookups that have received at least one data response"
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set ylabel "portion of lookups"
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set xlabel "time from start of lookup (ms)"
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set grid
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plot "dht_lookup_times_cdf.txt" using 1:3 with lines title "time to first result", \
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"dht_lookup_times_cdf.txt" using 2:3 with lines title "time to last result"
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set terminal postscript
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set output "dht_lookup_times_cdf.ps"
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replot
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set term png size 1200,700 small
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set xtics 100
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set xrange [0:2000]
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set output "dht_min_lookup_times_cdf.png"
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plot "dht_lookup_times_cdf.txt" using 1:3 with lines title "time to first result"
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set terminal postscript
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set output "dht_min_lookup_times_cdf.ps"
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replot
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set term png size 1200,700 small
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set output "dht_node_uptime_cdf.png"
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set xrange [0:*]
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set title "node up time"
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set ylabel "portion of nodes being offline"
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set xlabel "time from first seeing the node (minutes)"
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set xtics 10
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unset grid
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plot "dht_node_uptime_cdf.txt" using 1:2 title "nodes" with lines
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set term png size 1200,700 small
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set output "dht_announce_distribution.png"
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set xrange [0:30]
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set xtics 1
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set title "bucket # announces are made against relative to target node-id"
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set ylabel "# of announces"
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set boxwidth 1
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set xlabel "bit prefix of nodes in announces"
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set style fill solid border -1 pattern 2
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plot "dht_announce_distribution.dat" using 1:2 title "announces" with boxes
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set terminal postscript
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set output "dht_announce_distribution.ps"
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replot
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set term png size 1200,700 small
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set output "dht_lookup_distance_cdf.png"
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set title "portion of lookups that have reached a certain distance in their lookups"
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set ylabel "portion of lookups"
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set xlabel "time from start of lookup (ms)"
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set xrange [0:2000]
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set xtics 100
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set grid
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plot ''')
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dist = 0
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for i in lookup_distance:
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if dist > 0: out.write(', ')
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out.write('"dht_lookup_distance_%d.txt" using 1:2 title "%d" with lines' % (dist, dist))
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dist += 1
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out.close()
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os.system('gnuplot dht.gnuplot');
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