def plotBurstlenUsec(directory):
# Read burst lengths from the sniffer pickled files
burstlen_nsec_pfile = os.path.join(directory, "pickled/burstlen_nsec.txt")
burstlen_nsec_summary_pfile = os.path.join(directory, "pickled/burstlen_nsec_summary.txt")
burstlen_nsec = readPickledFile(burstlen_nsec_pfile)
summary = readPickledFile(burstlen_nsec_summary_pfile)
ports = summary.keys()
cdf_data = []
avg_data = []
pc99_data = []
for port in ports:
# Convert from nanoseconds to microseconds for plotting
cdf_data.append(map(lambda x: x / 1000.0, burstlen_nsec[port]))
avg, pc99 = summary[port]
avg_data.append(avg / 1000.0)
pc99_data.append(pc99 / 1000.0)
return plotCDFGraphSimple(
cdf_data,
avg_data,
pc99_data,
"Burst length (in microseconds)",
"Fractiles",
"CDF of burst length in microseconds",
)
def plotMcperfLatency(directory):
# Read latency histogram from the mcperf pickled files
mcperf_pfile = os.path.join(directory, 'pickled/mcperf_p.txt')
mcperf_summary_pfile = os.path.join(directory,
'pickled/mcperf_summary_p.txt')
agg_hist = readPickledFile(mcperf_pfile)
mcperf_summary = readPickledFile(mcperf_summary_pfile)
return plotCDFGraphFromHist(agg_hist, mcperf_summary['lat_avg'],
mcperf_summary['lat_pc99'],
mcperf_summary['lat_pc999'],
"Memcached transaction latency (usecs)",
"Fractiles",
"CDF of memcached transaction latency")
def plotMcperfLatency(directory):
# Read latency histogram from the mcperf pickled files
mcperf_pfile = os.path.join(directory, 'pickled/mcperf_p.txt')
mcperf_summary_pfile = os.path.join(
directory, 'pickled/mcperf_summary_p.txt')
agg_hist = readPickledFile(mcperf_pfile)
mcperf_summary = readPickledFile(mcperf_summary_pfile)
return plotCDFGraphFromHist(agg_hist, mcperf_summary['lat_avg'],
mcperf_summary['lat_pc99'],
mcperf_summary['lat_pc999'],
"Memcached transaction latency (usecs)",
"Fractiles",
"CDF of memcached transaction latency")
def plotIpt(directory):
# Read inter-packet arrival times from the sniffer pickled files
ipt_pfile = os.path.join(directory, "pickled/ipt.txt")
ipt_summary_pfile = os.path.join(directory, "pickled/ipt_summary.txt")
ipt = readPickledFile(ipt_pfile)
summary = readPickledFile(ipt_summary_pfile)
ports = summary.keys()
# Read packet lengths from sniffer pickled files
pkt_len_freq_pfile = os.path.join(directory, "pickled/pkt_len_freq.txt")
(most_freq_pkt_len, pkt_len_freq) = readPickledFile(pkt_len_freq_pfile)
cdf_data = []
avg_data = []
pc99_data = []
for port in ports:
# Convert from nanoseconds to microseconds for plotting
cdf_data.append(map(lambda x: x / 1000.0, ipt[port]))
avg, pc99 = summary[port]
avg_data.append(avg / 1000.0)
pc99_data.append(pc99 / 1000.0)
# Generate CDF plot
plot = plotCDFGraphSimple(
cdf_data,
avg_data,
pc99_data,
"Inter-packet time (in microseconds)",
"Fractiles",
"CDF of inter-packet time (not inter-packet gap) " "in microseconds",
)
# Compute ideal inter-packet arrival time for most frequently seen packet
# length in the trace
rate_mbps = float(readDirTagFileProperty(directory, "rate_mbps"))
nclasses = int(readDirTagFileProperty(directory, "nclasses"))
rate_per_class_gbps = rate_mbps / (1000.0 * nclasses)
ideal_nsec = idealIptNsec(most_freq_pkt_len, rate_per_class_gbps)
# Add VLine for the ideal inter-packet time
# Also convert from nanoseconds to microseconds for plotting
ideal_vline = boomslang.VLine(color="magenta", lineStyle="-.", width=2)
ideal_vline.xValues = [ideal_nsec / 1000.0]
ideal_vline.label = "Ideal"
plot.add(ideal_vline)
return plot
def getAvgBurstLenPkt(directory):
# Read the sniffer pickle file and return the average burst length in
# packets
burstlen_pkt_summary_pfile = os.path.join(
directory, 'pickled/burstlen_pkt_summary.txt')
summary = readPickledFile(burstlen_pkt_summary_pfile)
avg_burstlen = numpy.average(map(lambda port: summary[port][0],
summary.keys()))
return avg_burstlen
def getAvgBurstLenPkt(directory):
# Read the sniffer pickle file and return the average burst length in
# packets
burstlen_pkt_summary_pfile = os.path.join(
directory, 'pickled/burstlen_pkt_summary.txt')
summary = readPickledFile(burstlen_pkt_summary_pfile)
avg_burstlen = numpy.average(
map(lambda port: summary[port][0], summary.keys()))
return avg_burstlen
def getPc99BurstLenUsec(directory):
# Read the sniffer pickle file and return the average of pc99 burst length
# in usecs (convert from nsecs)
burstlen_nsec_summary_pfile = os.path.join(
directory, 'pickled/burstlen_nsec_summary.txt')
summary = readPickledFile(burstlen_nsec_summary_pfile)
avg_pc99_burstlen = (numpy.average(map(lambda port: summary[port][1],
summary.keys())) / 1000.0)
return avg_pc99_burstlen
def plotIpt(directory):
# Read inter-packet arrival times from the sniffer pickled files
ipt_pfile = os.path.join(directory, 'pickled/ipt.txt')
ipt_summary_pfile = os.path.join(directory, 'pickled/ipt_summary.txt')
ipt = readPickledFile(ipt_pfile)
summary = readPickledFile(ipt_summary_pfile)
ports = summary.keys()
# Read packet lengths from sniffer pickled files
pkt_len_freq_pfile = os.path.join(directory, 'pickled/pkt_len_freq.txt')
(most_freq_pkt_len, pkt_len_freq) = readPickledFile(pkt_len_freq_pfile)
cdf_data = []
avg_data = []
pc99_data = []
for port in ports:
# Convert from nanoseconds to microseconds for plotting
cdf_data.append(map(lambda x: x / 1000.0, ipt[port]))
avg, pc99 = summary[port]
avg_data.append(avg / 1000.0)
pc99_data.append(pc99 / 1000.0)
# Generate CDF plot
plot = plotCDFGraphSimple(
cdf_data, avg_data, pc99_data, "Inter-packet time (in microseconds)",
"Fractiles", "CDF of inter-packet time (not inter-packet gap) "
"in microseconds")
# Compute ideal inter-packet arrival time for most frequently seen packet
# length in the trace
rate_mbps = float(readDirTagFileProperty(directory, "rate_mbps"))
nclasses = int(readDirTagFileProperty(directory, "nclasses"))
rate_per_class_gbps = rate_mbps / (1000.0 * nclasses)
ideal_nsec = idealIptNsec(most_freq_pkt_len, rate_per_class_gbps)
# Add VLine for the ideal inter-packet time
# Also convert from nanoseconds to microseconds for plotting
ideal_vline = boomslang.VLine(color="magenta", lineStyle="-.", width=2)
ideal_vline.xValues = [ideal_nsec / 1000.0]
ideal_vline.label = "Ideal"
plot.add(ideal_vline)
return plot
def getPc99BurstLenUsec(directory):
# Read the sniffer pickle file and return the average of pc99 burst length
# in usecs (convert from nsecs)
burstlen_nsec_summary_pfile = os.path.join(
directory, 'pickled/burstlen_nsec_summary.txt')
summary = readPickledFile(burstlen_nsec_summary_pfile)
avg_pc99_burstlen = (
numpy.average(map(lambda port: summary[port][1], summary.keys())) /
1000.0)
return avg_pc99_burstlen
def getLatencyCDF(directory):
# Read latency histogram from the mcperf pickled files
mcperf_pfile = os.path.join(directory, 'pickled/mcperf_p.txt')
agg_hist = readPickledFile(mcperf_pfile)
if FOR_PAPER:
# Convert usec sample values to msec
agg_hist = {k / 1000.0: v for k, v in agg_hist.items()}
return cdfLineFromHist(agg_hist)
def plotBurstlenPkt(directory):
# Read burst lengths from the sniffer pickled files
burstlen_pkt_pfile = os.path.join(directory, "pickled/burstlen_pkt.txt")
burstlen_pkt_summary_pfile = os.path.join(directory, "pickled/burstlen_pkt_summary.txt")
burstlen_pkt = readPickledFile(burstlen_pkt_pfile)
summary = readPickledFile(burstlen_pkt_summary_pfile)
ports = summary.keys()
cdf_data = []
avg_data = []
pc99_data = []
for port in ports:
cdf_data.append(burstlen_pkt[port])
avg, pc99 = summary[port]
avg_data.append(avg)
pc99_data.append(pc99)
return plotCDFGraphSimple(
cdf_data, avg_data, pc99_data, "Burst length (in packets)", "Fractiles", "CDF of burst length in packets"
)
def getServerAvgTxRate(directory):
# Read the trafgen pickle file and return the average trafgen Tx rate on
# server machines
trafgen_pfile = os.path.join(directory, 'pickled/trafgen_p.txt')
(host_tx_goodput, host_rx_goodput) = readPickledFile(trafgen_pfile)
# Find the list of servers used for the experiment
servers, clients = getServersAndClients(directory)
rates = [ int(host_tx_goodput.get(server, 0) * 1514.0 / 1472.0)
for server in servers ]
return numpy.mean(rates)
def plotBurstlenPkt(directory):
# Read burst lengths from the sniffer pickled files
burstlen_pkt_pfile = os.path.join(directory, 'pickled/burstlen_pkt.txt')
burstlen_pkt_summary_pfile = os.path.join(
directory, 'pickled/burstlen_pkt_summary.txt')
burstlen_pkt = readPickledFile(burstlen_pkt_pfile)
summary = readPickledFile(burstlen_pkt_summary_pfile)
ports = summary.keys()
cdf_data = []
avg_data = []
pc99_data = []
for port in ports:
cdf_data.append(burstlen_pkt[port])
avg, pc99 = summary[port]
avg_data.append(avg)
pc99_data.append(pc99)
return plotCDFGraphSimple(cdf_data, avg_data, pc99_data,
"Burst length (in packets)", "Fractiles",
"CDF of burst length in packets")
def plotBurstlenUsec(directory):
# Read burst lengths from the sniffer pickled files
burstlen_nsec_pfile = os.path.join(directory, 'pickled/burstlen_nsec.txt')
burstlen_nsec_summary_pfile = os.path.join(
directory, 'pickled/burstlen_nsec_summary.txt')
burstlen_nsec = readPickledFile(burstlen_nsec_pfile)
summary = readPickledFile(burstlen_nsec_summary_pfile)
ports = summary.keys()
cdf_data = []
avg_data = []
pc99_data = []
for port in ports:
# Convert from nanoseconds to microseconds for plotting
cdf_data.append(map(lambda x: x / 1000.0, burstlen_nsec[port]))
avg, pc99 = summary[port]
avg_data.append(avg / 1000.0)
pc99_data.append(pc99 / 1000.0)
return plotCDFGraphSimple(cdf_data, avg_data, pc99_data,
"Burst length (in microseconds)", "Fractiles",
"CDF of burst length in microseconds")
def getServerAvgTxRate(directory):
# Read the trafgen pickle file and return the average trafgen Tx rate on
# server machines
trafgen_pfile = os.path.join(directory, 'pickled/trafgen_p.txt')
(host_tx_goodput, host_rx_goodput) = readPickledFile(trafgen_pfile)
# Find the list of servers used for the experiment
servers, clients = getServersAndClients(directory)
rates = [
int(host_tx_goodput.get(server, 0) * 1514.0 / 1472.0)
for server in servers
]
return numpy.mean(rates)
def getKernelCPUUtil(directory):
# Read the mpstat pickle file and return the kernel CPU utilization
mpstat_pfile = os.path.join(directory, 'pickled/mpstat_p.txt')
(kernel_usage, summary) = readPickledFile(mpstat_pfile)
return kernel_usage
def getServersAndClients(directory):
# Read the hosts info pickle file
hosts_pfile = os.path.join(directory, 'pickled/hosts_p.txt')
(servers, clients) = readPickledFile(hosts_pfile)
return (servers, clients)
def getpc999Latency(directory):
# Read the mcperf pickle file and return the average latency
mcperf_summary_pfile = os.path.join(
directory, 'pickled/mcperf_summary_p.txt')
mcperf_summary = readPickledFile(mcperf_summary_pfile)
return mcperf_summary['lat_pc999']
def getKernelCPUUtil(directory):
# Read the mpstat pickle file and return the kernel CPU utilization
mpstat_pfile = os.path.join(directory, 'pickled/mpstat_p.txt')
(kernel_usage, summary) = readPickledFile(mpstat_pfile)
return kernel_usage
def getServersAndClients(directory):
# Read the hosts info pickle file
hosts_pfile = os.path.join(directory, 'pickled/hosts_p.txt')
(servers, clients) = readPickledFile(hosts_pfile)
return (servers, clients)
