def aggregate_multi_flow_results(results):
if len(results) == 1:
return results
sample_result = results[0]
sample_flow = sample_result.flow
dummy_flow = Flow(
type=sample_flow.type,
generator=sample_flow.generator,
generator_bind=sample_flow.generator_bind,
generator_nic=sample_flow.generator_nic,
receiver=sample_flow.receiver,
receiver_bind=sample_flow.receiver_bind,
receiver_nic=sample_flow.receiver_nic,
receiver_port=None,
msg_size=sample_flow.msg_size,
duration=sample_flow.duration,
parallel_streams=sample_flow.parallel_streams,
cpupin=None,
aggregated_flow=True,
)
aggregated_result = AggregatedFlowMeasurementResults(
sample_result.measurement, dummy_flow)
nr_iterations = len(sample_result.individual_results)
for i in range(nr_iterations):
parallel_result = FlowMeasurementResults(
measurement=sample_result.measurement, flow=dummy_flow)
parallel_result.generator_results = ParallelPerfResult()
parallel_result.generator_cpu_stats = ParallelPerfResult()
parallel_result.receiver_results = ParallelPerfResult()
parallel_result.receiver_cpu_stats = ParallelPerfResult()
for result in results:
flow_result = result.individual_results[i]
parallel_result.generator_results.append(
flow_result.generator_results)
parallel_result.receiver_results.append(
flow_result.receiver_results)
parallel_result.generator_cpu_stats.append(
flow_result.generator_cpu_stats)
parallel_result.receiver_cpu_stats.append(
flow_result.receiver_cpu_stats)
aggregated_result.add_results(parallel_result)
return [aggregated_result]
def _parse_job_samples(self, job: Job) ->\
Tuple[ParallelPerfResult, ParallelPerfResult]:
"""
each perfinterval is samples.csv line #2 (l2) - line #1 (l1) to get # transactions and duration
timestamp is time of l1, but we need to convert it from CLOCK_MONOTONIC time to unix time.
samples.csv looks like this:
```
tid,flow_id,time,transactions,utime,stime,maxrss,minflt,majflt,nvcsw,nivcsw,latency_min,latency_mean,latency_max,latency_stddev
0,0,1898645.747723502,1,0.000371,0.000000,1144,39,0,2,0,0.000000,0.000000,0.000000,-nan
0,0,1898647.747733162,59322,0.185458,0.241758,1144,43,0,59320,0,0.000000,0.000000,0.000000,0.000000
0,0,1898648.747757407,89210,0.281500,0.354934,1144,43,0,89207,0,0.000000,0.000000,0.000000,0.000000
0,0,1898649.747737156,118790,0.281500,0.354934,1144,43,0,89207,0,0.000000,0.000000,0.000000,0.000000
```
:param job:
:type job:
:return:
:rtype:
"""
results = SequentialPerfResult()
cpu_results = SequentialPerfResult()
if not job.passed:
results.append(PerfInterval(0, 0, "transactions", time.time()))
cpu_results.append(PerfInterval(0, 0, "cpu_percent", time.time()))
elif job.what.is_crr_server():
# Neper doesn't support server stats for tcp_crr due to memory issues.
# Use perf_interval of 0.
# For duration neper doesn't have time_start/time_end for tcp_crr
# So just use the value of test length
d = float(job.what.params.test_length)
results.append(PerfInterval(0, d, "transactions", time.time()))
cpu_results.append(PerfInterval(0, d, "cpu_percent", time.time()))
else:
job_start = job.result['start_time']
samples = job.result['samples']
if samples is not None:
neper_start_time = float(samples[0]['time'])
for s_start, s_end in pairwise(samples):
flow, cpu = get_interval(s_start, s_end,
job_start, neper_start_time)
results.append(flow)
cpu_results.append(cpu)
#Wrap in ParallelPerfResult for now for easier graphing
#TODO When we add support for multiple flows and threads
#We want to update this accordingly.
p_results = ParallelPerfResult()
p_results.append(results)
p_cpu_results = ParallelPerfResult()
p_cpu_results.append(cpu_results)
return p_results, p_cpu_results
def _parse_job_streams(self, job):
result = ParallelPerfResult()
if not job.passed:
result.append(PerfInterval(0, 0, "bits"))
else:
for i in job.result["data"]["end"]["streams"]:
result.append(SequentialPerfResult())
for interval in job.result["data"]["intervals"]:
for i, stream in enumerate(interval["streams"]):
result[i].append(
PerfInterval(stream["bytes"] * 8, stream["seconds"],
"bits"))
return result
def _parse_job_streams(self, job):
result = ParallelPerfResult()
if not job.passed:
result.append(PerfInterval(0, 0, "bits", time.time()))
else:
for i in job.result["data"]["end"]["streams"]:
result.append(SequentialPerfResult())
job_start = job.result["data"]["start"]["timestamp"]["timesecs"]
for interval in job.result["data"]["intervals"]:
interval_start = interval["sum"]["start"]
for i, stream in enumerate(interval["streams"]):
result[i].append(PerfInterval(stream["bytes"] * 8,
stream["seconds"],
"bits", job_start + interval_start))
return result
ParallelPerfResult(
ParallelPerfResult(
SequentialPerfResult([
PerfInterval(value=8708503410.285599,
duration=1.0004048347473145,
unit="bits",
timestamp=1642059692),
PerfInterval(value=8714238798.109116,
duration=1.000683069229126,
unit="bits",
timestamp=1642059693.000405),
PerfInterval(value=8695993478.856504,
duration=0.9989690780639648,
unit="bits",
timestamp=1642059694.001088),
PerfInterval(value=8719970801.200619,
duration=1.000675916671753,
unit="bits",
timestamp=1642059695.000057),
PerfInterval(value=8682960442.327856,
duration=0.9997539520263672,
unit="bits",
timestamp=1642059696.000733),
PerfInterval(value=8639173440.0,
duration=0.9995779991149902,
unit="bits",
timestamp=1642059697.000487),
PerfInterval(value=8602684352.765568,
duration=0.9999890327453613,
unit="bits",
timestamp=1642059698.000065),
PerfInterval(value=8604246655.244764,
duration=1.0009279251098633,
unit="bits",
timestamp=1642059699.000054),
PerfInterval(value=8689737600.0,
duration=0.9991040229797363,
unit="bits",
timestamp=1642059700.000982),
PerfInterval(value=8655333119.999998,
duration=0.9999740123748779,
unit="bits",
timestamp=1642059701.000086),
PerfInterval(value=8727269760.0,
duration=1.0012290477752686,
unit="bits",
timestamp=1642059702.00006),
PerfInterval(value=8692866316.52941,
duration=0.9997501373291016,
unit="bits",
timestamp=1642059703.001289),
PerfInterval(value=8661589513.554712,
duration=0.9990200996398926,
unit="bits",
timestamp=1642059704.001039),
PerfInterval(value=8663151803.620401,
duration=0.9999699592590332,
unit="bits",
timestamp=1642059705.000059),
PerfInterval(value=8713196238.173647,
duration=1.0005011558532715,
unit="bits",
timestamp=1642059706.000029),
PerfInterval(value=8701205760.0,
duration=1.000087022781372,
unit="bits",
timestamp=1642059707.00053),
PerfInterval(value=8706418560.0,
duration=0.9995579719543457,
unit="bits",
timestamp=1642059708.000617),
PerfInterval(value=8586001856.349964,
duration=0.9998838901519775,
unit="bits",
timestamp=1642059709.000175),
PerfInterval(value=8552639941.408288,
duration=1.0009448528289795,
unit="bits",
timestamp=1642059710.000059),
PerfInterval(value=8709024960.0,
duration=0.9993410110473633,
unit="bits",
timestamp=1642059711.001004),
PerfInterval(value=8723098481.907879,
duration=1.0017168521881104,
unit="bits",
timestamp=1642059712.000345),
PerfInterval(value=8408901760.0,
duration=0.9994029998779297,
unit="bits",
timestamp=1642059713.002062),
PerfInterval(value=8544165890.720863,
duration=0.999985933303833,
unit="bits",
timestamp=1642059714.001465),
PerfInterval(value=8684290763.1963,
duration=1.0000500679016113,
unit="bits",
timestamp=1642059715.001451),
PerfInterval(value=8709780273.736055,
duration=1.0000219345092773,
unit="bits",
timestamp=1642059716.001501),
PerfInterval(value=8692865798.808567,
duration=0.9987020492553711,
unit="bits",
timestamp=1642059717.001523),
PerfInterval(value=8694951435.402685,
duration=1.0010781288146973,
unit="bits",
timestamp=1642059718.000225),
PerfInterval(value=8709545202.240353,
duration=1.0004808902740479,
unit="bits",
timestamp=1642059719.001303),
PerfInterval(value=8702249358.102018,
duration=0.9993131160736084,
unit="bits",
timestamp=1642059720.001784),
PerfInterval(value=8673057673.788025,
duration=1.0001170635223389,
unit="bits",
timestamp=1642059721.001097),
PerfInterval(value=8611545086.593794,
duration=0.999769926071167,
unit="bits",
timestamp=1642059722.001214),
PerfInterval(value=8541172800.0,
duration=1.0000920295715332,
unit="bits",
timestamp=1642059723.000984),
PerfInterval(value=8607376387.123661,
duration=0.9989831447601318,
unit="bits",
timestamp=1642059724.001076),
PerfInterval(value=8503914816.0,
duration=1.0019910335540771,
unit="bits",
timestamp=1642059725.000059),
PerfInterval(value=8612615232.0,
duration=0.999629020690918,
unit="bits",
timestamp=1642059726.00205),
PerfInterval(value=8675361792.0,
duration=1.0000829696655273,
unit="bits",
timestamp=1642059727.001679),
PerfInterval(value=8683481204.019453,
duration=0.9991998672485352,
unit="bits",
timestamp=1642059728.001762),
PerfInterval(value=8674620997.51447,
duration=0.9990980625152588,
unit="bits",
timestamp=1642059729.000962),
PerfInterval(value=8713715441.808777,
duration=1.0005438327789307,
unit="bits",
timestamp=1642059730.00006),
PerfInterval(value=8679311482.391106,
duration=0.9994559288024902,
unit="bits",
timestamp=1642059731.000604),
PerfInterval(value=8648035200.0,
duration=1.0011420249938965,
unit="bits",
timestamp=1642059732.00006),
PerfInterval(value=8683482240.0,
duration=1.0001649856567383,
unit="bits",
timestamp=1642059733.001202),
PerfInterval(value=8378012160.0,
duration=0.9986929893493652,
unit="bits",
timestamp=1642059734.001367),
PerfInterval(value=8547950458.776982,
duration=1.0002140998840332,
unit="bits",
timestamp=1642059735.00006),
PerfInterval(value=8685567360.0,
duration=1.000385046005249,
unit="bits",
timestamp=1642059736.000274),
PerfInterval(value=8677749194.726856,
duration=0.9997501373291016,
unit="bits",
timestamp=1642059737.000659),
PerfInterval(value=8703813196.750051,
duration=1.0007960796356201,
unit="bits",
timestamp=1642059738.000409),
PerfInterval(value=8627184000.0,
duration=1.0008490085601807,
unit="bits",
timestamp=1642059739.001205),
PerfInterval(value=8692865280.0,
duration=0.9993150234222412,
unit="bits",
timestamp=1642059740.002054),
PerfInterval(value=8642822915.827566,
duration=0.9986910820007324,
unit="bits",
timestamp=1642059741.001369),
PerfInterval(value=8703185842.501377,
duration=1.0000019073486328,
unit="bits",
timestamp=1642059742.00006),
PerfInterval(value=8677852160.0,
duration=1.0011889934539795,
unit="bits",
timestamp=1642059743.000062),
PerfInterval(value=8690779123.911945,
duration=0.9999358654022217,
unit="bits",
timestamp=1642059744.001251),
PerfInterval(value=8685046080.0,
duration=1.0002319812774658,
unit="bits",
timestamp=1642059745.001187),
PerfInterval(value=8578704960.0,
duration=0.9987289905548096,
unit="bits",
timestamp=1642059746.001419),
PerfInterval(value=8679577152.0,
duration=1.0011160373687744,
unit="bits",
timestamp=1642059747.000148),
PerfInterval(value=8703026247.286531,
duration=0.9989490509033203,
unit="bits",
timestamp=1642059748.001264),
PerfInterval(value=8695992960.0,
duration=0.9998459815979004,
unit="bits",
timestamp=1642059749.000213),
PerfInterval(value=8711631360.0,
duration=1.0000200271606445,
unit="bits",
timestamp=1642059750.000059),
PerfInterval(value=8694429120.0,
duration=1.000627040863037,
unit="bits",
timestamp=1642059751.000079),
]))))
def utilization(self):
return ParallelPerfResult([self._data["user"], self._data["nice"],
self._data["system"], self._data["irq"], self._data["softirq"],
self._data["steal"]])