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scripts/nvmf_perf: fix clat percentile calculations

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In case of latest fio versions "percentile" leaf for clat
latency measurements does not get created in case no IO
was run (e.g. write clat will not have "percentiles"
created in case rw mode was set to randread). This
caused KeyError exception when trying to access non-
existent dict key.

Change-Id: Ie0c28dc932481e5aab971505ba0f38b6798bff36
Signed-off-by: Karol Latecki <karol.latecki@intel.com>
Reviewed-on: https://review.spdk.io/gerrit/c/spdk/spdk/+/5466
Tested-by: SPDK CI Jenkins <sys_sgci@intel.com>
Reviewed-by: Tomasz Zawadzki <tomasz.zawadzki@intel.com>
Reviewed-by: John Kariuki <John.K.Kariuki@intel.com>
Reviewed-by: Aleksey Marchuk <alexeymar@mellanox.com>
This commit is contained in:
Karol Latecki 2020-12-07 16:10:23 +01:00 committed by Tomasz Zawadzki
parent da625683a6
commit 1bc2a2d9e9
1 changed files with 17 additions and 8 deletions
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25
scripts/perf/nvmf/run_nvmf.py
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@ -86,6 +86,19 @@ class Target(Server):
if k.startswith(key_prefix): if k.startswith(key_prefix):
return k, k.split("_")[1] return k, k.split("_")[1]
def get_clat_percentiles(clat_dict_leaf):
if "percentile" in clat_dict_leaf:
p99_lat = float(clat_dict_leaf["percentile"]["99.000000"])
p99_9_lat = float(clat_dict_leaf["percentile"]["99.900000"])
p99_99_lat = float(clat_dict_leaf["percentile"]["99.990000"])
p99_999_lat = float(clat_dict_leaf["percentile"]["99.999000"])
return [p99_lat, p99_9_lat, p99_99_lat, p99_999_lat]
else:
# Latest fio versions do not provide "percentile" results if no
# measurements were done, so just return zeroes
return [0, 0, 0, 0]
read_iops = float(data["jobs"][job_pos]["read"]["iops"]) read_iops = float(data["jobs"][job_pos]["read"]["iops"])
read_bw = float(data["jobs"][job_pos]["read"]["bw"]) read_bw = float(data["jobs"][job_pos]["read"]["bw"])
lat_key, lat_unit = get_lat_unit("lat", data["jobs"][job_pos]["read"]) lat_key, lat_unit = get_lat_unit("lat", data["jobs"][job_pos]["read"])
@ -93,10 +106,8 @@ class Target(Server):
read_min_lat = float(data["jobs"][job_pos]["read"][lat_key]["min"]) read_min_lat = float(data["jobs"][job_pos]["read"][lat_key]["min"])
read_max_lat = float(data["jobs"][job_pos]["read"][lat_key]["max"]) read_max_lat = float(data["jobs"][job_pos]["read"][lat_key]["max"])
clat_key, clat_unit = get_lat_unit("clat", data["jobs"][job_pos]["read"]) clat_key, clat_unit = get_lat_unit("clat", data["jobs"][job_pos]["read"])
read_p99_lat = float(data["jobs"][job_pos]["read"][clat_key]["percentile"]["99.000000"]) read_p99_lat, read_p99_9_lat, read_p99_99_lat, read_p99_999_lat = get_clat_percentiles(
read_p99_9_lat = float(data["jobs"][job_pos]["read"][clat_key]["percentile"]["99.900000"]) data["jobs"][job_pos]["read"][clat_key])
read_p99_99_lat = float(data["jobs"][job_pos]["read"][clat_key]["percentile"]["99.990000"])
read_p99_999_lat = float(data["jobs"][job_pos]["read"][clat_key]["percentile"]["99.999000"])
if "ns" in lat_unit: if "ns" in lat_unit:
read_avg_lat, read_min_lat, read_max_lat = [x / 1000 for x in [read_avg_lat, read_min_lat, read_max_lat]] read_avg_lat, read_min_lat, read_max_lat = [x / 1000 for x in [read_avg_lat, read_min_lat, read_max_lat]]
@ -113,10 +124,8 @@ class Target(Server):
write_min_lat = float(data["jobs"][job_pos]["write"][lat_key]["min"]) write_min_lat = float(data["jobs"][job_pos]["write"][lat_key]["min"])
write_max_lat = float(data["jobs"][job_pos]["write"][lat_key]["max"]) write_max_lat = float(data["jobs"][job_pos]["write"][lat_key]["max"])
clat_key, clat_unit = get_lat_unit("clat", data["jobs"][job_pos]["write"]) clat_key, clat_unit = get_lat_unit("clat", data["jobs"][job_pos]["write"])
write_p99_lat = float(data["jobs"][job_pos]["write"][clat_key]["percentile"]["99.000000"]) write_p99_lat, write_p99_9_lat, write_p99_99_lat, write_p99_999_lat = get_clat_percentiles(
write_p99_9_lat = float(data["jobs"][job_pos]["write"][clat_key]["percentile"]["99.900000"]) data["jobs"][job_pos]["write"][clat_key])
write_p99_99_lat = float(data["jobs"][job_pos]["write"][clat_key]["percentile"]["99.990000"])
write_p99_999_lat = float(data["jobs"][job_pos]["write"][clat_key]["percentile"]["99.999000"])
if "ns" in lat_unit: if "ns" in lat_unit:
write_avg_lat, write_min_lat, write_max_lat = [x / 1000 for x in [write_avg_lat, write_min_lat, write_max_lat]] write_avg_lat, write_min_lat, write_max_lat = [x / 1000 for x in [write_avg_lat, write_min_lat, write_max_lat]]