Commit 1bc2a2d9 authored by Karol Latecki's avatar Karol Latecki Committed by Tomasz Zawadzki
Browse files

scripts/nvmf_perf: fix clat percentile calculations 



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: default avatarKarol Latecki <karol.latecki@intel.com>
Reviewed-on: https://review.spdk.io/gerrit/c/spdk/spdk/+/5466


Tested-by: default avatarSPDK CI Jenkins <sys_sgci@intel.com>
Reviewed-by: default avatarTomasz Zawadzki <tomasz.zawadzki@intel.com>
Reviewed-by: default avatarJohn Kariuki <John.K.Kariuki@intel.com>
Reviewed-by: default avatarAleksey Marchuk <alexeymar@mellanox.com>
parent da625683

scripts/perf/nvmf/run_nvmf.py

+17 −8
Original line number Diff line number Diff line
@@ -86,6 +86,19 @@ class Target(Server): 
                    if k.startswith(key_prefix):

                        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_bw = float(data["jobs"][job_pos]["read"]["bw"])

            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_max_lat = float(data["jobs"][job_pos]["read"][lat_key]["max"])

            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_9_lat = float(data["jobs"][job_pos]["read"][clat_key]["percentile"]["99.900000"])

            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"])

            read_p99_lat, read_p99_9_lat, read_p99_99_lat, read_p99_999_lat = get_clat_percentiles(

                data["jobs"][job_pos]["read"][clat_key])



            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]]
@@ -113,10 +124,8 @@ class Target(Server): 
            write_min_lat = float(data["jobs"][job_pos]["write"][lat_key]["min"])

            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"])

            write_p99_lat = float(data["jobs"][job_pos]["write"][clat_key]["percentile"]["99.000000"])

            write_p99_9_lat = float(data["jobs"][job_pos]["write"][clat_key]["percentile"]["99.900000"])

            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"])

            write_p99_lat, write_p99_9_lat, write_p99_99_lat, write_p99_999_lat = get_clat_percentiles(

                data["jobs"][job_pos]["write"][clat_key])



            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]]