Commit bd1b0714 authored by Karol Latecki's avatar Karol Latecki Committed by Tomasz Zawadzki
Browse files

scripts/nvmf_perf: shorten dict path in results parsing 



Signed-off-by: default avatarKarol Latecki <karol.latecki@intel.com>
Change-Id: I2838cc2902ecc520a36be743ae31b708e87c8349
Reviewed-on: https://review.spdk.io/gerrit/c/spdk/spdk/+/23670


Reviewed-by: default avatarJim Harris <jim.harris@samsung.com>
Tested-by: default avatarSPDK CI Jenkins <sys_sgci@intel.com>
Reviewed-by: default avatarKrzysztof Karas <krzysztof.karas@intel.com>
Reviewed-by: default avatarKonrad Sztyber <konrad.sztyber@intel.com>
parent aea1abb9

scripts/perf/nvmf/common.py

+17 −17
Original line number Diff line number Diff line
@@ -14,7 +14,7 @@ from json.decoder import JSONDecodeError 
def read_json_stats(file):

    with open(file, "r") as json_data:

        data = json.load(json_data)

        job_pos = 0  # job_post = 0 because using aggregated results

        job_data = data["jobs"][0]  # 0 because using aggregated results, fio group reporting



        # Check if latency is in nano or microseconds to choose correct dict key

        def get_lat_unit(key_prefix, dict_section):
@@ -38,15 +38,15 @@ def read_json_stats(file): 
                # 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"])

        read_avg_lat = float(data["jobs"][job_pos]["read"][lat_key]["mean"])

        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_iops = float(job_data["read"]["iops"])

        read_bw = float(job_data["read"]["bw"])

        lat_key, lat_unit = get_lat_unit("lat", job_data["read"])

        read_avg_lat = float(job_data["read"][lat_key]["mean"])

        read_min_lat = float(job_data["read"][lat_key]["min"])

        read_max_lat = float(job_data["read"][lat_key]["max"])

        clat_key, clat_unit = get_lat_unit("clat", job_data["read"])

        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])

            job_data["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]]
@@ -56,15 +56,15 @@ def read_json_stats(file): 
            read_p99_99_lat = read_p99_99_lat / 1000

            read_p99_999_lat = read_p99_999_lat / 1000



        write_iops = float(data["jobs"][job_pos]["write"]["iops"])

        write_bw = float(data["jobs"][job_pos]["write"]["bw"])

        lat_key, lat_unit = get_lat_unit("lat", data["jobs"][job_pos]["write"])

        write_avg_lat = float(data["jobs"][job_pos]["write"][lat_key]["mean"])

        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_iops = float(job_data["write"]["iops"])

        write_bw = float(job_data["write"]["bw"])

        lat_key, lat_unit = get_lat_unit("lat", job_data["write"])

        write_avg_lat = float(job_data["write"][lat_key]["mean"])

        write_min_lat = float(job_data["write"][lat_key]["min"])

        write_max_lat = float(job_data["write"][lat_key]["max"])

        clat_key, clat_unit = get_lat_unit("clat", job_data["write"])

        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])

            job_data["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]]