-# Copyright (c) 2018 Cisco and/or its affiliates.
+# Copyright (c) 2019 Cisco and/or its affiliates.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at:
from datetime import timedelta
from utils import mean, stdev, relative_change, classify_anomalies, \
- convert_csv_to_pretty_txt
+ convert_csv_to_pretty_txt, relative_change_stdev
REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*')
try:
col_data = str(data[job][build][test][column["data"].
split(" ")[1]]).replace('"', '""')
- if column["data"].split(" ")[1] in ("vat-history",
+ if column["data"].split(" ")[1] in ("conf-history",
"show-run"):
col_data = replace(col_data, " |br| ", "",
maxreplace=1)
try:
col_data = str(data[test][column["data"].
split(" ")[1]]).replace('"', '""')
- if column["data"].split(" ")[1] in ("vat-history",
+ col_data = replace(col_data, "No Data",
+ "Not Captured ")
+ if column["data"].split(" ")[1] in ("conf-history",
"show-run"):
col_data = replace(col_data, " |br| ", "",
maxreplace=1)
format(col_data[:-5])
row_lst.append('"{0}"'.format(col_data))
except KeyError:
- row_lst.append("No data")
+ row_lst.append('"Not captured"')
table_lst.append(row_lst)
# Write the data to file
header = ["Test case", ]
if table["include-tests"] == "MRR":
- hdr_param = "Receive Rate"
+ hdr_param = "Rec Rate"
else:
- hdr_param = "Throughput"
+ hdr_param = "Thput"
history = table.get("history", None)
if history:
# Prepare data to the table:
tbl_dict = dict()
for job, builds in table["reference"]["data"].items():
+ topo = "2n-skx" if "2n-skx" in job else ""
for build in builds:
for tst_name, tst_data in data[job][str(build)].iteritems():
tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
if "across topologies" in table["title"].lower():
tst_name_mod = tst_name_mod.replace("2n1l-", "")
if tbl_dict.get(tst_name_mod, None) is None:
- name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
- "-".join(tst_data["name"].
- split("-")[:-1]))
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ nic = groups.group(0) if groups else ""
+ name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
+ split("-")[:-1]))
if "across testbeds" in table["title"].lower() or \
"across topologies" in table["title"].lower():
name = name.\
replace("4t4c", "4c").replace("8t4c", "4c")
if "across topologies" in table["title"].lower():
tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ nic = groups.group(0) if groups else ""
+ name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
+ split("-")[:-1]))
+ if "across testbeds" in table["title"].lower() or \
+ "across topologies" in table["title"].lower():
+ name = name.\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
try:
# TODO: Re-work when NDRPDRDISC tests are not used
if table["include-tests"] == "MRR":
tst_data["throughput"]["NDR"]["LOWER"])
else:
continue
- except KeyError:
+ except (KeyError, TypeError):
pass
+ if history:
+ for item in history:
+ for job, builds in item["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
+ replace("-ndrpdr", "").replace("-pdrdisc", ""). \
+ replace("-ndrdisc", "").replace("-pdr", ""). \
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ if "across topologies" in table["title"].lower():
+ tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ continue
+ if tbl_dict[tst_name_mod].get("history", None) is None:
+ tbl_dict[tst_name_mod]["history"] = OrderedDict()
+ if tbl_dict[tst_name_mod]["history"].get(item["title"],
+ None) is None:
+ tbl_dict[tst_name_mod]["history"][item["title"]] = \
+ list()
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["history"][item["title"
+ ]].append(tst_data["result"]["receive-rate"].
+ avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["history"][
+ item["title"]].\
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["history"][item[
+ "title"]].append(tst_data["throughput"][
+ "PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["history"][
+ item["title"]].\
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["history"][item[
+ "title"]].append(tst_data["throughput"][
+ "NDR"]["LOWER"])
+ else:
+ continue
+ except (TypeError, KeyError):
+ pass
+
+ tbl_lst = list()
+ footnote = False
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ if history:
+ if tbl_dict[tst_name].get("history", None) is not None:
+ for hist_data in tbl_dict[tst_name]["history"].values():
+ if hist_data:
+ item.append(round(mean(hist_data) / 1000000, 2))
+ item.append(round(stdev(hist_data) / 1000000, 2))
+ else:
+ item.extend(["Not tested", "Not tested"])
+ else:
+ item.extend(["Not tested", "Not tested"])
+ data_t = tbl_dict[tst_name]["ref-data"]
+ if data_t:
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
+ else:
+ item.extend(["Not tested", "Not tested"])
+ data_t = tbl_dict[tst_name]["cmp-data"]
+ if data_t:
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
+ else:
+ item.extend(["Not tested", "Not tested"])
+ if item[-2] == "Not tested":
+ pass
+ elif item[-4] == "Not tested":
+ item.append("New in CSIT-1908")
+ elif topo == "2n-skx" and "dot1q" in tbl_dict[tst_name]["name"]:
+ item.append("See footnote [1]")
+ footnote = True
+ elif item[-4] != 0:
+ item.append(int(relative_change(float(item[-4]), float(item[-2]))))
+ if (len(item) == len(header)) and (item[-3] != "Not tested"):
+ tbl_lst.append(item)
+
+ # Sort the table:
+ # 1. New in CSIT-XXXX
+ # 2. See footnote
+ # 3. Delta
+ tbl_new = list()
+ tbl_see = list()
+ tbl_delta = list()
+ for item in tbl_lst:
+ if isinstance(item[-1], str):
+ if "New in CSIT" in item[-1]:
+ tbl_new.append(item)
+ elif "See footnote" in item[-1]:
+ tbl_see.append(item)
+ else:
+ tbl_delta.append(item)
+
+ # Sort the tables:
+ tbl_new.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_see.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_see.sort(key=lambda rel: rel[-1], reverse=False)
+ tbl_delta.sort(key=lambda rel: rel[-1], reverse=True)
+
+ # Put the tables together:
+ tbl_lst = list()
+ tbl_lst.extend(tbl_new)
+ tbl_lst.extend(tbl_see)
+ tbl_lst.extend(tbl_delta)
+
+ # Generate csv tables:
+ csv_file = "{0}.csv".format(table["output-file"])
+ with open(csv_file, "w") as file_handler:
+ file_handler.write(header_str)
+ for test in tbl_lst:
+ file_handler.write(",".join([str(item) for item in test]) + "\n")
+
+ txt_file_name = "{0}.txt".format(table["output-file"])
+ convert_csv_to_pretty_txt(csv_file, txt_file_name)
+
+ if footnote:
+ with open(txt_file_name, 'a') as txt_file:
+ txt_file.writelines([
+ "\nFootnotes:\n",
+ "[1] CSIT-1908 changed test methodology of dot1q tests in "
+ "2-node testbeds, dot1q encapsulation is now used on both "
+ "links of SUT.\n",
+ " Previously dot1q was used only on a single link with the "
+ "other link carrying untagged Ethernet frames. This changes "
+ "results\n",
+ " in slightly lower throughput in CSIT-1908 for these "
+ "tests. See release notes."
+ ])
+
+
+def table_performance_comparison_nic(table, input_data):
+ """Generate the table(s) with algorithm: table_performance_comparison
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the tables
+ try:
+ header = ["Test case", ]
+
+ if table["include-tests"] == "MRR":
+ hdr_param = "Rec Rate"
+ else:
+ hdr_param = "Thput"
+
+ history = table.get("history", None)
+ if history:
+ for item in history:
+ header.extend(
+ ["{0} {1} [Mpps]".format(item["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(item["title"])])
+ header.extend(
+ ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["reference"]["title"]),
+ "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["compare"]["title"]),
+ "Delta [%]"])
+ header_str = ",".join(header) + "\n"
+ except (AttributeError, KeyError) as err:
+ logging.error("The model is invalid, missing parameter: {0}".
+ format(err))
+ return
+
+ # Prepare data to the table:
+ tbl_dict = dict()
+ for job, builds in table["reference"]["data"].items():
+ topo = "2n-skx" if "2n-skx" in job else ""
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ if table["reference"]["nic"] not in tst_data["tags"]:
+ continue
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
+ replace("-ndrpdr", "").replace("-pdrdisc", "").\
+ replace("-ndrdisc", "").replace("-pdr", "").\
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ if "across topologies" in table["title"].lower():
+ tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ name = "{0}".format("-".join(tst_data["name"].
+ split("-")[:-1]))
+ if "across testbeds" in table["title"].lower() or \
+ "across topologies" in table["title"].lower():
+ name = name.\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["ref-data"]. \
+ append(tst_data["result"]["receive-rate"].avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["ref-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["ref-data"].append(
+ tst_data["throughput"]["PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["ref-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["ref-data"].append(
+ tst_data["throughput"]["NDR"]["LOWER"])
+ else:
+ continue
except TypeError:
- tbl_dict.pop(tst_name_mod, None)
+ pass # No data in output.xml for this test
+
+ for job, builds in table["compare"]["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ if table["compare"]["nic"] not in tst_data["tags"]:
+ continue
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
+ replace("-ndrpdr", "").replace("-pdrdisc", ""). \
+ replace("-ndrdisc", "").replace("-pdr", ""). \
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ if "across topologies" in table["title"].lower():
+ tst_name_mod = tst_name_mod.replace("2n1l-", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ name = "{0}".format("-".join(tst_data["name"].
+ split("-")[:-1]))
+ if "across testbeds" in table["title"].lower() or \
+ "across topologies" in table["title"].lower():
+ name = name.\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["cmp-data"]. \
+ append(tst_data["result"]["receive-rate"].avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["cmp-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["cmp-data"].append(
+ tst_data["throughput"]["PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["cmp-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["cmp-data"].append(
+ tst_data["throughput"]["NDR"]["LOWER"])
+ else:
+ continue
+ except (KeyError, TypeError):
+ pass
+
if history:
for item in history:
for job, builds in item["data"].items():
for build in builds:
for tst_name, tst_data in data[job][str(build)].iteritems():
+ if item["nic"] not in tst_data["tags"]:
+ continue
tst_name_mod = tst_name.replace("-ndrpdrdisc", ""). \
replace("-ndrpdr", "").replace("-pdrdisc", ""). \
replace("-ndrdisc", "").replace("-pdr", ""). \
replace("1t1c", "1c").replace("2t1c", "1c").\
replace("2t2c", "2c").replace("4t2c", "2c").\
replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
if "across topologies" in table["title"].lower():
tst_name_mod = tst_name_mod.replace("2n1l-", "")
if tbl_dict.get(tst_name_mod, None) is None:
pass
tbl_lst = list()
+ footnote = False
for tst_name in tbl_dict.keys():
item = [tbl_dict[tst_name]["name"], ]
if history:
item.append(round(mean(hist_data) / 1000000, 2))
item.append(round(stdev(hist_data) / 1000000, 2))
else:
- item.extend([None, None])
+ item.extend(["Not tested", "Not tested"])
else:
- item.extend([None, None])
+ item.extend(["Not tested", "Not tested"])
+ data_t = tbl_dict[tst_name]["ref-data"]
+ if data_t:
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
+ else:
+ item.extend(["Not tested", "Not tested"])
+ data_t = tbl_dict[tst_name]["cmp-data"]
+ if data_t:
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
+ else:
+ item.extend(["Not tested", "Not tested"])
+ if item[-2] == "Not tested":
+ pass
+ elif item[-4] == "Not tested":
+ item.append("New in CSIT-1908")
+ elif topo == "2n-skx" and "dot1q" in tbl_dict[tst_name]["name"]:
+ item.append("See footnote [1]")
+ footnote = True
+ elif item[-4] != 0:
+ item.append(int(relative_change(float(item[-4]), float(item[-2]))))
+ if (len(item) == len(header)) and (item[-3] != "Not tested"):
+ tbl_lst.append(item)
+
+ # Sort the table:
+ # 1. New in CSIT-XXXX
+ # 2. See footnote
+ # 3. Delta
+ tbl_new = list()
+ tbl_see = list()
+ tbl_delta = list()
+ for item in tbl_lst:
+ if isinstance(item[-1], str):
+ if "New in CSIT" in item[-1]:
+ tbl_new.append(item)
+ elif "See footnote" in item[-1]:
+ tbl_see.append(item)
+ else:
+ tbl_delta.append(item)
+
+ # Sort the tables:
+ tbl_new.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_see.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_see.sort(key=lambda rel: rel[-1], reverse=False)
+ tbl_delta.sort(key=lambda rel: rel[-1], reverse=True)
+
+ # Put the tables together:
+ tbl_lst = list()
+ tbl_lst.extend(tbl_new)
+ tbl_lst.extend(tbl_see)
+ tbl_lst.extend(tbl_delta)
+
+ # Generate csv tables:
+ csv_file = "{0}.csv".format(table["output-file"])
+ with open(csv_file, "w") as file_handler:
+ file_handler.write(header_str)
+ for test in tbl_lst:
+ file_handler.write(",".join([str(item) for item in test]) + "\n")
+
+ txt_file_name = "{0}.txt".format(table["output-file"])
+ convert_csv_to_pretty_txt(csv_file, txt_file_name)
+
+ if footnote:
+ with open(txt_file_name, 'a') as txt_file:
+ txt_file.writelines([
+ "\nFootnotes:\n",
+ "[1] CSIT-1908 changed test methodology of dot1q tests in "
+ "2-node testbeds, dot1q encapsulation is now used on both "
+ "links of SUT.\n",
+ " Previously dot1q was used only on a single link with the "
+ "other link carrying untagged Ethernet frames. This changes "
+ "results\n",
+ " in slightly lower throughput in CSIT-1908 for these "
+ "tests. See release notes."
+ ])
+
+
+def table_nics_comparison(table, input_data):
+ """Generate the table(s) with algorithm: table_nics_comparison
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the tables
+ try:
+ header = ["Test case", ]
+
+ if table["include-tests"] == "MRR":
+ hdr_param = "Rec Rate"
+ else:
+ hdr_param = "Thput"
+
+ header.extend(
+ ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["reference"]["title"]),
+ "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["compare"]["title"]),
+ "Delta [%]"])
+ header_str = ",".join(header) + "\n"
+ except (AttributeError, KeyError) as err:
+ logging.error("The model is invalid, missing parameter: {0}".
+ format(err))
+ return
+
+ # Prepare data to the table:
+ tbl_dict = dict()
+ for job, builds in table["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
+ replace("-ndrpdr", "").replace("-pdrdisc", "").\
+ replace("-ndrdisc", "").replace("-pdr", "").\
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ if tbl_dict.get(tst_name_mod, None) is None:
+ name = "-".join(tst_data["name"].split("-")[:-1])
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
+ try:
+ if table["include-tests"] == "MRR":
+ result = tst_data["result"]["receive-rate"].avg
+ elif table["include-tests"] == "PDR":
+ result = tst_data["throughput"]["PDR"]["LOWER"]
+ elif table["include-tests"] == "NDR":
+ result = tst_data["throughput"]["NDR"]["LOWER"]
+ else:
+ result = None
+
+ if result:
+ if table["reference"]["nic"] in tst_data["tags"]:
+ tbl_dict[tst_name_mod]["ref-data"].append(result)
+ elif table["compare"]["nic"] in tst_data["tags"]:
+ tbl_dict[tst_name_mod]["cmp-data"].append(result)
+ except (TypeError, KeyError) as err:
+ logging.debug("No data for {0}".format(tst_name))
+ logging.debug(repr(err))
+ # No data in output.xml for this test
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
data_t = tbl_dict[tst_name]["ref-data"]
if data_t:
item.append(round(mean(data_t) / 1000000, 2))
convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
+def table_soak_vs_ndr(table, input_data):
+ """Generate the table(s) with algorithm: table_soak_vs_ndr
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the table
+ try:
+ header = [
+ "Test case",
+ "{0} Thput [Mpps]".format(table["reference"]["title"]),
+ "{0} Stdev [Mpps]".format(table["reference"]["title"]),
+ "{0} Thput [Mpps]".format(table["compare"]["title"]),
+ "{0} Stdev [Mpps]".format(table["compare"]["title"]),
+ "Delta [%]", "Stdev of delta [%]"]
+ header_str = ",".join(header) + "\n"
+ except (AttributeError, KeyError) as err:
+ logging.error("The model is invalid, missing parameter: {0}".
+ format(err))
+ return
+
+ # Create a list of available SOAK test results:
+ tbl_dict = dict()
+ for job, builds in table["compare"]["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ if tst_data["type"] == "SOAK":
+ tst_name_mod = tst_name.replace("-soak", "")
+ if tbl_dict.get(tst_name_mod, None) is None:
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ nic = groups.group(0) if groups else ""
+ name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
+ split("-")[:-1]))
+ tbl_dict[tst_name_mod] = {
+ "name": name,
+ "ref-data": list(),
+ "cmp-data": list()
+ }
+ try:
+ tbl_dict[tst_name_mod]["cmp-data"].append(
+ tst_data["throughput"]["LOWER"])
+ except (KeyError, TypeError):
+ pass
+ tests_lst = tbl_dict.keys()
+
+ # Add corresponding NDR test results:
+ for job, builds in table["reference"]["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdr", "").\
+ replace("-mrr", "")
+ if tst_name_mod in tests_lst:
+ try:
+ if tst_data["type"] in ("NDRPDR", "MRR", "BMRR"):
+ if table["include-tests"] == "MRR":
+ result = tst_data["result"]["receive-rate"].avg
+ elif table["include-tests"] == "PDR":
+ result = tst_data["throughput"]["PDR"]["LOWER"]
+ elif table["include-tests"] == "NDR":
+ result = tst_data["throughput"]["NDR"]["LOWER"]
+ else:
+ result = None
+ if result is not None:
+ tbl_dict[tst_name_mod]["ref-data"].append(
+ result)
+ except (KeyError, TypeError):
+ continue
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ data_r = tbl_dict[tst_name]["ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
+ else:
+ data_r_mean = None
+ data_r_stdev = None
+ item.extend([None, None])
+ data_c = tbl_dict[tst_name]["cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
+ else:
+ data_c_mean = None
+ data_c_stdev = None
+ item.extend([None, None])
+ if data_r_mean and data_c_mean:
+ delta, d_stdev = relative_change_stdev(
+ data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
+ item.append(round(delta, 2))
+ item.append(round(d_stdev, 2))
+ tbl_lst.append(item)
+
+ # Sort the table according to the relative change
+ tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
+
+ # Generate csv tables:
+ csv_file = "{0}.csv".format(table["output-file"])
+ with open(csv_file, "w") as file_handler:
+ file_handler.write(header_str)
+ for test in tbl_lst:
+ file_handler.write(",".join([str(item) for item in test]) + "\n")
+
+ convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
+
+
def table_performance_trending_dashboard(table, input_data):
"""Generate the table(s) with algorithm:
table_performance_trending_dashboard
for job, builds in table["data"].items():
for build in builds:
for tst_name, tst_data in data[job][str(build)].iteritems():
- if tst_name.lower() in table["ignore-list"]:
+ if tst_name.lower() in table.get("ignore-list", list()):
continue
if tbl_dict.get(tst_name, None) is None:
groups = re.search(REGEX_NIC, tst_data["parent"])
if classification_lst:
if isnan(rel_change_last) and isnan(rel_change_long):
continue
+ if (isnan(last_avg) or
+ isnan(rel_change_last) or
+ isnan(rel_change_long)):
+ continue
tbl_lst.append(
[tbl_dict[tst_name]["name"],
- '-' if isnan(last_avg) else
round(last_avg / 1000000, 2),
- '-' if isnan(rel_change_last) else rel_change_last,
- '-' if isnan(rel_change_long) else rel_change_long,
+ rel_change_last,
+ rel_change_long,
classification_lst[-win_size:].count("regression"),
classification_lst[-win_size:].count("progression")])
file_name = "vm_vhost_l2"
if "114b" in test_name:
feature = ""
- elif "l2xcbase" in test_name:
+ elif "l2xcbase" in test_name and "x520" in test_name:
feature = "-base-l2xc"
- elif "l2bdbasemaclrn" in test_name:
+ elif "l2bdbasemaclrn" in test_name and "x520" in test_name:
feature = "-base-l2bd"
else:
feature = "-base"
file_name = "vm_vhost_ip4"
feature = "-base"
+ elif "ipsecbasetnlsw" in test_name:
+ file_name = "ipsecsw"
+ feature = "-base-scale"
+
elif "ipsec" in test_name:
file_name = "ipsec"
feature = "-base-scale"
+ if "hw-" in test_name:
+ file_name = "ipsechw"
+ elif "sw-" in test_name:
+ file_name = "ipsecsw"
+ if "-int-" in test_name:
+ feature = "-base-scale-int"
+ elif "tnl" in test_name:
+ feature = "-base-scale-tnl"
elif "ethip4lispip" in test_name or "ethip4vxlan" in test_name:
file_name = "ip4_tunnels"
nic = "xl710-"
elif "xxv710" in test_name:
nic = "xxv710-"
+ elif "vic1227" in test_name:
+ nic = "vic1227-"
+ elif "vic1385" in test_name:
+ nic = "vic1385-"
+ elif "x553" in test_name:
+ nic = "x553-"
else:
nic = ""
anchor += nic
elif "8t4c" in test_name:
anchor += "8t4c"
- return url + file_name + '-' + testbed + '-' + nic + framesize + feature + \
- anchor + feature
+ return url + file_name + '-' + testbed + '-' + nic + framesize + \
+ feature.replace("-int", "").replace("-tnl", "") + anchor + feature
def table_performance_trending_dashboard_html(table, input_data):
return
+def table_last_failed_tests(table, input_data):
+ """Generate the table(s) with algorithm: table_last_failed_tests
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+
+ logging.info(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ if data is None or data.empty:
+ logging.warn(" No data for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ return
+
+ tbl_list = list()
+ for job, builds in table["data"].items():
+ for build in builds:
+ build = str(build)
+ try:
+ version = input_data.metadata(job, build).get("version", "")
+ except KeyError:
+ logging.error("Data for {job}: {build} is not present.".
+ format(job=job, build=build))
+ return
+ tbl_list.append(build)
+ tbl_list.append(version)
+ for tst_name, tst_data in data[job][build].iteritems():
+ if tst_data["status"] != "FAIL":
+ continue
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ if not groups:
+ continue
+ nic = groups.group(0)
+ tbl_list.append("{0}-{1}".format(nic, tst_data["name"]))
+
+ file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])
+ logging.info(" Writing file: '{0}'".format(file_name))
+ with open(file_name, "w") as file_handler:
+ for test in tbl_list:
+ file_handler.write(test + '\n')
+
+
def table_failed_tests(table, input_data):
"""Generate the table(s) with algorithm: table_failed_tests
specified in the specification file.
for build in builds:
build = str(build)
for tst_name, tst_data in data[job][build].iteritems():
- if tst_name.lower() in table["ignore-list"]:
+ if tst_name.lower() in table.get("ignore-list", list()):
continue
if tbl_dict.get(tst_name, None) is None:
groups = re.search(REGEX_NIC, tst_data["parent"])
generated,
input_data.metadata(job, build).get("version", ""),
build)
- except (TypeError, KeyError):
- pass # No data in output.xml for this test
+ except (TypeError, KeyError) as err:
+ logging.warning("tst_name: {} - err: {}".
+ format(tst_name, repr(err)))
+ max_fails = 0
tbl_lst = list()
for tst_data in tbl_dict.values():
fails_nr = 0
fails_last_vpp = val[2]
fails_last_csit = val[3]
if fails_nr:
+ max_fails = fails_nr if fails_nr > max_fails else max_fails
tbl_lst.append([tst_data["name"],
fails_nr,
fails_last_date,
tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
tbl_sorted = list()
- for nrf in range(table["window"], -1, -1):
+ for nrf in range(max_fails, -1, -1):
tbl_fails = [item for item in tbl_lst if item[1] == nrf]
tbl_sorted.extend(tbl_fails)
file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])