def main():
# LODATAStruct_mul
flat_test_workloads = [TEST_WORKLOADS[t] for t in TEST_WORKLOADS]
flat_test_workloads = [e for l in flat_test_workloads for e in l]
lods = make_LODatastruct_mul(flat_test_workloads,
DATA_FOLDER,
CONFIG_PATH,
with_intensive=False,
si=True,
destroy=False)
print("Running tests on newly created lods object....")
check_shared_configs_consistency(lods)
assert_no_shared_in_test(lods)
assert_no_shared_in_test(lods, 'shared_traincomplement')
lods.serialize(os.path.join(OUTPUT_FOLDER, "lods_mul_var.bin"),
destroy=True)
# Now reads the serialized object and repeat the tests
print("\nRepeating tests after reading serialized lods...")
lods = None
lods = LODataStruct.load_from_file(os.path.join(OUTPUT_FOLDER,
"lods_mul_var.bin"),
autobuild=True)
check_shared_configs_consistency(lods)
assert_no_shared_in_test(lods)
assert_no_shared_in_test(lods, 'shared_traincomplement')
def main():
if not os.path.exists(OUT_FOLDER):
os.makedirs(OUT_FOLDER)
for fname in os.listdir(IN_FOLDER):
if ".bin" in fname:
fpath = os.path.join(IN_FOLDER, fname)
lods = LODataStruct.load_from_file(os.path.join(fpath),
autobuild=False)
lods.serialize(os.path.join(OUT_FOLDER, fname), destroy=True)
def main():
print("Loading LODS...")
lods = {}
lods_mul = LODataStruct.load_from_file(os.path.join(
OUTPUT_FOLDER, "lods_mul.bin"), autobuild=True)
lods["mul"] = lods_mul
for t in TEMPLATES:
lods[t] = LODataStruct.load_from_file(os.path.join(
OUTPUT_FOLDER, "lods_{}.bin".format(t)), autobuild=True)
print("LODS loaded, starting tests...")
# 1) Make sure test data the same between LODS_X and LODS_mul
test_eval_jobs(lods, 'test')
test_eval_splits(lods, 'test')
# 2) Make sure observation data is the same between LODS_X and LODS_mul
test_eval_jobs(lods, 'traincomplement')
test_eval_splits(lods, 'traincomplement')
# 3) Make sure training data points in LODS_X also appear in LODS_mul
test_training_jobs(lods, "trainval")
test_training_splits(lods, "trainval")
def read_lods(describe=False):
# Autobuild is set to false because persisted as built object.
lods = LODataStruct.load_from_file(os.path.join(
LODS_FOLDER_PATH, LODS_FNAME), autobuild=False)
# Overwrite folder containing csvs and autobuild
csv_folder = "../../../../datasets/tpcx-bb/"
lods.folder = csv_folder
lods._autobuild()
# Notice that I didn't call minmaxscale, because Ottertune code does that.
if describe:
lods.describe()
return lods
def get_lods(describe=False):
# autobuild is set to false because persisted as built object.
lods = LODataStruct.load_from_file(os.path.join(LODS_FOLDER_PATH,
LODS_FNAME),
autobuild=False)
# Overwrite folder containing csvs and autobuild
csv_folder = "../../../../datasets/tpcx-bb/"
lods.folder = csv_folder
lods._autobuild()
lods.minmaxscale("X")
lods.minmaxscale("Y")
if describe:
lods.describe()
return lods
def get_lods(describe=False):
# autobuild is set to false because persisted as built object.
lods = LODataStruct.load_from_file(os.path.join(
LODS_FOLDER_PATH, LODS_FNAME), autobuild=False)
# Overwrite folder containing csvs and autobuild
lods.id_to_fname = None # backward compatibility for streaming
csv_folder = "../../../../datasets/streaming/"
lods.folder = csv_folder
lods._autobuild()
lods.minmaxscale("X")
lods.minmaxscale("Y")
if describe:
lods.describe()
return lods
def make_LODatastruct_mul(
test_workloads, data_folder, config_path, with_intensive=False,
si=False, destroy_on_serialize=False, config_dict=None,
shared_within_templates=True):
"""Makes and serializes LODS_mul for workload mapping scenarios.
test_workloads: list
Contains the list of test workloads
data_folder: str
Path to folder containing csv files for each workloads data.
config_path: str
Path to a json configuration file that defines the splits.
with_intensive: bool
Whether or not to include intensive workloads
si: bool, default=False
si stands for 'separate intersections'. Indicates whether or not we
need to separate intersecting (shared) configurations across a
particular template from non-intersecting configurations.
config_dict: dict
Dictionary containing settings put into config.py when this LODS was created.
shared_within_templates: boolean, default=True
Whether the shared configurations intersections should be computed within templates
or across all workloads (beyond template definition)
"""
param_training_workloads = sorted(
list(set(PARAM_WORKLOADS) - set(test_workloads)))
if with_intensive:
training_workloads = INTENSIVE_WORKLOADS + param_training_workloads
else:
training_workloads = param_training_workloads
lods = LODataStruct(test_workloads, lo_config_path=config_path,
test_size=0.8)
lods.read_jobs_data(training_workloads+test_workloads,
data_folder, id_to_fname=id_to_str)
if shared_within_templates:
lods.build(
separate_intersections=si, templates=TEMPLATES)
else:
lods.build(separate_intersections=si)
if config_dict is not None:
lods.set_config_dict(config_dict)
lods.serialize(os.path.join(OUTPUT_FOLDER, "lods_mul.bin"),
destroy=destroy_on_serialize)
return lods
def make_LODatastruct_X(template_X, test_X, data_folder,
config_path,
with_intensive=False,
split_definitions=None,
X="X", destroy_on_serialize=False,
separate_intersections=False,
config_dict=None,
shared_within_templates=True):
""" Makes and serializes LODS_X for left out template scenarios
template_X: list
List of workloads from the template X
test_X: list
List of test workloads from this template
data_folder: str
Path to folder containing csv files for each workloads data.
config_path: str
Path to a json configuration file that defines the splits.
with_intensive: boolean
Whether or not to include intensive workloads
split_definitions: dict
Contains split definitinons for the datasets trainval, traincomplement,
test, shared_trainval, shared_traincomplement.
config_dict: dict
Dictionary containing the values of the global variables defined in
config.py at the moment of creation of LODS.
separate_intersections: boolean, default=False
Whether or not to put the intersecting (shared) configurations across
workloads into a separate dataset (prefixed by the word "shared")
config_dict: dict
Dictionary containing settings put into config.py when this LODS was created.
shared_within_templates: boolean, default=True
Whether the shared configurations intersections should be computed within templates
or across all workloads (beyond template definition)
"""
# X can be any of "A", "B", "C", ... "G" (templates)
param_except_X = sorted(
list(set(PARAM_WORKLOADS) - set(template_X)))
aux = [TEST_WORKLOADS[t] for t in TEST_WORKLOADS]
flatten_test_workloads = [e for l in aux for e in l]
param_except_X_and_other_test = sorted(
list(set(param_except_X) - set(flatten_test_workloads)))
if separate_intersections:
# jobs in template X but not in test (only used for intersections)
# plus test jobs from other templates
additional_jobs = list(set(template_X) - set(flatten_test_workloads))
for temp_name in TEST_WORKLOADS:
for j in TEST_WORKLOADS[temp_name]:
if j not in test_X:
additional_jobs.append(j)
else:
additional_jobs = []
if with_intensive:
training_except_X = INTENSIVE_WORKLOADS + param_except_X_and_other_test
else:
training_except_X = param_except_X_and_other_test
lods = LODataStruct(test_X, lo_config_path=config_path,
test_size=0.8)
lods.read_jobs_data(training_except_X+test_X, data_folder,
additional_jobs=additional_jobs, id_to_fname=id_to_str)
if shared_within_templates:
lods.build(
imported_sd=split_definitions,
separate_intersections=separate_intersections,
templates=TEMPLATES)
else:
lods.build(
imported_sd=split_definitions,
separate_intersections=separate_intersections)
if config_dict is not None:
lods.set_config_dict(config_dict)
lods.serialize(os.path.join(OUTPUT_FOLDER, "lods_{}.bin".format(X)),
destroy=destroy_on_serialize)
def main():
if not os.path.exists(OUTPUT_FOLDER):
os.makedirs(OUTPUT_FOLDER)
config_dict = get_config_dict()
flat_test_workloads = [TEST_WORKLOADS[t] for t in TEST_WORKLOADS]
flat_test_workloads = [e for l in flat_test_workloads for e in l]
lods = make_LODatastruct_mul(
flat_test_workloads, DATA_FOLDER, CONFIG_PATH,
with_intensive=WITH_INTENSIVE, si=SEPARATE_INTERSECTIONS_MUL,
config_dict=config_dict,
shared_within_templates=SHARED_WITHIN_TEMPLATES)
sd = lods.get_split_definitions()
for temp in TEMPLATES:
print("[making LODS_{}]".format(temp))
make_LODatastruct_X(
TEMPLATES[temp],
TEST_WORKLOADS[temp],
DATA_FOLDER, CONFIG_PATH, with_intensive=WITH_INTENSIVE,
split_definitions=sd, X=temp,
separate_intersections=SEPARATE_INTERSECTIONS_X,
config_dict=config_dict,
shared_within_templates=SHARED_WITHIN_TEMPLATES)
autobuild = DESTROY_ON_SERIALIZE
print("Loading LODS...")
lods = {}
lods_mul = LODataStruct.load_from_file(os.path.join(
OUTPUT_FOLDER, "lods_mul.bin"),
autobuild=DESTROY_ON_SERIALIZE)
lods["mul"] = lods_mul
print("LODS_mul loaded...")
for t in TEMPLATES:
print("Loading LODS_{}".format(t))
lods[t] = LODataStruct.load_from_file(
os.path.join(OUTPUT_FOLDER, "lods_{}.bin".format(t)),
autobuild=DESTROY_ON_SERIALIZE)
for lod_name in lods:
lods[lod_name].minmaxscale("X")
lods[lod_name].minmaxscale("Y")
print("LODS loaded, starting tests...")
print("**** CONSISTENCY TESTS (LODS_mul & LODS_X) *****")
test_eval_jobs(lods, 'test')
test_eval_splits(lods, 'test')
test_eval_jobs(lods, 'traincomplement')
test_eval_splits(lods, 'traincomplement')
test_training_jobs(lods, "trainval")
test_training_splits(lods, "trainval")
print("**** ***** *****")
if SEPARATE_INTERSECTIONS_MUL:
print("***** SHARED/UNSHARED TESTS ON LODS_mul *****")
check_shared_configs_consistency(lods["mul"])
assert_no_shared_in_test(lods["mul"])
assert_no_shared_in_test(lods["mul"], 'shared_traincomplement')
