def post_process_for_test_mode(t):
logger.info("Preparing track [%s] for test mode." % str(t))
for index in t.indices:
for type in index.types:
if type.has_valid_document_data():
logger.info(
"Reducing corpus size to 1000 documents for [%s/%s]" %
(index, type))
type.number_of_documents = 1000
path, ext = io.splitext(type.document_archive)
path_2, ext_2 = io.splitext(path)
type.document_archive = "%s-1k%s%s" % (path_2, ext_2, ext)
type.document_file = "%s-1k%s" % (path_2, ext_2)
# we don't want to check sizes
type.compressed_size_in_bytes = None
type.uncompressed_size_in_bytes = None
for challenge in t.challenges:
for task in challenge.schedule:
if task.warmup_iterations > 1:
logger.info("Resetting warmup iterations to 1 for [%s]" %
str(task))
task.warmup_iterations = 1
if task.iterations > 1:
logger.info("Resetting measurement iterations to 1 for [%s]" %
str(task))
task.iterations = 1
if task.warmup_time_period is not None:
logger.info(
"Resetting warmup time period for [%s] to 1 second." %
str(task))
task.warmup_time_period = 1
return t
def post_process_for_test_mode(t):
logger.info("Preparing track [%s] for test mode." % str(t))
for index in t.indices:
for type in index.types:
if type.has_valid_document_data():
logger.info("Reducing corpus size to 1000 documents for [%s/%s]" % (index, type))
type.number_of_documents = 1000
path, ext = io.splitext(type.document_archive)
path_2, ext_2 = io.splitext(path)
type.document_archive = "%s-1k%s%s" % (path_2, ext_2, ext)
type.document_file = "%s-1k%s" % (path_2, ext_2)
# we don't want to check sizes
type.compressed_size_in_bytes = None
type.uncompressed_size_in_bytes = None
for challenge in t.challenges:
for task in challenge.schedule:
if task.warmup_iterations > 1:
logger.info("Resetting warmup iterations to 1 for [%s]" % str(task))
task.warmup_iterations = 1
if task.iterations > 1:
logger.info("Resetting measurement iterations to 1 for [%s]" % str(task))
task.iterations = 1
if task.warmup_time_period is not None:
logger.info("Resetting warmup time period for [%s] to 1 second." % str(task))
task.warmup_time_period = 1
return t
def _create_type(self, type_spec, mapping_dir):
docs = self._r(type_spec, "documents", mandatory=False)
if docs:
if io.is_archive(docs):
document_archive = docs
document_file = io.splitext(docs)[0]
else:
document_archive = None
document_file = docs
number_of_documents = self._r(type_spec, "document-count")
compressed_bytes = self._r(type_spec, "compressed-bytes", mandatory=False)
uncompressed_bytes = self._r(type_spec, "uncompressed-bytes", mandatory=False)
else:
document_archive = None
document_file = None
number_of_documents = 0
compressed_bytes = 0
uncompressed_bytes = 0
mapping_file = os.path.join(mapping_dir, self._r(type_spec, "mapping"))
with self.source(mapping_file, "rt") as f:
mapping = json.load(f)
return track.Type(name=self._r(type_spec, "name"),
mapping=mapping,
document_file=document_file,
document_archive=document_archive,
includes_action_and_meta_data=self._r(type_spec, "includes-action-and-meta-data", mandatory=False,
default_value=False),
number_of_documents=number_of_documents,
compressed_size_in_bytes=compressed_bytes,
uncompressed_size_in_bytes=uncompressed_bytes)
def _create_type(self, type_spec, mapping_dir, data_dir):
compressed_docs = self._r(type_spec, "documents", mandatory=False)
if compressed_docs:
document_archive = "%s/%s" % (data_dir, compressed_docs)
document_file = "%s/%s" % (data_dir,
io.splitext(compressed_docs)[0])
else:
document_archive = None
document_file = None
return track.Type(
name=self._r(type_spec, "name"),
mapping_file="%s/%s" %
(mapping_dir, self._r(type_spec, "mapping")),
document_file=document_file,
document_archive=document_archive,
number_of_documents=self._r(type_spec,
"document-count",
mandatory=False,
default_value=0),
compressed_size_in_bytes=self._r(type_spec,
"compressed-bytes",
mandatory=False),
uncompressed_size_in_bytes=self._r(type_spec,
"uncompressed-bytes",
mandatory=False))
def decompress(data_set_path, expected_size_in_bytes):
# we assume that track data are always compressed and try to decompress them before running the benchmark
basename, extension = io.splitext(data_set_path)
decompressed = False
if not os.path.isfile(basename) or os.path.getsize(
basename) != expected_size_in_bytes:
decompressed = True
if type.uncompressed_size_in_bytes:
console.info(
"Decompressing track data from [%s] to [%s] (resulting size: %.2f GB) ... "
% (data_set_path, basename,
convert.bytes_to_gb(type.uncompressed_size_in_bytes)),
end='',
flush=True,
logger=logger)
else:
console.info(
"Decompressing track data from [%s] to [%s] ... " %
(data_set_path, basename),
end='',
flush=True,
logger=logger)
io.decompress(data_set_path, io.dirname(data_set_path))
console.println("[OK]")
extracted_bytes = os.path.getsize(basename)
if expected_size_in_bytes is not None and extracted_bytes != expected_size_in_bytes:
raise exceptions.DataError(
"[%s] is corrupt. Extracted [%d] bytes but [%d] bytes are expected."
% (basename, extracted_bytes, expected_size_in_bytes))
return basename, decompressed
def _unzip(self, data_set_path):
# we assume that track data are always compressed and try to unzip them before running the benchmark
basename, extension = io.splitext(data_set_path)
if not os.path.isfile(basename):
logger.info("Unzipping track data from [%s] to [%s]." % (data_set_path, basename))
io.unzip(data_set_path, io.dirname(data_set_path))
return basename
def mapping_file_name(self, type):
distribution_version = self._config.opts("source", "distribution.version", mandatory=False)
if distribution_version and len(distribution_version.strip()) > 0:
path, extension = io.splitext(type.mapping_file_name)
return "%s-%s%s" % (path, distribution_version, extension)
else:
return type.mapping_file_name
def _unzip(self, data_set_path):
# we assume that track data are always compressed and try to unzip them before running the benchmark
basename, extension = io.splitext(data_set_path)
if not os.path.isfile(basename):
logger.info("Unzipping track data from [%s] to [%s]." % (data_set_path, basename))
io.unzip(data_set_path, io.dirname(data_set_path))
return basename
def mapping_file_name(self, type):
distribution_version = self._config.opts("source", "distribution.version", mandatory=False)
if distribution_version and len(distribution_version.strip()) > 0:
path, extension = io.splitext(type.mapping_file_name)
return "%s-%s%s" % (path, distribution_version, extension)
else:
return type.mapping_file_name
def _create_type(self, type_spec, mapping_dir):
compressed_docs = self._r(type_spec, "documents", mandatory=False)
if compressed_docs:
relative_data_dir = self.name.lower()
document_archive = os.path.join(relative_data_dir, compressed_docs)
document_file = os.path.join(relative_data_dir, io.splitext(compressed_docs)[0])
number_of_documents = self._r(type_spec, "document-count")
compressed_bytes = self._r(type_spec, "compressed-bytes", mandatory=False)
uncompressed_bytes = self._r(type_spec, "uncompressed-bytes", mandatory=False)
else:
document_archive = None
document_file = None
number_of_documents = 0
compressed_bytes = 0
uncompressed_bytes = 0
mapping_file = os.path.join(mapping_dir, self._r(type_spec, "mapping"))
with self.source(mapping_file, "rt") as f:
mapping = json.load(f)
return track.Type(name=self._r(type_spec, "name"),
mapping=mapping,
document_file=document_file,
document_archive=document_archive,
includes_action_and_meta_data=self._r(type_spec, "includes-action-and-meta-data", mandatory=False,
default_value=False),
number_of_documents=number_of_documents,
compressed_size_in_bytes=compressed_bytes,
uncompressed_size_in_bytes=uncompressed_bytes)
def post_process_for_test_mode(t):
logger.info("Preparing track [%s] for test mode." % str(t))
for index in t.indices:
for type in index.types:
if type.has_valid_document_data():
logger.info(
"Reducing corpus size to 1000 documents for [%s/%s]" %
(index, type))
type.number_of_documents = 1000
path, ext = io.splitext(type.document_archive)
path_2, ext_2 = io.splitext(path)
type.document_archive = "%s-1k%s%s" % (path_2, ext_2, ext)
type.document_file = "%s-1k%s" % (path_2, ext_2)
# we don't want to check sizes
type.compressed_size_in_bytes = None
type.uncompressed_size_in_bytes = None
for challenge in t.challenges:
for task in challenge.schedule:
# we need iterate over leaf tasks and await iterating over possible intermediate 'parallel' elements
for leaf_task in task:
# iteration-based schedules are divided among all clients and we should provide at least one iteration for each client.
if leaf_task.warmup_iterations > leaf_task.clients:
count = leaf_task.clients
logger.info("Resetting warmup iterations to %d for [%s]" %
(count, str(leaf_task)))
leaf_task.warmup_iterations = count
if leaf_task.iterations > leaf_task.clients:
count = leaf_task.clients
logger.info(
"Resetting measurement iterations to %d for [%s]" %
(count, str(leaf_task)))
leaf_task.iterations = count
if leaf_task.warmup_time_period is not None and leaf_task.warmup_time_period > 0:
leaf_task.warmup_time_period = 0
logger.info(
"Resetting warmup time period for [%s] to [%d] seconds."
% (str(leaf_task), leaf_task.warmup_time_period))
if leaf_task.time_period is not None and leaf_task.time_period > 10:
leaf_task.time_period = 10
logger.info(
"Resetting measurement time period for [%s] to [%d] seconds."
% (str(leaf_task), leaf_task.time_period))
return t
def decompress(data_set_path, expected_size_in_bytes):
# we assume that track data are always compressed and try to decompress them before running the benchmark
basename, extension = io.splitext(data_set_path)
if not os.path.isfile(basename) or os.path.getsize(basename) != expected_size_in_bytes:
logger.info("Unzipping track data from [%s] to [%s]." % (data_set_path, basename))
io.decompress(data_set_path, io.dirname(data_set_path))
extracted_bytes = os.path.getsize(basename)
if extracted_bytes != expected_size_in_bytes:
raise exceptions.DataError("[%s] is corrupt. Extracted [%d] bytes but [%d] bytes are expected." %
(basename, extracted_bytes, expected_size_in_bytes))
def decompress(data_set_path, expected_size_in_bytes):
# we assume that track data are always compressed and try to decompress them before running the benchmark
basename, extension = io.splitext(data_set_path)
if not os.path.isfile(basename) or os.path.getsize(basename) != expected_size_in_bytes:
logger.info("Unzipping track data from [%s] to [%s]." % (data_set_path, basename))
print("Decompressing %s (resulting size: %.2f GB) ... " %
(type.document_archive, convert.bytes_to_gb(type.uncompressed_size_in_bytes)), end='', flush=True)
io.decompress(data_set_path, io.dirname(data_set_path))
print("Done")
extracted_bytes = os.path.getsize(basename)
if extracted_bytes != expected_size_in_bytes:
raise exceptions.DataError("[%s] is corrupt. Extracted [%d] bytes but [%d] bytes are expected." %
(basename, extracted_bytes, expected_size_in_bytes))
def _configured_plugins(self, variables=None):
configured_plugins = []
# each directory is a plugin, each .ini is a config (just go one level deep)
for entry in os.listdir(self.plugins_root_path):
plugin_path = os.path.join(self.plugins_root_path, entry)
if os.path.isdir(plugin_path):
for child_entry in os.listdir(plugin_path):
if os.path.isfile(os.path.join(plugin_path, child_entry)) and io.has_extension(child_entry, ".ini"):
f, _ = io.splitext(child_entry)
plugin_name = self._file_to_plugin_name(entry)
config = io.basename(f)
configured_plugins.append(PluginDescriptor(name=plugin_name, config=config, variables=variables))
return configured_plugins
def _configured_plugins(self):
configured_plugins = []
# each directory is a plugin, each .ini is a config (just go one level deep)
for entry in os.listdir(self.plugins_root_path):
plugin_path = os.path.join(self.plugins_root_path, entry)
if os.path.isdir(plugin_path):
for child_entry in os.listdir(plugin_path):
if os.path.isfile(os.path.join(plugin_path, child_entry)) and io.has_extension(child_entry, ".ini"):
f, _ = io.splitext(child_entry)
plugin_name = self._file_to_plugin_name(entry)
config = io.basename(f)
configured_plugins.append(PluginDescriptor(name=plugin_name, config=config))
return configured_plugins
def post_process_for_test_mode(t):
logger.info("Preparing track [%s] for test mode." % str(t))
for index in t.indices:
for type in index.types:
if type.has_valid_document_data():
logger.info("Reducing corpus size to 1000 documents for [%s/%s]" % (index, type))
type.number_of_documents = 1000
path, ext = io.splitext(type.document_archive)
path_2, ext_2 = io.splitext(path)
type.document_archive = "%s-1k%s%s" % (path_2, ext_2, ext)
type.document_file = "%s-1k%s" % (path_2, ext_2)
# we don't want to check sizes
type.compressed_size_in_bytes = None
type.uncompressed_size_in_bytes = None
for challenge in t.challenges:
for task in challenge.schedule:
# we need iterate over leaf tasks and await iterating over possible intermediate 'parallel' elements
for leaf_task in task:
# iteration-based schedules are divided among all clients and we should provide at least one iteration for each client.
if leaf_task.warmup_iterations > leaf_task.clients:
count = leaf_task.clients
logger.info("Resetting warmup iterations to %d for [%s]" % (count, str(leaf_task)))
leaf_task.warmup_iterations = count
if leaf_task.iterations > leaf_task.clients:
count = leaf_task.clients
logger.info("Resetting measurement iterations to %d for [%s]" % (count, str(leaf_task)))
leaf_task.iterations = count
if leaf_task.warmup_time_period is not None and leaf_task.warmup_time_period > 0:
leaf_task.warmup_time_period = 0
logger.info("Resetting warmup time period for [%s] to [%d] seconds." % (str(leaf_task), leaf_task.warmup_time_period))
if leaf_task.time_period is not None and leaf_task.time_period > 10:
leaf_task.time_period = 10
logger.info("Resetting measurement time period for [%s] to [%d] seconds." % (str(leaf_task), leaf_task.time_period))
return t
def _create_type(self, type_spec, mapping_dir, data_dir):
compressed_docs = self._r(type_spec, "documents", mandatory=False)
if compressed_docs:
document_archive = "%s/%s" % (data_dir, compressed_docs)
document_file = "%s/%s" % (data_dir, io.splitext(compressed_docs)[0])
else:
document_archive = None
document_file = None
return track.Type(name=self._r(type_spec, "name"),
mapping_file="%s/%s" % (mapping_dir, self._r(type_spec, "mapping")),
document_file=document_file,
document_archive=document_archive,
number_of_documents=self._r(type_spec, "document-count", mandatory=False, default_value=0),
compressed_size_in_bytes=self._r(type_spec, "compressed-bytes", mandatory=False),
uncompressed_size_in_bytes=self._r(type_spec, "uncompressed-bytes", mandatory=False)
)
def __init__(self, track_path):
if not os.path.exists(track_path):
raise exceptions.SystemSetupError("Track path %s does not exist" % track_path)
if os.path.isdir(track_path):
self.track_name = io.basename(track_path)
self._track_dir = track_path
self._track_file = os.path.join(track_path, "track.json")
if not os.path.exists(self._track_file):
raise exceptions.SystemSetupError("Could not find track.json in %s" % track_path)
elif os.path.isfile(track_path):
if io.has_extension(track_path, ".json"):
self._track_dir = io.dirname(track_path)
self._track_file = track_path
self.track_name = io.splitext(io.basename(track_path))[0]
else:
raise exceptions.SystemSetupError("%s has to be a JSON file" % track_path)
else:
raise exceptions.SystemSetupError("%s is neither a file nor a directory" % track_path)
def decompress(data_set_path, expected_size_in_bytes):
# we assume that track data are always compressed and try to decompress them before running the benchmark
basename, extension = io.splitext(data_set_path)
decompressed = False
if not os.path.isfile(basename) or os.path.getsize(basename) != expected_size_in_bytes:
decompressed = True
if type.uncompressed_size_in_bytes:
console.info("Decompressing track data from [%s] to [%s] (resulting size: %.2f GB) ... " %
(data_set_path, basename, convert.bytes_to_gb(type.uncompressed_size_in_bytes)),
end='', flush=True, logger=logger)
else:
console.info("Decompressing track data from [%s] to [%s] ... " % (data_set_path, basename), end='',
flush=True, logger=logger)
io.decompress(data_set_path, io.dirname(data_set_path))
console.println("[OK]")
extracted_bytes = os.path.getsize(basename)
if expected_size_in_bytes is not None and extracted_bytes != expected_size_in_bytes:
raise exceptions.DataError("[%s] is corrupt. Extracted [%d] bytes but [%d] bytes are expected." %
(basename, extracted_bytes, expected_size_in_bytes))
return basename, decompressed
def plain_text(file):
_, ext = io.splitext(file)
return ext in [
".ini", ".txt", ".json", ".yml", ".yaml", ".options", ".properties"
]
def __is_car(path):
_, extension = io.splitext(path)
return extension == ".ini"
def __car_name(path):
p, _ = io.splitext(path)
return io.basename(p)
def __car_name(path):
p, _ = io.splitext(path)
return io.basename(p)
def __is_car(path):
_, extension = io.splitext(path)
return extension == ".ini"
def plain_text(file):
_, ext = io.splitext(file)
return ext in [".ini", ".txt", ".json", ".yml", ".yaml", ".options", ".properties"]