def _AddHistogramFromData(params, revision, test_key, internal_only):
data_dict = params['data']
diagnostics = params.get('diagnostics')
new_guids_to_existing_diagnostics = yield ProcessDiagnostics(
diagnostics, revision, test_key, internal_only)
hs = histogram_set.HistogramSet()
hs.ImportDicts([data_dict])
for new_guid, existing_diagnostic in (iter(
new_guids_to_existing_diagnostics.items())):
hs.ReplaceSharedDiagnostic(
new_guid,
diagnostic_ref.DiagnosticRef(existing_diagnostic['guid']))
data = hs.GetFirstHistogram().AsDict()
entity = histogram.Histogram(id=str(uuid.uuid4()),
data=data,
test=test_key,
revision=revision,
internal_only=internal_only)
yield entity.put_async()
measurement = upload_completion_token.Measurement.GetById(
params.get('test_path'), params.get('token'))
if measurement is not None:
measurement.histogram = entity.key
measurement.put_async()
def _AddMockData(self):
"""Adds sample TestMetadata, Row, and Anomaly entities."""
testing_common.AddTests(*_MOCK_DATA)
# Add 50 Row entities to one of the tests.
# Also add 2 Anomaly entities.
test_path = 'ChromiumPerf/mac/SunSpider/Total/t'
test_key = utils.TestKey(test_path)
test_container_key = utils.GetTestContainerKey(test_key)
for rev in range(15000, 15100, 2):
graph_data.Row(id=rev, parent=test_container_key,
value=(rev * 2)).put()
if rev % 50 == 0:
data = generic_set.GenericSet(['foo_%s' % rev])
data = data.AsDict()
anomaly.Anomaly(start_revision=(rev - 2),
end_revision=rev,
median_before_anomaly=100,
median_after_anomaly=50,
test=test_key).put()
histogram.SparseDiagnostic(test=test_key,
start_revision=rev - 50,
end_revision=rev - 1,
data=data).put()
histogram.Histogram(test=test_key).put()
def post(self):
"""Adds a single histogram or sparse shared diagnostic to the datastore.
The |data| request parameter can be either a histogram or a sparse shared
diagnostic; the set of diagnostics that are considered sparse (meaning that
they don't normally change on every upload for a given benchmark from a
given bot) is shown in add_histograms.SPARSE_DIAGNOSTIC_TYPES.
See https://goo.gl/lHzea6 for detailed information on the JSON format for
histograms and diagnostics.
Request parameters:
data: JSON encoding of a histogram or shared diagnostic.
revision: a revision, given as an int.
test_path: the test path to which this diagnostic or histogram should be
attached.
"""
datastore_hooks.SetPrivilegedRequest()
data = self.request.get('data')
data_dict = json.loads(data)
revision = int(self.request.get('revision'))
test_key = utils.TestKey(self.request.get('test_path'))
if data_dict.get('type') in add_histograms.SPARSE_DIAGNOSTIC_TYPES:
entity = histogram.SparseDiagnostic(data=data,
test=test_key,
start_revision=revision,
end_revision=revision)
else:
entity = histogram.Histogram(data=data,
test=test_key,
revision=revision)
entity.put()
def GetTestHistogram(self,
owners_diagnostic=None,
commit_position_diagnostic=None):
if not commit_position_diagnostic:
commit_position_diagnostic = generic_set.GenericSet([123])
if not owners_diagnostic:
owners_diagnostic = generic_set.GenericSet(['owner_name'])
return histogram.Histogram(
id=str(uuid.uuid4()),
data={
'allBins': {
'1': [1],
'3': [1],
'4': [1]
},
'binBoundaries': [1, [1, 1000, 20]],
'diagnostics': {
reserved_infos.CHROMIUM_COMMIT_POSITIONS.name:
commit_position_diagnostic.AsDict(),
reserved_infos.OWNERS.name:
owners_diagnostic.guid,
'irrelevant_diagnostic':
generic_set.GenericSet([42]).AsDict(),
},
'name': 'foo',
'running': [3, 3, 0.5972531564093516, 2, 1, 6, 2],
'sampleValues': [1, 2, 3],
'unit': 'count_biggerIsBetter'
},
test=None,
revision=123,
internal_only=True)
def _MockData(self, path='master/bot/suite/measure/case',
internal_only=False):
test = graph_data.TestMetadata(
has_rows=True,
id=path,
improvement_direction=anomaly.DOWN,
internal_only=internal_only,
units='units')
test.UpdateSheriff()
test.put()
for i in range(1, 21, 2):
graph_data.Row(
error=(i / 2.0),
id=i,
parent=test.key,
r_i2=(i * 2),
timestamp=datetime.datetime.utcfromtimestamp(i),
value=float(i)).put()
histogram.Histogram(
data=_TEST_HISTOGRAM_DATA,
id=str(uuid.uuid4()),
internal_only=internal_only,
revision=i,
test=test.key).put()
anomaly.Anomaly(
end_revision=11,
internal_only=internal_only,
is_improvement=False,
median_after_anomaly=6,
median_before_anomaly=4,
subscriptions=[Subscription(
name='Taylor',
notification_email=testing_common.INTERNAL_USER.email(),
)],
subscription_names=['Taylor'],
start_revision=10,
test=test.key).put()
histogram.SparseDiagnostic(
data={'type': 'GenericSet', 'guid': str(uuid.uuid4()), 'values': [1]},
end_revision=11,
id=str(uuid.uuid4()),
internal_only=internal_only,
name=reserved_infos.DEVICE_IDS.name,
start_revision=1,
test=test.key).put()
histogram.SparseDiagnostic(
data={'type': 'GenericSet', 'guid': str(uuid.uuid4()), 'values': [2]},
end_revision=None,
id=str(uuid.uuid4()),
internal_only=internal_only,
name=reserved_infos.DEVICE_IDS.name,
start_revision=11,
test=test.key).put()
def _AddMockData(self):
"""Adds sample TestMetadata and Row entities."""
testing_common.AddTests(*_MOCK_DATA)
# Add 50 Row entities to some of the tests.
for test_path in _TESTS_WITH_ROWS:
testing_common.AddRows(test_path, range(15000, 15100, 2))
histogram.SparseDiagnostic(test=utils.TestKey(test_path)).put()
histogram.Histogram(test=utils.TestKey(test_path)).put()
def post(self):
"""Adds a single histogram or sparse shared diagnostic to the datastore.
The |data| request parameter can be either a histogram or a sparse shared
diagnostic; the set of diagnostics that are considered sparse (meaning that
they don't normally change on every upload for a given benchmark from a
given bot) is shown in add_histograms.SPARSE_DIAGNOSTIC_TYPES.
See https://goo.gl/lHzea6 for detailed information on the JSON format for
histograms and diagnostics.
Request parameters:
data: JSON encoding of a histogram or shared diagnostic.
revision: a revision, given as an int.
test_path: the test path to which this diagnostic or histogram should be
attached.
"""
datastore_hooks.SetPrivilegedRequest()
data = self.request.get('data')
revision = int(self.request.get('revision'))
test_path = self.request.get('test_path')
data_dict = json.loads(data)
guid = data_dict['guid']
is_diagnostic = 'type' in data_dict
test_path_parts = test_path.split('/')
master = test_path_parts[0]
bot = test_path_parts[1]
test_name = '/'.join(test_path_parts[2:])
bot_whitelist = stored_object.Get(add_point_queue.BOT_WHITELIST_KEY)
internal_only = add_point_queue.BotInternalOnly(bot, bot_whitelist)
extra_args = {} if is_diagnostic else GetUnitArgs(data_dict['unit'])
# TDOO(eakuefner): Populate benchmark_description once it appears in
# diagnostics.
test_key = add_point_queue.GetOrCreateAncestors(
master, bot, test_name, internal_only, **extra_args).key
if is_diagnostic:
entity = histogram.SparseDiagnostic(id=guid,
data=data,
test=test_key,
start_revision=revision,
end_revision=revision,
internal_only=internal_only)
else:
entity = histogram.Histogram(id=guid,
data=data,
test=test_key,
revision=revision,
internal_only=internal_only)
AddRow(data_dict, test_key, revision, test_path, internal_only)
entity.put()
def _AddHistogramFromData(params, revision, test_key, internal_only):
data_dict = params['data']
diagnostics = params.get('diagnostics')
new_guids_to_existing_diagnostics = yield ProcessDiagnostics(
diagnostics, revision, test_key, internal_only)
hs = histogram_set.HistogramSet()
hs.ImportDicts([data_dict])
for new_guid, existing_diagnostic in (
iter(new_guids_to_existing_diagnostics.items())):
hs.ReplaceSharedDiagnostic(
new_guid, diagnostic_ref.DiagnosticRef(
existing_diagnostic['guid']))
data = hs.GetFirstHistogram().AsDict()
entity = histogram.Histogram(
id=str(uuid.uuid4()), data=data, test=test_key, revision=revision,
internal_only=internal_only)
yield entity.put_async()
def _AddHistogramFromData(params, revision, test_key, internal_only):
data_dict = params['data']
guid = data_dict['guid']
diagnostics = params.get('diagnostics')
new_guids_to_existing_diagnostics = yield ProcessDiagnostics(
diagnostics, revision, test_key, internal_only)
# TODO(eakuefner): Move per-histogram monkeypatching logic to Histogram.
hs = histogram_set.HistogramSet()
hs.ImportDicts([data_dict])
# TODO(eakuefner): Share code for replacement logic with add_histograms
for new_guid, existing_diagnostic in (
new_guids_to_existing_diagnostics.iteritems()):
hs.ReplaceSharedDiagnostic(
new_guid, diagnostic_ref.DiagnosticRef(
existing_diagnostic['guid']))
data = hs.GetFirstHistogram().AsDict()
entity = histogram.Histogram(
id=guid, data=data, test=test_key, revision=revision,
internal_only=internal_only)
yield entity.put_async()
def testGet_SuccessWithMeasurementsAndAssociatedHistogram(self):
owners_diagnostic = generic_set.GenericSet(['owner_name'])
commit_position_diagnostic = generic_set.GenericSet([123])
irrelevant_diagnostic = generic_set.GenericSet([42])
owners_diagnostic.guid = str(uuid.uuid4())
commit_position_diagnostic.guid = str(uuid.uuid4())
histogram.SparseDiagnostic(id=owners_diagnostic.guid,
data=owners_diagnostic.AsDict(),
name=reserved_infos.OWNERS.name,
test=None,
start_revision=1,
end_revision=999).put().get()
hs = histogram.Histogram(
id=str(uuid.uuid4()),
data={
'allBins': {
'1': [1],
'3': [1],
'4': [1]
},
'binBoundaries': [1, [1, 1000, 20]],
'diagnostics': {
reserved_infos.CHROMIUM_COMMIT_POSITIONS.name:
commit_position_diagnostic.AsDict(),
reserved_infos.OWNERS.name:
owners_diagnostic.guid,
'irrelevant_diagnostic':
irrelevant_diagnostic.AsDict(),
},
'name': 'foo',
'running': [3, 3, 0.5972531564093516, 2, 1, 6, 2],
'sampleValues': [1, 2, 3],
'unit': 'count_biggerIsBetter'
},
test=None,
revision=123,
internal_only=True).put().get()
token_id = str(uuid.uuid4())
test_path = 'Chromium/win7/suite/metric1'
token = upload_completion_token.Token(id=token_id).put().get()
measurement = token.AddMeasurement(test_path, True).get_result()
measurement.histogram = hs.key
measurement.put()
expected = {
'token':
token_id,
'file':
None,
'created':
str(token.creation_time),
'lastUpdated':
str(token.update_time),
'state':
'PROCESSING',
'measurements': [
{
'name':
test_path,
'state':
'PROCESSING',
'monitored':
True,
'lastUpdated':
str(measurement.update_time),
'dimensions': [
{
'name': reserved_infos.OWNERS.name,
'value': list(owners_diagnostic),
},
{
'name':
reserved_infos.CHROMIUM_COMMIT_POSITIONS.name,
'value': list(commit_position_diagnostic),
},
]
},
]
}
response = self.GetFullInfoRequest(token_id)
expected['measurements'][0]['dimensions'].sort()
response['measurements'][0]['dimensions'].sort()
self.assertEqual(response, expected)
def _AddMockData(self, histogram_data, internal_only=False):
histogram.Histogram(id=histogram_data['guid'],
test=ndb.Key('TestMetadata', 'M/B/S'),
revision=10,
data=histogram_data,
internal_only=internal_only).put()
def post(self):
"""Adds a single histogram or sparse shared diagnostic to the datastore.
The |data| request parameter can be either a histogram or a sparse shared
diagnostic; the set of diagnostics that are considered sparse (meaning that
they don't normally change on every upload for a given benchmark from a
given bot) is shown in add_histograms.SPARSE_DIAGNOSTIC_TYPES.
See https://goo.gl/lHzea6 for detailed information on the JSON format for
histograms and diagnostics.
Request parameters:
data: JSON encoding of a histogram or shared diagnostic.
revision: a revision, given as an int.
test_path: the test path to which this diagnostic or histogram should be
attached.
"""
datastore_hooks.SetPrivilegedRequest()
data = self.request.get('data')
revision = int(self.request.get('revision'))
test_path = self.request.get('test_path')
data_dict = json.loads(data)
guid = data_dict['guid']
is_diagnostic = 'type' in data_dict
test_path_parts = test_path.split('/')
master = test_path_parts[0]
bot = test_path_parts[1]
test_name = '/'.join(test_path_parts[2:])
bot_whitelist = stored_object.Get(add_point_queue.BOT_WHITELIST_KEY)
internal_only = add_point_queue.BotInternalOnly(bot, bot_whitelist)
extra_args = {} if is_diagnostic else GetUnitArgs(data_dict['unit'])
# TDOO(eakuefner): Populate benchmark_description once it appears in
# diagnostics.
parent_test = add_point_queue.GetOrCreateAncestors(
master, bot, test_name, internal_only, **extra_args)
test_key = parent_test.key
added_rows = []
monitored_test_keys = []
if is_diagnostic:
entity = histogram.SparseDiagnostic(id=guid,
data=data,
test=test_key,
start_revision=revision,
end_revision=revision,
internal_only=internal_only)
else:
diagnostics = self.request.get('diagnostics')
if diagnostics:
diagnostic_data = json.loads(diagnostics)
diagnostic_entities = []
for diagnostic_datum in diagnostic_data:
# TODO(eakuefner): Pass map of guid to dict to avoid overhead
guid = diagnostic_datum['guid']
diagnostic_entities.append(
histogram.SparseDiagnostic(
id=guid,
data=diagnostic_datum,
test=test_key,
start_revision=revision,
end_revision=sys.maxint,
internal_only=internal_only))
new_guids_to_existing_diagnostics = add_histograms.DeduplicateAndPut(
diagnostic_entities, test_key, revision).iteritems()
# TODO(eakuefner): Move per-histogram monkeypatching logic to Histogram.
hs = histogram_set.HistogramSet()
hs.ImportDicts([data_dict])
# TODO(eakuefner): Share code for replacement logic with add_histograms
for new_guid, existing_diagnostic in new_guids_to_existing_diagnostics:
hs.ReplaceSharedDiagnostic(
new_guid,
diagnostic_ref.DiagnosticRef(
existing_diagnostic['guid']))
data = hs.GetFirstHistogram().AsDict()
entity = histogram.Histogram(id=guid,
data=data,
test=test_key,
revision=revision,
internal_only=internal_only)
row = AddRow(data_dict, test_key, revision, test_path,
internal_only)
added_rows.append(row)
is_monitored = parent_test.sheriff and parent_test.has_rows
if is_monitored:
monitored_test_keys.append(parent_test.key)
entity.put()
tests_keys = [
k for k in monitored_test_keys if not add_point_queue.IsRefBuild(k)
]
# Updating of the cached graph revisions should happen after put because
# it requires the new row to have a timestamp, which happens upon put.
futures = [
graph_revisions.AddRowsToCacheAsync(added_rows),
find_anomalies.ProcessTestsAsync(tests_keys)
]
ndb.Future.wait_all(futures)
