def testDeduplicateAndPut_Different(self):
d = {
'buildNumber': 0,
'buildbotMasterName': '',
'buildbotName': '',
'displayBotName': 'bot',
'displayMasterName': 'master',
'guid': 'e9c2891d-2b04-413f-8cf4-099827e67626',
'logUri': '',
'type': 'BuildbotInfo'
}
test_key = utils.TestKey('Chromium/win7/foo')
entity = histogram.SparseDiagnostic(data=d,
test=test_key,
start_revision=1,
end_revision=sys.maxint,
id='abc')
entity.put()
d2 = d.copy()
d2['guid'] = 'def'
d2['displayBotName'] = 'mac'
entity2 = histogram.SparseDiagnostic(data=d2,
test=test_key,
start_revision=1,
end_revision=sys.maxint,
id='def')
add_histograms.DeduplicateAndPut([entity2], test_key, 2)
sparse = histogram.SparseDiagnostic.query().fetch()
self.assertEqual(2, len(sparse))
def testDeduplicateAndPut_New(self):
d = {
'guid': 'abc',
'osName': 'linux',
'type': 'DeviceInfo'
}
test_key = utils.TestKey('Chromium/win7/foo')
entity = histogram.SparseDiagnostic(
data=json.dumps(d), test=test_key, start_revision=1,
end_revision=sys.maxint, id='abc')
entity.put()
add_histograms.DeduplicateAndPut([entity], test_key, 1)
sparse = histogram.SparseDiagnostic.query().fetch()
self.assertEqual(1, len(sparse))
def testDeduplicateAndPut_New(self):
d = {
'values': ['master'],
'guid': 'e9c2891d-2b04-413f-8cf4-099827e67626',
'type': 'GenericSet'
}
test_key = utils.TestKey('Chromium/win7/foo')
entity = histogram.SparseDiagnostic(
data=d, test=test_key, start_revision=1,
end_revision=sys.maxint, id='abc')
entity.put()
add_histograms.DeduplicateAndPut([entity], test_key, 1)
sparse = histogram.SparseDiagnostic.query().fetch()
self.assertEqual(1, len(sparse))
def testDeduplicateAndPut_Same(self):
d = {
'guid': 'abc',
'osName': 'linux',
'type': 'DeviceInfo'
}
test_key = utils.TestKey('Chromium/win7/foo')
entity = histogram.SparseDiagnostic(
data=d, test=test_key, start_revision=1,
end_revision=sys.maxint, id='abc')
entity.put()
d2 = d.copy()
d2['guid'] = 'def'
entity2 = histogram.SparseDiagnostic(
data=d2, test=test_key,
start_revision=2, end_revision=sys.maxint, id='def')
add_histograms.DeduplicateAndPut([entity2], test_key, 2)
sparse = histogram.SparseDiagnostic.query().fetch()
self.assertEqual(1, len(sparse))
def testDeduplicateAndPut_Different(self):
d = {
'values': ['master'],
'guid': 'e9c2891d-2b04-413f-8cf4-099827e67626',
'type': 'GenericSet'
}
test_key = utils.TestKey('Chromium/win7/foo')
entity = histogram.SparseDiagnostic(
data=d, name='masters', test=test_key, start_revision=1,
end_revision=sys.maxint, id='abc')
entity.put()
d2 = d.copy()
d2['guid'] = 'def'
d2['displayBotName'] = 'mac'
entity2 = histogram.SparseDiagnostic(
data=d2, test=test_key,
start_revision=1, end_revision=sys.maxint, id='def')
add_histograms.DeduplicateAndPut([entity2], test_key, 2)
sparse = histogram.SparseDiagnostic.query().fetch()
self.assertEqual(2, len(sparse))
def ProcessDiagnostics(diagnostics, revision, test_key, internal_only):
if not diagnostics:
return {}
diagnostic_data = json.loads(diagnostics)
diagnostic_entities = []
for name, diagnostic_datum in diagnostic_data.iteritems():
# TODO(eakuefner): Pass map of guid to dict to avoid overhead
guid = diagnostic_datum['guid']
diagnostic_entities.append(
histogram.SparseDiagnostic(id=guid,
name=name,
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()
return new_guids_to_existing_diagnostics
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)
