def get_metric_list(self, request, metrics, begin, end, job, max_points,
num_points, **kwargs):
errors = {}
reduce_fn, group_by = map(request.GET.get, ('reduce_fn', 'group_by'))
if not reduce_fn and group_by:
errors[
'reduce_fn'] = "This field is mandatory if 'group_by' is specified"
if errors:
return self.create_response(request,
errors,
response_class=HttpBadRequest)
try:
base_bundle = self.build_bundle(request=request)
objs = self.obj_get_list(bundle=base_bundle,
**self.remove_api_resource_names(kwargs))
except Http404 as exc:
raise custom_response(self, request, http.HttpNotFound,
{'metrics': exc})
metrics = metrics or set(
itertools.chain.from_iterable(
MetricStore(obj).names for obj in objs))
result = dict((obj.id,
self._fetch(MetricStore(obj), metrics, begin, end, job,
max_points, num_points)) for obj in objs)
if not reduce_fn:
for obj_id, stats in result.items():
result[obj_id] = self._format(stats)
return self.create_response(request, result)
if not group_by:
stats = self._reduce(metrics, result, reduce_fn)
return self.create_response(request, self._format(stats))
# Want to reduce into groups, one series per group
groups = defaultdict(dict)
for obj in objs:
if hasattr(obj, 'content_type'):
obj = obj.downcast()
if hasattr(obj, group_by):
group_val = getattr(obj, group_by)
groups[getattr(group_val, 'id',
group_val)][obj.id] = result[obj.id]
for key in groups:
stats = self._reduce(metrics, groups[key], reduce_fn)
groups[key] = self._format(stats)
return self.create_response(request, groups)
def get_metric_detail(self, request, metrics, begin, end, job, max_points,
num_points, **kwargs):
obj = self.cached_obj_get(request=request,
**self.remove_api_resource_names(kwargs))
metrics = metrics or MetricStore(obj).names
if isinstance(obj, StorageResourceRecord):
# FIXME: there is a level of indirection here to go from a StorageResourceRecord to individual time series.
# Although no longer necessary, time series are still stored in separate resources.
stats = defaultdict(dict)
for stat in StorageResourceStatistic.objects.filter(
storage_resource=obj, name__in=metrics):
for dt, data in self._fetch(stat.metrics, metrics, begin, end,
job, max_points,
num_points).items():
stats[dt].update(data)
else:
stats = self._fetch(MetricStore(obj), metrics, begin, end, job,
max_points, num_points)
if not job:
for data in stats.values():
data.update(dict.fromkeys(set(metrics).difference(data), 0.0))
return self.create_response(request, self._format(stats))
def metrics(self):
from chroma_core.lib.metrics import MetricStore
if not hasattr(self, '_metrics'):
self._metrics = MetricStore.new(self)
return self._metrics