diff options
| -rw-r--r-- | nova/weights.py | 40 |
1 files changed, 36 insertions, 4 deletions
diff --git a/nova/weights.py b/nova/weights.py index a093df0345..b88caaa186 100644 --- a/nova/weights.py +++ b/nova/weights.py @@ -19,9 +19,14 @@ Pluggable Weighing support import abc +from oslo_log import log as logging + from nova import loadables +LOG = logging.getLogger(__name__) + + def normalize(weight_list, minval=None, maxval=None): """Normalize the values in a list between 0 and 1.0. @@ -127,13 +132,40 @@ class BaseWeightHandler(loadables.BaseLoader): for weigher in weighers: weights = weigher.weigh_objects(weighed_objs, weighing_properties) + LOG.debug( + "%s: raw weights %s", + weigher.__class__.__name__, + {(obj.obj.host, obj.obj.nodename): weight + for obj, weight in zip(weighed_objs, weights)} + ) + # Normalize the weights - weights = normalize(weights, - minval=weigher.minval, - maxval=weigher.maxval) + weights = list( + normalize( + weights, minval=weigher.minval, maxval=weigher.maxval)) + + LOG.debug( + "%s: normalized weights %s", + weigher.__class__.__name__, + {(obj.obj.host, obj.obj.nodename): weight + for obj, weight in zip(weighed_objs, weights)} + ) + + log_data = {} for i, weight in enumerate(weights): obj = weighed_objs[i] - obj.weight += weigher.weight_multiplier(obj.obj) * weight + multiplier = weigher.weight_multiplier(obj.obj) + weigher_score = multiplier * weight + obj.weight += weigher_score + + log_data[(obj.obj.host, obj.obj.nodename)] = ( + f"{multiplier} * {weight}") + + LOG.debug( + "%s: score (multiplier * weight) %s", + weigher.__class__.__name__, + {name: log for name, log in log_data.items()} + ) return sorted(weighed_objs, key=lambda x: x.weight, reverse=True) |