65 lines
2.8 KiB
Python
65 lines
2.8 KiB
Python
import datetime
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from django.contrib.contenttypes.models import ContentType
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from django.db.models.loading import get_model
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from django.utils import timezone
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from orchestra.models.utils import get_model_field_path
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from .backends import ServiceMonitor
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def compute_resource_usage(data):
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""" Computes MonitorData.used based on related monitors """
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from .models import MonitorData
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resource = data.resource
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today = timezone.now()
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result = 0
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has_result = False
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for monitor in resource.monitors:
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# Get related dataset
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resource_model = data.content_type.model_class()
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monitor_model = get_model(ServiceMonitor.get_backend(monitor).model)
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if resource_model == monitor_model:
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dataset = MonitorData.objects.filter(monitor=monitor,
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content_type=data.content_type_id, object_id=data.object_id)
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else:
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path = get_model_field_path(monitor_model, resource_model)
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fields = '__'.join(path)
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objects = monitor_model.objects.filter(**{fields: data.object_id})
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pks = objects.values_list('id', flat=True)
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ct = ContentType.objects.get_for_model(monitor_model)
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dataset = MonitorData.objects.filter(monitor=monitor, content_type=ct, object_id__in=pks)
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# Process dataset according to resource.period
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if resource.period == resource.MONTHLY_AVG:
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try:
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last = dataset.latest()
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except MonitorData.DoesNotExist:
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continue
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has_result = True
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epoch = datetime(year=today.year, month=today.month, day=1, tzinfo=timezone.utc)
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total = (last.created_at-epoch).total_seconds()
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dataset = dataset.filter(created_at__year=today.year, created_at__month=today.month)
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ini = epoch
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for data in dataset:
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slot = (data.created_at-ini).total_seconds()
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result += data.value * slot/total
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ini = data.created_at
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elif resource.period == resource.MONTHLY_SUM:
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dataset = dataset.filter(created_at__year=today.year, created_at__month=today.month)
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# FIXME Aggregation of 0s returns None! django bug?
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# value = dataset.aggregate(models.Sum('value'))['value__sum']
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values = dataset.values_list('value', flat=True)
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if values:
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has_result = True
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result += sum(values)
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elif resource.period == resource.LAST:
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try:
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result += dataset.latest().value
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except MonitorData.DoesNotExist:
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continue
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has_result = True
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else:
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raise NotImplementedError("%s support not implemented" % data.period)
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return float(result)/resource.get_scale() if has_result else None
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