performance: use a distinct query for statistics X axis (#69606)

src/authentic2/apps/journal/models.py

@@ -30,7 +30,7 @@ from django.contrib.postgres.fields import ArrayField
 from django.contrib.postgres.fields.jsonb import KeyTextTransform
 from django.core.exceptions import ObjectDoesNotExist
 from django.db import models
-from django.db.models import Count, F, Q, QuerySet, Value
+from django.db.models import Count, F, Max, Min, Q, QuerySet, Value
 from django.db.models.functions import Trunc
 from django.utils.timezone import now, utc
 from django.utils.translation import gettext_lazy as _
@@ -142,6 +142,7 @@ class EventTypeDefinition(metaclass=EventTypeDefinitionMeta):
             qs = qs.filter(timestamp__gte=start)
         if end:
             qs = qs.filter(timestamp__lte=end)
+        x_interval_qs = qs
 
         values = [group_by_time]
         if group_by_time != 'timestamp':
@@ -162,7 +163,12 @@ class EventTypeDefinition(metaclass=EventTypeDefinitionMeta):
 
         qs = qs.values(*values)
         qs = qs.annotate(count=Count('id'))
-        return qs.order_by(group_by_time)
+        x_interval = x_interval_qs.aggregate(
+            min=Trunc(Min("timestamp"), kind=group_by_time, output_field=models.DateField()),
+            max=Trunc(Max("timestamp"), kind=group_by_time, output_field=models.DateField()),
+        )
+
+        return (qs.order_by(group_by_time), x_interval)
 
     @classmethod
     def get_global_statistics(cls, group_by_time, y_label, start=None, end=None):
@@ -447,6 +453,9 @@ class Event(models.Model):
         verbose_name = _('event')
         verbose_name_plural = _('events')
         ordering = ('timestamp', 'id')
+        index_together = [
+            ("type", "timestamp"),
+        ]
 
 
 class EventCursor(str):

src/authentic2/apps/journal/utils.py

@@ -48,9 +48,9 @@ class Statistics:
     }
     default_y_label = _('None')
 
-    def __init__(self, qs, time_interval):
+    def __init__(self, qs, time_interval, x_interval = None):
         self.time_interval = time_interval
-        self.x_labels = self.build_x_labels(qs)
+        self.x_labels = self.build_x_labels(qs, x_interval)
         self._x_labels_indexes = {label: i for i, label in enumerate(self.x_labels)}
         self.series = {}
         self.y_labels = []
@@ -58,15 +58,18 @@ class Statistics:
     def set_y_labels(self, y_labels):
         self.y_labels[:] = y_labels
 
-    def build_x_labels(self, qs):
+    def build_x_labels(self, qs, x_interval = None):
         if self.time_interval == 'timestamp':
             return list(qs.distinct().values_list(self.time_interval, flat=True))
 
-        aggregate = qs.aggregate(min=Min(self.time_interval), max=Max(self.time_interval))
-        if not aggregate['min']:
-            return []
+        if x_interval is not None:
+            aggregate = x_interval
+        else:
+            aggregate = qs.aggregate(min=Min(self.time_interval), max=Max(self.time_interval))
+            if not aggregate['min']:
+                return []
 
-        min_date, max_date = aggregate['min'].date(), aggregate['max'].date()
+        min_date, max_date = aggregate['min'], aggregate['max']
         if self.time_interval == 'day':
             return [min_date + timedelta(days=i) for i in range((max_date - min_date).days + 1)]
         if self.time_interval == 'year':

src/authentic2/journal_event_types.py

@@ -68,7 +68,7 @@ class EventTypeWithHow(EventTypeWithService):
         elif service:
             which_references = service
 
-        qs = cls.get_statistics(
+        qs, x_interval = cls.get_statistics(
             group_by_time=group_by_time,
             group_by_field='how',
             which_references=which_references,
@@ -76,7 +76,7 @@ class EventTypeWithHow(EventTypeWithService):
             start=start,
             end=end,
         )
-        stats = Statistics(qs, time_interval=group_by_time)
+        stats = Statistics(qs, time_interval=group_by_time, x_interval=x_interval)
 
         for stat in qs:
             stats.add(x_label=stat[group_by_time], y_label=stat['how'], value=stat['count'])