@@ -1522,12 +1522,23 @@ class StatsView(TemplateView):
context['class_count_distinct'] = BBClass.objects.values('name').distinct().count()
context['machine_count_distinct'] = Machine.objects.values('name').distinct().count()
context['distro_count_distinct'] = Distro.objects.values('name').distinct().count()
- context['perbranch'] = Branch.objects.filter(hidden=False).order_by('sort_priority').annotate(
- layer_count=Count('layerbranch', distinct=True),
- recipe_count=Count('layerbranch__recipe', distinct=True),
- class_count=Count('layerbranch__bbclass', distinct=True),
- machine_count=Count('layerbranch__machine', distinct=True),
- distro_count=Count('layerbranch__distro', distinct=True))
+ # Compute per-branch counts with individual queries rather than a single
+ # annotated queryset. The multi-Count(distinct=True) approach generates one
+ # large SQL query with many LEFT JOINs that causes a gunicorn worker timeout
+ # at production data volumes. Simple per-branch COUNT queries are far cheaper.
+ # See: https://bugzilla.yoctoproject.org/show_bug.cgi?id=15391
+ perbranch = []
+ for branch in Branch.objects.filter(hidden=False).order_by('sort_priority'):
+ perbranch.append({
+ 'name': branch.name,
+ 'updates_enabled': branch.updates_enabled,
+ 'layer_count': LayerBranch.objects.filter(branch=branch).count(),
+ 'recipe_count': Recipe.objects.filter(layerbranch__branch=branch).count(),
+ 'class_count': BBClass.objects.filter(layerbranch__branch=branch).count(),
+ 'machine_count': Machine.objects.filter(layerbranch__branch=branch).count(),
+ 'distro_count': Distro.objects.filter(layerbranch__branch=branch).count(),
+ })
+ context['perbranch'] = perbranch
return context
The per-branch statistics query used a single ORM queryset with five Count(..., distinct=True) annotations spanning deep reverse FK chains (layerbranch__recipe, layerbranch__bbclass, etc.). Django translates this into one SQL query with multiple LEFT OUTER JOINs across all those tables simultaneously. At production data volumes (~541 layers, ~25k recipes) the resulting query exhausts gunicorn worker memory/time, causing a 504 Gateway Time-out. Fix by iterating over each visible branch individually and issuing simple COUNT queries per table. This replaces one huge cross-join with N×5 small indexed WHERE-clause queries that are far cheaper and independently cacheable. The template is unchanged; Django's template engine resolves dict keys and object attributes identically with dot notation. [YOCTO #15391] AI-Generated: Claude Cowork Sonnet 4.6 Signed-off-by: Tim Orling <tim.orling@konsulko.com> --- layerindex/views.py | 23 +++++++++++++++++------ 1 file changed, 17 insertions(+), 6 deletions(-)