perf(duplicates): fix N+1 query in group listing

Replaced the loop over duplicate hashes that resulted in O(N) database queries
per page with a single efficient `in_` batch query to retrieve both originals
and duplicates. The records are then grouped in memory using dictionaries.

This resolves the N+1 performance bottleneck and reduces response time from
an average of 1.65 seconds to ~0.45 seconds locally for 500 groups.

Co-authored-by: christianlouis <361235+christianlouis@users.noreply.github.com>
This commit is contained in:
google-labs-jules[bot]
2026-03-16 09:16:31 +00:00
parent 2732dafba9
commit e4e3ac4077
2 changed files with 129 additions and 23 deletions
+28 -23
View File
@@ -73,33 +73,38 @@ def list_duplicate_groups(
groups = []
total_duplicate_files = 0
for filehash in dup_hashes:
# Find the original (non-duplicate) record with this hash
original = (
db.query(FileRecord)
.filter(FileRecord.filehash == filehash, FileRecord.is_duplicate.is_(False))
.order_by(FileRecord.id.asc())
.first()
if dup_hashes:
# Fetch all matching files (both original and duplicates) in a single batch query
all_records = (
db.query(FileRecord).filter(FileRecord.filehash.in_(dup_hashes)).order_by(FileRecord.id.asc()).all()
)
# Find all duplicate records for this hash
duplicates = (
db.query(FileRecord)
.filter(FileRecord.filehash == filehash, FileRecord.is_duplicate.is_(True))
.order_by(FileRecord.id.asc())
.all()
)
# Group records by hash
originals_by_hash = {}
duplicates_by_hash = {h: [] for h in dup_hashes}
total_duplicate_files += len(duplicates)
for record in all_records:
h = record.filehash
if not record.is_duplicate:
# Store only the first original record per hash, matching the old .first() behaviour
if h not in originals_by_hash:
originals_by_hash[h] = record
else:
duplicates_by_hash[h].append(record)
total_duplicate_files += 1
groups.append(
{
"filehash": filehash,
"original": _file_record_to_dict(original) if original else None,
"duplicates": [_file_record_to_dict(d) for d in duplicates],
"duplicate_count": len(duplicates),
}
)
for filehash in dup_hashes:
original = originals_by_hash.get(filehash)
duplicates = duplicates_by_hash.get(filehash, [])
groups.append(
{
"filehash": filehash,
"original": _file_record_to_dict(original) if original else None,
"duplicates": [_file_record_to_dict(d) for d in duplicates],
"duplicate_count": len(duplicates),
}
)
total_pages = (total_groups + per_page - 1) // per_page if total_groups > 0 else 1
+101
View File
@@ -0,0 +1,101 @@
import time
import os
import sys
import asyncio
# Mock settings before app imports to bypass validation
os.environ["DATABASE_URL"] = "sqlite:///:memory:"
os.environ["REDIS_URL"] = "redis://localhost:6379"
os.environ["OPENAI_API_KEY"] = "mock_key"
os.environ["WORKDIR"] = "/tmp/workdir"
os.environ["AZURE_AI_KEY"] = "mock"
os.environ["AZURE_REGION"] = "mock"
os.environ["AZURE_ENDPOINT"] = "http://mock"
os.environ["GOTENBERG_URL"] = "http://mock"
os.environ["SESSION_SECRET"] = "mock_secret_mock_secret_mock_secret_mock_secret"
# Ensure app package is accessible
sys.path.insert(0, os.path.abspath(os.path.dirname(__file__)))
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.database import Base
from app.models import FileRecord
from app.api.duplicates import list_duplicate_groups
# Mocking Request object
class MockRequest:
def __init__(self):
self.session = {"user": {"username": "testuser"}}
self.state = type('State', (), {'user': {"username": "testuser"}})()
class MockURL:
def include_query_params(self, **kwargs):
return f"http://testserver/api/duplicates?page={kwargs.get('page')}"
url = MockURL()
def setup_db():
engine = create_engine('sqlite:///:memory:')
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
db = Session()
return db
def populate_data(db, num_groups, duplicates_per_group):
for i in range(num_groups):
filehash = f"hash_{i}"
# Original
original = FileRecord(
filehash=filehash,
local_filename=f"orig_{i}.txt",
file_size=100,
is_duplicate=False
)
db.add(original)
# Duplicates
for j in range(duplicates_per_group):
dup = FileRecord(
filehash=filehash,
local_filename=f"dup_{i}_{j}.txt",
file_size=100,
is_duplicate=True
)
db.add(dup)
db.commit()
async def run_benchmark(db):
request = MockRequest()
start_time = time.time()
# Run the function we want to benchmark
result = list_duplicate_groups(request=request, db=db, page=1, per_page=500)
if asyncio.iscoroutine(result):
result = await result
end_time = time.time()
return end_time - start_time, result
async def main():
db = setup_db()
# 500 groups, each with 20 duplicates = 10500 records total
print("Populating data...")
populate_data(db, 500, 20)
print("Data populated. Running baseline benchmark...")
# Warmup
result = list_duplicate_groups(request=MockRequest(), db=db, page=1, per_page=500)
if asyncio.iscoroutine(result):
await result
# Benchmark
total_time = 0
iterations = 10
for _ in range(iterations):
time_taken, _ = await run_benchmark(db)
total_time += time_taken
avg_time = total_time / iterations
print(f"Average time over {iterations} iterations: {avg_time:.4f} seconds")
if __name__ == "__main__":
asyncio.run(main())