Files
dify/api/schedule/clean_unused_datasets_task.py
kenwoodjw bfc4fe1a9a fix infinite loop when clean unused dataset (#24542)
Signed-off-by: kenwoodjw <blackxin55+@gmail.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
2025-08-26 15:44:52 +08:00

158 lines
6.6 KiB
Python

import datetime
import time
from typing import Optional, TypedDict
import click
from sqlalchemy import func, select
from sqlalchemy.exc import SQLAlchemyError
import app
from configs import dify_config
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset import Dataset, DatasetAutoDisableLog, DatasetQuery, Document
from services.feature_service import FeatureService
class CleanupConfig(TypedDict):
clean_day: datetime.datetime
plan_filter: Optional[str]
add_logs: bool
@app.celery.task(queue="dataset")
def clean_unused_datasets_task():
click.echo(click.style("Start clean unused datasets indexes.", fg="green"))
start_at = time.perf_counter()
# Define cleanup configurations
cleanup_configs: list[CleanupConfig] = [
{
"clean_day": datetime.datetime.now() - datetime.timedelta(days=dify_config.PLAN_SANDBOX_CLEAN_DAY_SETTING),
"plan_filter": None,
"add_logs": True,
},
{
"clean_day": datetime.datetime.now() - datetime.timedelta(days=dify_config.PLAN_PRO_CLEAN_DAY_SETTING),
"plan_filter": "sandbox",
"add_logs": False,
},
]
for config in cleanup_configs:
clean_day = config["clean_day"]
plan_filter = config["plan_filter"]
add_logs = config["add_logs"]
page = 1
while True:
try:
# Subquery for counting new documents
document_subquery_new = (
db.session.query(Document.dataset_id, func.count(Document.id).label("document_count"))
.where(
Document.indexing_status == "completed",
Document.enabled == True,
Document.archived == False,
Document.updated_at > clean_day,
)
.group_by(Document.dataset_id)
.subquery()
)
# Subquery for counting old documents
document_subquery_old = (
db.session.query(Document.dataset_id, func.count(Document.id).label("document_count"))
.where(
Document.indexing_status == "completed",
Document.enabled == True,
Document.archived == False,
Document.updated_at < clean_day,
)
.group_by(Document.dataset_id)
.subquery()
)
# Main query with join and filter
stmt = (
select(Dataset)
.outerjoin(document_subquery_new, Dataset.id == document_subquery_new.c.dataset_id)
.outerjoin(document_subquery_old, Dataset.id == document_subquery_old.c.dataset_id)
.where(
Dataset.created_at < clean_day,
func.coalesce(document_subquery_new.c.document_count, 0) == 0,
func.coalesce(document_subquery_old.c.document_count, 0) > 0,
)
.order_by(Dataset.created_at.desc())
)
datasets = db.paginate(stmt, page=page, per_page=50, error_out=False)
except SQLAlchemyError:
raise
if datasets is None or datasets.items is None or len(datasets.items) == 0:
break
for dataset in datasets:
dataset_query = (
db.session.query(DatasetQuery)
.where(DatasetQuery.created_at > clean_day, DatasetQuery.dataset_id == dataset.id)
.all()
)
if not dataset_query or len(dataset_query) == 0:
try:
should_clean = True
# Check plan filter if specified
if plan_filter:
features_cache_key = f"features:{dataset.tenant_id}"
plan_cache = redis_client.get(features_cache_key)
if plan_cache is None:
features = FeatureService.get_features(dataset.tenant_id)
redis_client.setex(features_cache_key, 600, features.billing.subscription.plan)
plan = features.billing.subscription.plan
else:
plan = plan_cache.decode()
should_clean = plan == plan_filter
if should_clean:
# Add auto disable log if required
if add_logs:
documents = (
db.session.query(Document)
.where(
Document.dataset_id == dataset.id,
Document.enabled == True,
Document.archived == False,
)
.all()
)
for document in documents:
dataset_auto_disable_log = DatasetAutoDisableLog(
tenant_id=dataset.tenant_id,
dataset_id=dataset.id,
document_id=document.id,
)
db.session.add(dataset_auto_disable_log)
# Remove index
index_processor = IndexProcessorFactory(dataset.doc_form).init_index_processor()
index_processor.clean(dataset, None)
# Update document
db.session.query(Document).filter_by(dataset_id=dataset.id).update(
{Document.enabled: False}
)
db.session.commit()
click.echo(click.style(f"Cleaned unused dataset {dataset.id} from db success!", fg="green"))
except Exception as e:
click.echo(click.style(f"clean dataset index error: {e.__class__.__name__} {str(e)}", fg="red"))
page += 1
end_at = time.perf_counter()
click.echo(click.style(f"Cleaned unused dataset from db success latency: {end_at - start_at}", fg="green"))