dosubot[bot] commented on issue #3059:
URL: https://github.com/apache/hugegraph/issues/3059#issuecomment-4679851161

   <!-- Answer -->
   The reason restarting doesn't help is that **HugeGraph persists 
running/pending tasks as `~task` vertices in backend storage and automatically 
restores them on server startup** 
[[1]](https://github.com/apache/hugegraph/blob/9126c80e414c073b60fc074361b211cfb409e0eb/hugegraph-server/hugegraph-core/src/main/java/org/apache/hugegraph/StandardHugeGraph.java).
 So your problematic task keeps getting re-queued every time the server comes 
back up.
   
   **To break out of this cycle, use the force-delete API:**
   
   ```bash
   DELETE http://{IP}:{PORT}/graphs/{GRAPH_NAME}/tasks/{TASK_ID}?force=true
   ```
   
   This removes the task from both memory and backend storage, preventing it 
from being restored on the next restart 
[[2]](https://github.com/apache/hugegraph/blob/9126c80e414c073b60fc074361b211cfb409e0eb/hugegraph-server/hugegraph-api/src/main/java/org/apache/hugegraph/api/job/TaskAPI.java)
 [[3]](https://github.com/apache/hugegraph/issues/3057#issuecomment-4656832523).
   
   **If all APIs are hanging**, try this sequence:
   
   1. Restart the server
   2. **Immediately** issue the force-delete request before the restored task 
consumes all resources again
   3. If you don't know the task ID, try `GET 
/graphs/{graph}/tasks?status=RUNNING` quickly after restart
   
   **If that still doesn't work** (because the task re-queues too fast), you 
could try:
   
   - Temporarily reduce the Gremlin task thread pool or add a short startup 
delay to give yourself a window
   - As a last resort, if you have direct access to the RocksDB data directory, 
you could delete and recreate the problematic graph entirely using `DELETE 
/graphs/{graph}/clear` right after restart
   
   **To prevent this in the future:**
   
   - Set `task.result_size_limit` to a smaller value to prevent tasks from 
accumulating massive results
   - For complex analytical queries, consider using the OLAP/algorithm APIs 
rather than raw Gremlin tasks, or break the query into smaller batches
   - Note that HugeGraph only has 4 threads dedicated to Gremlin task execution 
[[4]](https://github.com/apache/hugegraph/blob/9126c80e414c073b60fc074361b211cfb409e0eb/hugegraph-server/hugegraph-core/src/main/java/org/apache/hugegraph/task/TaskManager.java),
 so a single resource-intensive task can significantly impact throughput
   
   
   <!-- Dosu Comment Footer -->
   *To reply, just mention 
[@dosu](https://go.dosu.dev/dosubot?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=reply-with-mention&utm_term=apache%2Fhugegraph).*
   
   ---
   
   Share context across your team and agents. Try 
[Dosu](https://dosu.dev?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-tagline&utm_term=apache%2Fhugegraph).
   
   [![Leave 
Feedback](https://img.shields.io/badge/Leave%20Feedback-555555?style=flat)](https://app.dosu.dev/response-feedback?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-feedback&utm_term=apache%2Fhugegraph&message_id=814ded56-ebdb-48d4-ac3b-6507af5bcf36)
 [![Learn about hugegraph with 
Dosu](https://img.shields.io/badge/Learn%20about%20hugegraph%20with%20Dosu-2f7b3f?style=flat&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iODYiIGhlaWdodD0iODkiIHZpZXdCb3g9IjAgMCA4NiA4OSIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj48cGF0aCBkPSJNNS4yOTIzNiAxMi43OTI4TDE3Ljc1OTMgNi42ODE4OFY3Mi41NjY3TDUuMjkyMzYgODQuMDYxOFYxMi43OTI4WiIgZmlsbD0iI0I0QkI5MSIvPjxwYXRoIGQ9Ik0xOC4yNTc1IDczLjExOTZMNTkuMTMyOSA3Mi43NDhMNTEuNzAxMSA4Mi40MDk1TDI5LjAzMzggODYuMjkxTDYuMjM5NjIgODUuMTU1NEwxOC4yNTc1IDczLjExOTZaIiBmaWxsPSIjNzc4NTYxIi8%2BPHBhdGggZD0iTTE3LjQ5MTYgMy43MzYzM0wzLjU4NTU3IDEyLjcwOTlWODMuNTc5MkMzLjU4NTU3IDg0Ljc1N
 
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%2BPHBhdGggZmlsbC1ydWxlPSJldmVub2RkIiBjbGlwLXJ1bGU9ImV2ZW5vZGQiIGQ9Ik00MC43MDQgMC41MTgwNjZIMTcuMDQzOVY3Ni4yMjIxSDQwLjcwNEg0Mi41ODA1SDQ3LjgwMTNDNjguNzA2NCA3Ni4yMjIxIDg1LjY1MzMgNTkuMjc1MiA4NS42NTMzIDM4LjM3MDFDODUuNjUzMyAxNy40NjUgNjguNzA2MyAwLjUxODA2NiA0Ny44MDEzIDAuNTE4MDY2SDQyLjU4MDVINDAuNzA0WiIgZmlsbD0iI0YzRjZGMSIvPjxwYXRoIGQ9Ik0xNy4wNDM5IDAuNTE4MDY2Vi02LjU3OTE5SDkuOTQ2NjlWMC41MTgwNjZIMTcuMDQzOVpNMTcuMDQzOSA3Ni4yMjIxSDkuOTQ2NjlWODMuMzE5NEgxNy4wNDM5Vjc2LjIyMjFaTTE3LjA0MzkgNy42MTUzMkg0MC43MDRW
 
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
 
WNrIiBzdHJva2Utd2lkdGg9IjcuNjkxNjEiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIgc3Ryb2tlLWxpbmVqb2luPSJyb3VuZCIvPjxwYXRoIGQ9Ik0wLjM0ODYzMyA4NS40OTQ2QzAuMzQ4NjMzIDg1LjQ5NDYgMjkuNDg1NiA4NS44MzA5IDM0LjgwOSA4NS42OThDNDQuODMzNyA4NS40NDc3IDUxLjI4NzIgODQuNDAyIDU3LjUyNjkgNzguOTcyNEM2Mi44MTI5IDc0LjM3MjcgNzUuMTM0MiA1OS42ODM2IDc1LjEzNDIgNTkuNjgzNiIgc3Ryb2tlPSJibGFjayIgc3Ryb2tlLXdpZHRoPSI2LjE2NDgyIi8%2BPC9zdmc%2B)](https://github.dosu.com/apache/hugegraph?utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-learn-repo&utm_term=apache%2Fhugegraph)
 [![Add Dosu to your 
team](https://img.shields.io/badge/Add%20Dosu%20to%20your%20team-1f6feb?style=flat)](https://app.dosu.dev/signup?referrer=openSource&source=github-footer&utm_source=github&utm_medium=bot-comment&utm_campaign=github-comment-footer-20260415&utm_content=knowledge-infrastructure-add-team&utm_term=apache%2Fhugegraph)


-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: [email protected]

For queries about this service, please contact Infrastructure at:
[email protected]


---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]

Reply via email to