[FEATURE] Improve response upsert bulk endpoint performance

[frascuchon]

The new bulk endpoint for response creation takes a long time to process the request (around 6 seconds for 100 responses). This may affect the global server performance. The bottleneck must be identified and fixed as soon as possible.

cc @jfcalvo

[dosubot]

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Based on the current implementation of the response upsert bulk endpoint in Argilla, there are several strategies that could be employed to improve its performance:

1. Batch Processing: Instead of processing each response one by one, you can process them in batches. This can significantly reduce the number of database operations and thus improve performance.

2. Parallel Processing: If the processing of each response is independent of others, you can use parallel processing to speed up the operation. This can be achieved by using Python's concurrent.futures or asyncio libraries.

3. Database Optimization: You can optimize your database queries to improve performance. This can include using indexes for faster lookup, denormalizing your data, or using stored procedures.

4. Caching: If you have some data that is used frequently and does not change often, you can cache it to reduce the number of database hits.

However, the actual implementation of these strategies would depend on the specific requirements and constraints of your application.

The current implementation of the response upsert bulk endpoint is the create_current_user_responses_bulk function. This function is a POST request to the "/me/responses/bulk" endpoint. It takes in a ResponsesBulkCreate object in the request body, which contains multiple response items to be created or updated.

For each item in the request body, it retrieves the corresponding record using the _get_record function. It then authorizes the current user to create a response for the record. After authorization, it calls the upsert_response function from the datasets module to create or update the response. If any error occurs during this process, it appends a ResponseBulk object with the error detail to the responses_bulk_items list. If no error occurs, it appends a ResponseBulk object with the created or updated response to the responses_bulk_items list.

Finally, it returns a ResponsesBulk object containing all the ResponseBulk items in the responses_bulk_items list.

You can find the code for the create_current_user_responses_bulk function in the responses.py file.

As for the current performance of the response upsert bulk endpoint, I wasn't able to find specific metrics within the repository. However, implementing the strategies mentioned above should help improve its performance.

If you need further clarification or have additional questions, feel free to ask.

Sources

• src/argilla/server/apis/v1/handlers/records.py
• src/argilla/server/apis/v1/handlers/responses.py

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[frascuchon]

Fixed by #4451