Links are inserted when should be updated cause of frequest motion events

Chatgpts answer: Given that you have a single handler that is called frequently, and you're dealing with concurrent calls, you might want to explore the following strategies:

Database Connection Pooling: Ensure that your database connection is managed efficiently through connection pooling. This helps in reusing existing database connections instead of creating a new connection for each handler call, reducing the overhead associated with database connections.
Asynchronous Processing: Consider making your handler asynchronous. Instead of waiting for the database operation to complete before moving on to the next task, an asynchronous handler can initiate the database operation and continue with other tasks. This can be achieved using async/await or similar constructs depending on the programming language you're using.
Queueing or Buffering: Introduce a queue or a buffer to store the acceleration event data temporarily before it is processed by the handler. The handler can then work on the data from the queue sequentially, reducing the likelihood of conflicts.
Throttling: Implement a throttling mechanism to control the rate at which acceleration events are processed. This can help in preventing a flood of events from overwhelming the system and causing conflicts.
Retry and Backoff: Include a retry mechanism in your handler. If a database insertion fails due to a concurrent update, the handler can retry the operation after a short delay. Implementing an exponential backoff strategy can further help in reducing contention.
Optimistic Concurrency Control: As mentioned earlier, consider using optimistic concurrency control. Include a version number or timestamp in your database records, and when updating, check whether the record has been modified since it was retrieved by the handler.

Here's a simplified example in pseudo-code using asynchronous processing and a basic retry mechanism:

import asyncio

async def handle_acceleration_event(event):
    retry_count = 3
    while retry_count > 0:
        try:
            # Perform database operation here
            # ...

            # If successful, break out of the loop
            break
        except DatabaseConcurrencyError as e:
            # Handle concurrency conflict, decrement retry count, and wait before retrying
            retry_count -= 1
            await asyncio.sleep(0.1 * (4 - retry_count))  # Exponential backoff

# Example usage
async def main():
    events = [...]  # List of acceleration events
    tasks = [handle_acceleration_event(event) for event in events]
    await asyncio.gather(*tasks)

# Run the event loop
asyncio.run(main())

Adjust the parameters and strategies based on the specific requirements and characteristics of your application.

deep-foundation / capacitor-motion

Links are inserted when should be updated cause of frequest motion events #4

Description