MySQL: Persistent Connection vs. Connection Pooling in Multi-Threaded Applications
To reduce the overhead of establishing new database connections, MySQL provides two options: persistent connections and connection pooling. Understanding their distinctions is crucial for optimizing database interactions in high-throughput multi-threaded applications.
Persistent Connections
Persistent connections aim to reuse existing database connections instead of creating new ones for each query. Although not explicitly shared among threads, persistent connections maintain a single open connection that is reused by multiple threads within the application. While this approach reduces connection overhead, it can result in blocking if multiple threads simultaneously request database access.
Connection Pooling
In contrast, connection pooling involves maintaining a pool of database connections. Threads acquire connections from the pool, perform their tasks, and return the connections to the pool. This allows multiple threads to access the database concurrently without experiencing significant delays due to connection establishment overhead. However, considerations must be made regarding thread wait times for acquiring connections and the queuing mechanism used by the pool.
Best Option for Multi-Threaded Applications
In multi-threaded applications with high query volumes, connection pooling is a more robust option than persistent connections. Connection pooling distributes database access across a dedicated pool of connections, minimizing contention and preventing blocking from shared connections.
Should Threads Wait or Send Requests?
When using connection pooling, threads should not wait indefinitely to acquire a connection. Instead, they should employ round-robin mechanisms to send requests on available connections. This approach reduces wait times and allows requests to enter the database queue, ensuring fair distribution of database access.
By leveraging connection pooling techniques, multi-threaded applications can significantly improve database interaction performance, handling thousands of requests per second without compromising response times or introducing bottlenecks.
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