MySQL distributed transaction processing and concurrency control project experience analysis

MySQL distributed transaction processing and concurrency control project experience analysis

In recent years, with the rapid development of the Internet and the increasing number of users, the requirements for databases have It is also increasing day by day. In large-scale distributed systems, MySQL, as one of the most commonly used relational database management systems, has always played an important role. However, as the data size increases and concurrent access increases, MySQL's performance and scalability face severe challenges. Especially in a distributed environment, how to handle transactions and control concurrency has become an urgent problem to be solved.

This article will explore the best practices of transaction processing and concurrency control of MySQL in a distributed environment through the experience analysis of an actual project.

In our project, we need to process massive amounts of data and require data consistency and reliability. To meet these requirements, we adopt a distributed transaction processing mechanism based on the two-phase commit (2PC) protocol.

First, in order to achieve distributed transactions, we split the database into multiple independent fragments, each fragment is deployed on a different node. In this way, each node only needs to be responsible for managing and processing its own data, which greatly reduces the load and latency of the database.

Secondly, in order to ensure the consistency of transactions, we introduce the concepts of coordinators and participants. The coordinator is a special node responsible for coordinating the execution process of distributed transactions. Participants are nodes responsible for performing actual operations. After the participants complete the operation, the results are returned to the coordinator.

In the execution of transactions, we adopt the two-phase commit (2PC) protocol. The first phase is the preparation phase. In this phase, the coordinator sends preparation requests to all participants, and the participants perform relevant operations and record redo logs. If all participants execute successfully and return a ready message, the coordinator sends a commit request; otherwise, the coordinator sends an abort request. The second phase is the submission phase. After receiving the submission request, the participant performs the transaction submission operation.

In addition to distributed transaction processing, we also need to solve the problem of concurrency control. In a distributed environment, since multiple nodes access the same data at the same time, the consistency and concurrency of the database are easily affected. To solve this problem, we adopt an optimistic concurrency control strategy.

Optimistic concurrency control is a version-based concurrency control strategy that determines conflicts between read and write operations by adding a version number to each data item in the database. When a transaction reads a data item, the current version number is recorded; when the transaction commits, it is checked whether the current version number is consistent with the previously read version number. If it is consistent, it means that no other transaction modified the data item during the transaction and it can be submitted; if it is inconsistent, the transaction needs to be re-executed.

At the same time, in order to improve concurrency, we also use distributed locks to control access to shared resources through the lock mechanism. For read operations, we use shared locks; for write operations, we use exclusive locks.

Our project experience shows that by adopting a distributed transaction processing mechanism and an optimistic concurrency control strategy based on the two-phase commit protocol, the transaction processing and concurrency control problems of MySQL in a distributed environment can be effectively solved. At the same time, through reasonable data splitting and the use of distributed locks, the performance and scalability of the system can be improved.

In short, MySQL distributed transaction processing and concurrency control is a complex and critical issue. In actual projects, factors such as the system's data size, access mode, and performance requirements need to be comprehensively considered. Through continuous practice and summary, we believe that we can find the best practices suitable for our own system and improve the reliability and performance of the system.

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