Distributed storage method based on MySQL design

Abstract

The invention discloses a distributed storage method based on MySQL design. The storage method comprises the following steps: performing data fragmentation on a MySQL database; performing master-slave copying; and carrying out load balancing and fault recovery. Proper fragmentation methods and strategies are selected, data distribution is balanced, and the hot spot problem is avoided. The data is backed up regularly, and an effective recovery strategy is formulated to prevent the data from being lost or damaged. And the construction of an efficient and stable distributed database system is facilitated.

Description

Technical Field

[0001] The present invention relates to the field of data storage, and in particular to a distributed storage method based on MySQL design. Background Art

[0002] The solution of the existing technology: The distributed storage solution based on MySQL considers improving the design of the distributed storage solution from the logical structure of the data table to optimizing the performance of the data table, from improving the data query principle to improving the performance of slow SQL, from transactions to optimizing the transaction execution efficiency, etc. The specific details are as follows: Data sharding divides the data into different database instances by row, such as sharding based on user ID or timestamp. At the same time, the data is divided into different database instances by column, which is suitable for separation between different modules. The main database writes and the slave database reads to share the query pressure. Use asynchronous or semi-synchronous replication to ensure data consistency. Pay attention to the failover strategy when the main database fails.

[0003] Split data horizontally into multiple database instances to reduce the load on a single instance. Use strategies such as consistent hashing or range sharding to select the appropriate sharding solution based on business characteristics. Use load balancing to send write requests to the master database and distribute read requests to multiple slave databases. Use middleware to achieve read-write separation. Introduce a load balancer at the application layer or database layer to intelligently distribute requests to different database instances. Improve the performance of a single database instance through index optimization, query optimization, and database design optimization. Perform performance analysis regularly and adjust database configuration. Provide higher availability, flexibility, and scalability.

[0004] Using the master-slave replication architecture, write requests are sent to the master database, and read requests are distributed to multiple slave databases to reduce the burden on the master database. By allowing the data redundancy of the MySQL database to be transmitted through binlog, the binlog is transferred from the master database to the slave database, and replayed on the slave database to achieve data redundancy, and the capacity of the database is expanded through data sharding, sub-library, and sub-table. Adopt a horizontal sharding strategy to distribute data to multiple database instances to reduce the pressure on a single database. Use middleware (such as MySQLProxy, ProxySQL) to achieve read-write separation and optimize database query performance. Through Zookeeper to coordinate DBLE cluster metadata, using DBLE as a high-performance sub-library and sub-table middleware, MySQL sharding can be expanded horizontally. Each MySQL shard adopts a master-slave solution, implements a regular backup strategy, and formulates a quick recovery plan to deal with data loss or damage. Ensure high availability.

[0005] By transmitting the data redundancy of the MySQL database through binlog, transferring the binlog from the master database to the slave database, and replaying it on the slave database, the data redundancy is achieved, and the capacity of the database is expanded through data sharding, sub-database, and sub-table. Secondly, the master-slave identity switching is essentially to change the master-slave identity of each node in the database to increase the concurrency and improve the availability, so that the client can always use the master database. Although this can achieve the increase in concurrency, availability, and concurrency, the problem that comes with it is that more hardware resources will be occupied, the availability may be reduced, and the data during the switching period will be lost. Summary of the invention

[0006] In view of the above problems, the present invention is proposed to provide a distributed storage method based on MySQL design that overcomes the above problems or at least partially solves the above problems.

[0007] According to one aspect of the present invention, a distributed storage method based on MySQL is provided, the storage method comprising:

[0008] Shard the MySQL database;

[0009] Master-slave replication;

[0010] Perform load balancing and fault recovery.

[0011] Optionally, sharding the MySQL database specifically includes: horizontally slicing the data into different database instances.

[0012] Optionally, the data sharding strategy is range sharding, hash sharding and directory sharding.

[0013] Optionally, the range sharding is divided according to the range of the primary key.

[0014] Optionally, the hash sharding distributes data to multiple nodes through a hash algorithm to avoid hotspot data.

[0015] Optionally, the directory sharding specifically includes: allocating data to multiple sharding tables, suitable for specific query modes.

[0016] Optionally, the horizontal segmentation of the data into different database instances specifically includes:

[0017] Determine the sharding key and select appropriate fields as the basis for sharding;

[0018] Design sharding strategies and formulate reasonable sharding plans based on data characteristics;

[0019] Modify the application layer code and implement data routing logic to direct requests to the correct shard.

[0020] Optionally, the master-slave replication specifically includes: copying data from a master node to multiple slave nodes to ensure that the system continues to operate normally when a master node fails.

[0021] The present invention provides a distributed storage method based on MySQL design, which includes: sharding the MySQL database; master-slave replication; load balancing and fault recovery. Select appropriate sharding methods and strategies to balance data distribution and avoid hot spots. Back up data regularly and formulate effective recovery strategies to prevent data loss or damage. It is helpful to build an efficient and stable distributed database system.

[0022] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0024] Figure 1 A flowchart of a distributed storage method based on MySQL design provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0026] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0027] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0028] With the surge in data volume, traditional single database architecture is difficult to meet the requirements of high availability, scalability and performance. As a popular relational database, MySQL does not support distributed storage, but it implements distributed storage through architectural design and tools.

[0029] The specific plan is as follows: Distribute the MySQL database to multiple nodes to achieve load balancing and high availability. It mainly includes: data sharding, master-slave replication, load balancing and fault recovery. Data sharding is to divide the data horizontally into different database instances. The sharding strategies are range sharding, hash sharding and directory sharding. Among them, range sharding is based on the range of the primary key, such as the ID range. Hash sharding distributes data to multiple nodes through the hash algorithm to avoid hot data. Directory sharding is to distribute data to different shard tables, which is suitable for specific query modes.

[0030] The specific implementation is as follows: determine the sharding key and select the appropriate field as the basis for sharding. Design the sharding strategy and formulate a reasonable sharding plan based on the characteristics of the data. Modify the application layer code, implement the data routing logic, and direct the request to the correct shard. Among them, master-slave replication is a key technology for achieving high availability and data backup. By replicating data from the master node to multiple slave nodes, it ensures that the system can still operate normally even if the master node fails. The specific implementation steps are to configure the master node, enable binary log (binlog), and set a unique ID. Configure the slave node, connect to the master node and start data replication. Monitor the replication status, ensure data synchronization, and handle exceptions in time. At the same time, load balancing can disperse read requests to multiple slave nodes, thereby improving the system's concurrent processing capabilities. Through Zookeeper to coordinate DBLE cluster metadata, use DBLE as a high-performance sharding middleware to implement intelligent routing of requests. Dynamically adjust request distribution according to node load to avoid overloading a single node. Fault recovery strategy ensures that the system can recover quickly when a fault occurs. Back up the database regularly to ensure that data can be recovered. Monitor node health status: Use the monitoring tool Prometheus to monitor each node in real time. Implement automatic failover: When the master node fails, traffic is automatically switched to the slave node.

[0031] The distributed storage solution based on MySQL can effectively solve the scalability and high availability problems faced by a single database. Through reasonable data sharding, master-slave replication, load balancing and fault recovery mechanisms, enterprises can build a stable and reliable distributed database system. When implementing, it is necessary to combine specific business scenarios and select appropriate technical solutions to meet the needs of business development.

[0032] Beneficial effects: By achieving the basic guarantee of high performance and high concurrency of MySql database, through the key of database high availability and switching identity, creating partition tables to optimize node performance and partition isolation. Ensure the consistency of data between different nodes in a distributed environment, especially in master-slave replication and sharding scenarios. Design a high-availability architecture to cope with node failures, including automatic failover and data recovery strategies. Effectively distribute request loads, minimize network latency and query response time, and improve performance by optimizing query, indexing and caching mechanisms. Avoid single-point bottlenecks and ensure that the system can handle high concurrency efficiently. Choose appropriate sharding methods and strategies to balance data distribution and avoid hot spots. Back up data regularly and develop effective recovery strategies to prevent data loss or damage. Based on the above, solve the problems of frequent database downtime, insufficient database capacity, data consistency, load balancing, latency and performance optimization, and data sharding strategy. Solving the problem helps build an efficient and stable distributed database system.

[0033] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A distributed storage method based on MySQL design, characterized in that: The storage method comprises: Shard the MySQL database; Master-slave replication; Perform load balancing and fault recovery.

2. According to a distributed storage method based on MySQL design according to claim 1, it is characterized in that: The data sharding of the MySQL database specifically includes: horizontally slicing the data into different database instances.

3. According to a distributed storage method based on MySQL design according to claim 1, it is characterized in that: The data sharding strategies include range sharding, hash sharding and directory sharding.

4. A distributed storage method based on MySQL design according to claim 3, characterized in that: The range sharding is divided according to the range of the primary key.

5. According to a distributed storage method based on MySQL design according to claim 3, it is characterized in that: The hash sharding distributes data to multiple nodes through a hash algorithm to avoid hot spots.

6. A distributed storage method based on MySQL design according to claim 3, characterized in that: The directory sharding specifically includes: allocating data to multiple sharding tables, suitable for specific query modes.

7. A distributed storage method based on MySQL design according to claim 2, characterized in that: The horizontal segmentation of data into different database instances specifically includes: Determine the sharding key and select appropriate fields as the basis for sharding; Design sharding strategies and formulate reasonable sharding plans based on data characteristics; Modify the application layer code and implement data routing logic to direct requests to the correct shard.

8. The distributed storage method based on MySQL design according to claim 1, characterized in that: The master-slave replication specifically includes: replicating data from a master node to multiple slave nodes to ensure that the system still operates normally when a master node fails.

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