PHP method to implement database sharding and shrinkage

With the development of Internet applications, the rapid growth of data volume has become a major problem faced by companies, and database sharding technology was born to deal with this problem. Database sharding is a technology that divides a large database into multiple smaller databases. Through sharding, data can be dispersed across multiple servers to achieve horizontal expansion and improve database performance and flexibility.

However, with the adjustment and development of business, the capacity of the database often needs to be dynamically adjusted according to the actual situation, and accordingly, the sharding also needs to be reduced. This article mainly introduces the method of implementing database sharding and shrinking in PHP.

1. Background and principles of database sharding and shrinkage

In large websites, as data continues to increase, the capacity of the database will also continue to expand. At a certain moment, the data capacity of some shards may have exceeded a set threshold, so these shards need to be spread out to other shards. The specific operations must take into account issues such as data migration and concurrency security and performance of shrink operations.

In database sharding, the hash function of sharding is the core technology to implement sharding. The data will be distributed to multiple different shards according to the processing results of the hash function. For example, if 1,000 user data is hashed and the result is a number between 0 and 4, then this batch of data will be stored in five shards numbered 0 to 4.

When we want to shrink, we need to migrate some unbalanced data to other shards. Usually, we choose to shrink the shards with relatively even data. At the same time, we also need to consider issues such as data security, performance, and stability.

2. Implementation steps

1. Determine the shrinkage strategy

When it is necessary to shrink the database, we need to formulate specific shrinkage strategies based on the actual situation. content strategy. It can be comprehensively considered based on the data volume, access pressure and other factors. Generally, it is necessary to shrink the shards with relatively even data capacity, and at the same time, the reduced data needs to be backed up.

2. Migrate data

For the data raised after the reduction, we need to migrate the data to other shards. The specific method is: from the reduced shards Read a certain proportion of the data, then perform hash calculation and distribute it to other shards based on the result. The migration process needs to consider issues such as data migration speed and data accuracy.

3. Reallocation of shards after shrinkage

After the shrinkage is completed, the remaining shards need to be reallocated, and the hash function of the shards may occur. Changes require ensuring that data is correctly migrated to new shards. In addition, it is necessary to ensure that the data storage structure remains unchanged, otherwise data may be lost or inaccessible.

4. Complete the reduction

According to the reduction strategy and data backup requirements, complete the reduction and ensure the availability and security of the data.

3. Application of related technologies

In the process of implementing database sharding, we need to use many related technologies, such as PHP database extension package (pdo_mysql, pdo_pgsql), Redis, MySQL cluster, MySQL Proxy, etc., these technologies can well serve the needs of sharding reduction. In addition, attention needs to be paid to timing control, such as preventing concurrent access and avoiding program crashes. This can be achieved by using mechanisms such as segmented processing and current limiting.

4. Summary

Through the introduction of this article, we have learned about the related technologies and implementation steps of database sharding and shrinkage. In practical applications, we need to determine the actual shrinkage strategy based on specific circumstances and adopt corresponding technical implementation solutions to achieve efficient and stable operation of the database.

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