Shulou(Shulou.com)06/01 Report--

Sharding of data can be divided into two split modes according to the type of split rules. One is to split into different databases (hosts) according to different tables (or Schema), which can be called vertical (vertical) split of data.

The other is to split the data in the same table to multiple databases (hosts) according to certain conditions according to the logical relationship of the data in the table, which is called horizontal (horizontal) split of the data.

Advantages of vertical split:

After the split, the business is clear and the split rules are clear.

It is easy to integrate or expand between systems

It is easy to manage tables on different machines according to cost, level of application, type of application, etc.

The design pattern of database table which is convenient to realize dynamic and static separation, cold and hot separation.

Data maintenance is relatively simple

Disadvantages of vertical split:

Some business tables can not be Join, so they can only be solved by interface, which increases the complexity of the system.

Due to the different limitations of each business, there is a performance bottleneck of a single database, so it is not easy to expand data and improve performance.

Transaction processing is complex

Advantages of horizontal split:

The data of single database and single table can be kept at a certain order of magnitude, which is helpful to improve the performance.

The split table structure is the same, the application layer modification is less, only need to add routing rules.

The stability and load capacity of the system are improved.

Disadvantages of horizontal split:

After sharding, the data is dispersed, cross-library join operation is difficult and the performance is poor.

Split rules are difficult to abstract

The consistency of sharding transactions is difficult to solve.

The difficulty and maintenance of data expansion are extremely large.

To sum up, what vertical split and horizontal split have in common are:

There is a problem with distributed transactions

Cross-node Join problem

There are problems of merging sorting and paging across nodes

There is a problem of multiple data source management.

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