MySQL sub-list to achieve millions of tens of thousands of records distributed storage design pattern of bulk query

We know that we can put a large number of records of MySQL big table according to the primary key, Time field, conditional field, etc. into several tables and even saved in several servers.

The only problem is that the query is cumbersome across servers and can only be solved through the application. Talk about the solution in Java. Other language principles are similar.

The table here is not the partition of MySQL 5.1, but the person who has several tables or different servers for separating a table.

1. Application level Implementation

See schematic

Selectthreadmanager Table Data Query Manager

It creates a thread pool for each database or server in the table

AddTask ()-Add a task

Stoptask ()-Stop task

GetResult ()-Get execution results

Fastest execution time = slowest MySQL node query consumption time

The slowest execution time = timeout time