The SHARDING-JDBC of distributed database middleware

Small series in doing SHARDING-JDBC today, there are some problems, on the Internet Bai, found on-line SHARDING-JDBC reference is very little, alas or to continue to learn to read the document.

SHARDING-JDBC Introduction

SHARDING-JDBC is a database horizontal extension framework that is separated from the relational database module DD-RDB in the application framework Ddframe, which is the transparent database sub-table access.

In the era of high concurrency in the Internet, in order to cope with the high concurrent read and write of DB, we use read-write separation technology. Read-write separation refers to the use of database master-slave technology (copying data into multiple nodes), decentralized read multiple libraries to support high-concurrency reading, and write only on the master library. The master-slave technology in DB is only responsible for copying and synchronizing data, while the read-write separation technology needs to be implemented by the business application itself. Sharding-jdbc through simple development, can easily realize the reading and writing separation technology.

Read-Write Separation implementation

Library and table structure design diagram:

code example

I'm here. Use SSH for test (spring+struts2+hibernate) configuration please refer to: http://www.cnblogs.com/niechen/p/8619713.html

Here we use yml way to do the sub-database table, here only shows the sub-table, the principle of the library is the same as the first to create a sharding-jdbc-core.yml file

datasources:  !! com.alibaba.druid.pool.DruidDataSource    driverClassName:com.mysql.jdbc.Driver    url:jdbc:mysql: // localhost:3306/Database     username:root    password:shardingrule:  tables:    class:      actualdatanodes:ds.class_${0..3}      tablestrategy:        inline:          shardingcolumn:id          % 4}      keygeneratorcolumnname:id  defaultkeygeneratorclass: Com.bdqn.lyrk.ssh.study.generator.MyKeyGenerator

Using 4 tables as an example

Here is a brief introduction to the above is the data of the split here only to do a data source!! followed by the kind of data sources we used have a lot of dbcp and so on. Ali's Druid here, not much to say in the back.

The following is a split of the table

Class: Represents the logical table name

Actualdatanodes: Data source name. class_${0..3} is the three table corresponding to Class_0,class_1,class_2,class_3, if it is multiple data sources, it is: Data source name _${..... CLASS_${0..3}

Tablestategy The following parameter is a specification for setting a split table

Shardingcolumn: According to which column to contract to split the table, generally we are based on the primary key so here is the ID

Algorithmexpression: Agreed to the rules of the split table, here is the 4 table corresponding to 0,1,2,3, then if the balance of 4 is definitely between 0~3, then so is class_${id% 4}

Keygeneratorcolumnname: The generator for ID is specified here

Defaultkeygenerotorclass: Specify the corresponding generator of our own

 PackageCom.bdqn.lyrk.ssh.study.generator;ImportIo.shardingjdbc.core.keygen.KeyGenerator;Importorg.springframework.context.annotation.Configuration;ImportJava.util.Random;/** * @authorYang Tianle * @date 2018/4/16 21:10*/@Configuration Public classMykeygeneratorImplementsKeygenerator {@Override PublicNumber GenerateKey () {random random=NewRandom (); introm= Random.nextint (100); returnROM; }}

View Code

Note here with the random generation do not use math to generate, or there will be decimals, then must not find the corresponding table, this is a small part of the problem of the pit dad today.

Next we want to load the yml that we just configured, we create a Shardingjdbcconfig.java

 PackageCom.bdqn.lyrk.ssh.study.config;Importio.shardingjdbc.core.api.ShardingDataSourceFactory;ImportOrg.springframework.context.annotation.Bean;Importorg.springframework.context.annotation.Configuration;ImportJavax.sql.DataSource;ImportJava.io.File;Importjava.io.IOException;Importjava.sql.SQLException;/** * @authorYang Tianle * @date 2018/4/16 17:10*/@Configuration Public classShardingjdbcconfig {@Bean PublicDataSource DataSource ()throwsIOException, SQLException {DataSource DataSource= Shardingdatasourcefactory.createdatasource (NewFile (shardingjdbcconfig.class. getClassLoader (). GetResource ("Sharding-jdbc-core.yml"). GetFile ())); returnDataSource; }}

View Code

Load our YML configuration. It must be from ClassLoader to get the configuration.

Next, let's test the add operation (business layer I won't write, just a Hibernate save method), insert 5 data to see where they were inserted? (I emptied the table's data)

This is the 5 data I inserted in order 0~3

You can also be based on these IDs to find the remainder, see the corresponding table?

Refer to Sharding official documentation and official DEMO,SSH integration examples http://www.cnblogs.com/niechen/p/8619713.html

The SHARDING-JDBC of distributed database middleware