@[toc]
一、简述
- 简述
ShardingSphere-Proxy4.0 已经升级到5.0了，但是两者的配置文件还有一定的差别的，这篇文章讲述的就是ShardingSphere-Proxy 5.0 的落地。概念、分表、分库、分库分表的原理的基本和4.0一样的，需要了解可查看 https://blog.csdn.net/Fu_Shi_...。 - 开发者文档
https://shardingsphere.apache...
二、ShardingSphere-Proxy5.0 落地
环境
JAVA JDK下载
https://pan.baidu.com/s/1A-ksNN0YicT3hXjFscGGwA 提取码：r9e0JDBC数据连接驱动下载
https://pan.baidu.com/s/1924iUe7wxGpStAzxxv2K3g 提取码：jy7zShardingSphere-Proxy 5.0 下载、
https://archive.apache.org/dist/shardingsphere/5.0.0/- Window 11
落地
条件
- 真实数据库
- 逻辑数据库
- ShardingSphere-Proxy5.0 配置文件
步骤
新建真实数据库和表【hmms.user 表为例】
数据库表结构语句
SET NAMES utf8mb4; SET FOREIGN_KEY_CHECKS = 0; -- ---------------------------- -- Table structure for user -- ---------------------------- DROP TABLE IF EXISTS `user`; CREATE TABLE `user` ( `useid` int(11) NOT NULL, `usenam` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '登录名', `usepwd` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '登录密码', `usestate` int(11) NULL DEFAULT 2 COMMENT '-1：删除1：注销 2：正常 3：挂失', `usekey` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户秘钥', `usetel` varchar(11) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户手机', `createbyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '添加人', `createbytime` datetime(0) NULL DEFAULT NULL COMMENT '添加时间', `modifybyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '修改人', `modifybytime` datetime(0) NULL DEFAULT NULL COMMENT '修改时间', PRIMARY KEY (`useid`) USING BTREE ) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic; SET FOREIGN_KEY_CHECKS = 1;运行结果如下：
2. 修改ShardingSphere-Proxy5.0 配置文件，并连接
config-sharding.yaml
```
# 3、创建客户端连接库
schemaName: hmms
#1、连接mysql
dataSources:
hmmsdatasources-0:
url: jdbc:mysql://localhost:3306/hmms?serverTimezone=UTC&useSSL=false
username: root
password: ****
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
# 2、分片规则
rules:
- !SHARDING
tables:
user: #表名
actualDataNodes: hmmsdatasources-0.user-${0..1} #分表规则
tableStrategy:
standard:
shardingColumn: useid #分片键
shardingAlgorithmName: use_MOD #分表算法
shardingAlgorithms: #分表算法
use_MOD: #取模算法
type: MOD
props:
sharding-count: 2
```
server.yaml
```
rules:
- !AUTHORITY
users:
- root@%:*****
- sharding@:sharding
provider:
type: ALL_PRIVILEGES_PERMITTED
```
运行命令
```
#在ShardingSphere-Proxy bin
start.bat 端口号
```
运行结果如下：
3. 新建逻辑数据连接，并执行表结构和数据脚本
逻辑库执行结果如下：
逻辑数据库添加两条数据
SQL语句
```
INSERT INTO `user` VALUES (1, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);
INSERT INTO `user` VALUES (2, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);
```
执行结果如下：
- 分库分表
ShardingSphere-Proxy 5.0 配置
# 3、创建客户端连接库
schemaName: hmms
#1、连接mysql
dataSources:
hmmsdatasources-0:
url: jdbc:mysql://主机地址:端口号/hmms-0?serverTimezone=UTC&useSSL=false
username: root
password: 密码
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
hmmsdatasources-1:
url: jdbc:mysql://主机地址:端口号/hmms-1?serverTimezone=UTC&useSSL=false
username: root
password: 密码
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
# 2、分片规则
rules:
- !SHARDING
tables:
user:
actualDataNodes: hmmsdatasources-${0..1}.user-${0..1}
tableStrategy:
standard:
shardingColumn: useid
shardingAlgorithmName: use_MOD
databaseStrategy: #分库规则
standard:
shardingColumn: useid
shardingAlgorithmName: use_MOD
keyGenerateStrategy:
column: useid
keyGeneratorName: snowflake
shardingAlgorithms:
use_MOD:
type: MOD
props:
sharding-count: 2
use_HASH_MOD:
type: HASH_MOD
props:
sharding-count: '2'
keyGenerators:
snowflake:
type: SNOWFLAKE
props:
worker-id: 123分片算法
- 取模算法
shardingAlgorithms: #分表算法 use_MOD: #取模算法 type: MOD props: sharding-count: 2 #分表数据和分表的表达式必须是一致的
范围算法
shardingAlgorithms: use_BOUNDARY_RANGE: type: BOUNDARY_RANGE props: sharding-ranges: 2,100 #多个节点是以逗号分割 [是根据分的表结合配置节点] #备注 #分片键为：useid int类型 #分表的为3个表 #sharding-ranges: 2,100 是以2为节点，小于2的数据存到表0，2到99存到表1,100以上存到表3容量算法
shardingAlgorithms: use_VOLUME_RANGE: type: VOLUME_RANGE props: range-lower: '20000000' #最小值 range-upper: '40000000' #最大值 # 分片的区间的数据的间隔 sharding-volume: '20000000' #备注 最小值为2000万，也就是说表数据量小于等于2000万，最大数量为4000万 表与表的间隔为2000万 比如说分了两张表： 1-2000万 存到表0 2001万-4000万 存到表1 是根据分表的数量来定义最大值的 分了三张表，那最大值为6000万HASH-CODE算法 【如果分片键是字符串类型，需要这种算法分表】
shardingAlgorithms: use_HASH_MOD: type: HASH_MOD props: sharding-count: '2' #分表数量，单引号必须要加根据时间分表算法
shardingAlgorithms: use_AUTO_INTERVAL: type: AUTO_INTERVAL props: datetime-lower: '2020-01-01 23:59:59' datetime-upper: '2022-12-31 23:59:59' # 以1年度为单位进行划分 sharding-seconds: '31536000' # 以1个月为单位进行划分 #sharding-seconds: '2678400' # 以1天为单位进行划分 #sharding-seconds: '86400' #设置的最大值必须和分多少表匹配才行，否者报错，找不到表
分布式ID
config-sharding.yaml
# 3、创建客户端连接库 schemaName: hmms #1、连接mysql dataSources: hmmsdatasources-0: url: jdbc:mysql://localhost:3306/hmms?serverTimezone=UTC&useSSL=false username: root password: 1QAZ2WSX3EDC connectionTimeoutMilliseconds: 30000 idleTimeoutMilliseconds: 60000 maxLifetimeMilliseconds: 1800000 maxPoolSize: 50 minPoolSize: 1 # 2、分片规则 rules: - !SHARDING tables: user: actualDataNodes: hmmsdatasources-0.user-${0..1} tableStrategy: standard: shardingColumn: id shardingAlgorithmName: use_HASH_MOD keyGenerateStrategy: column: id keyGeneratorName: snowflake shardingAlgorithms: use_MOD: type: MOD props: sharding-count: 2 use_HASH_MOD: type: HASH_MOD props: sharding-count: '2' keyGenerators: snowflake: type: SNOWFLAKE props: worker-id: 123表结构sql语句
SET NAMES utf8mb4; SET FOREIGN_KEY_CHECKS = 0; -- ---------------------------- -- Table structure for user -- ---------------------------- DROP TABLE IF EXISTS `user`; CREATE TABLE `user` ( `id` varchar(100), `useid` int(11) NOT NULL, `usenam` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT '登录名', `usepwd` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '登录密码', `usestate` int(11) NULL DEFAULT 2 COMMENT '-1：删除1：注销 2：正常 3：挂失', `usekey` varchar(100) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户秘钥', `usetel` varchar(11) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '用户手机', `createbyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '添加人', `createbytime` datetime(0) NULL DEFAULT NULL COMMENT '添加时间', `modifybyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '修改人', `modifybytime` datetime(0) NULL DEFAULT NULL COMMENT '修改时间', PRIMARY KEY (`useid`) USING BTREE ) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic; SET FOREIGN_KEY_CHECKS = 1;数据填充语句
INSERT INTO `user`(useid,usenam,usepwd,usestate,usekey,usetel,createbyid,createbytime,modifybyid,modifybytime) VALUES (1, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);执行结构如下：
