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一、简述
- 简述
ShardingSphere-Proxy4.0 曾经降级到 5.0 了,然而两者的配置文件还有肯定的差异的,这篇文章讲述的就是 ShardingSphere-Proxy 5.0 的落地。概念、分表、分库、分库分表的原理的根本和 4.0 一样的,须要理解可查看 https://blog.csdn.net/Fu_Shi_…。 - 开发者文档
https://shardingsphere.apache…
二、ShardingSphere-Proxy5.0 落地
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环境
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JAVA JDK 下载
https://pan.baidu.com/s/1A-ksNN0YicT3hXjFscGGwA 提取码:r9e0
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JDBC 数据连贯驱动下载
https://pan.baidu.com/s/1924iUe7wxGpStAzxxv2K3g 提取码:jy7z
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ShardingSphere-Proxy 5.0 下载、
https://archive.apache.org/dist/shardingsphere/5.0.0/
- Window 11
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落地
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条件
- 实在数据库
- 逻辑数据库
- ShardingSphere-Proxy5.0 配置文件
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步骤
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新建实在数据库和表【hmms.user 表为例】
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数据库表构造语句
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 '登录明码', `usestate` int(11) NULL DEFAULT 2 COMMENT '-1:删除 1:登记 2:失常 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 '增加人', `createbytime` datetime(0) NULL DEFAULT NULL COMMENT '增加工夫', `modifybyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '批改人', `modifybytime` datetime(0) NULL DEFAULT NULL COMMENT '批改工夫', PRIMARY KEY (`useid`) USING BTREE ) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic; SET FOREIGN_KEY_CHECKS = 1;
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运行后果如下:
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2. 批改 ShardingSphere-Proxy5.0 配置文件,并连贯
config-sharding.yaml
```
# 3、创立客户端连贯库
schemaName: hmms
#1、连贯 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、分片规定
rules:
- !SHARDING
tables:
user: #表名
actualDataNodes: hmmsdatasources-0.user-${0..1} #分表规定
tableStrategy:
standard:
shardingColumn: useid #分片键
shardingAlgorithmName: use_MOD #分表算法
shardingAlgorithms: #分表算法
use_MOD: #取模算法
type: MOD
props:
sharding-count: 2
```
server.yaml
```
rules:
- !AUTHORITY
users:
- root@%:*****
- sharding@:sharding
provider:
type: ALL_PRIVILEGES_PERMITTED
```
运行命令
```
#在 ShardingSphere-Proxy bin
start.bat 端口号
```
运行后果如下:![在这里插入图片形容](https://img-blog.csdnimg.cn/8d7b5ca3c7e84edb927779bcc84da367.png?x-oss-process=image/watermark,type_d3F5LXplbmhlaQ,shadow_50,text_Q1NETiBAQEDnpZ7lhpw=,size_20,color_FFFFFF,t_70,g_se,x_16#pic_center)
3. 新建逻辑数据连贯,并执行表构造和数据脚本
逻辑库执行后果如下:![在这里插入图片形容](https://img-blog.csdnimg.cn/fcb4986d5c6142b58892c09826ea715e.png#pic_center)
逻辑数据库增加两条数据
SQL 语句
```
INSERT INTO `user` VALUES (1, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);
INSERT INTO `user` VALUES (2, 'admin', '202CB962AC59075B964B07152D234B70', 2, '123', '123123', 'xiaogang', '2021-08-25 20:12:15', 'xiaogang', NULL);
```
执行后果如下:![在这里插入图片形容](https://img-blog.csdnimg.cn/2e27942bdd1b472fb4451ead2f76c133.png#pic_center)
- 分库分表
ShardingSphere-Proxy 5.0 配置
# 3、创立客户端连贯库
schemaName: hmms
#1、连贯 mysql
dataSources:
hmmsdatasources-0:
url: jdbc:mysql:// 主机地址: 端口号 /hmms-0?serverTimezone=UTC&useSSL=false
username: root
password: 明码
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
hmmsdatasources-1:
url: jdbc:mysql:// 主机地址: 端口号 /hmms-1?serverTimezone=UTC&useSSL=false
username: root
password: 明码
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 50
minPoolSize: 1
# 2、分片规定
rules:
- !SHARDING
tables:
user:
actualDataNodes: hmmsdatasources-${0..1}.user-${0..1}
tableStrategy:
standard:
shardingColumn: useid
shardingAlgorithmName: use_MOD
databaseStrategy: #分库规定
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
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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统一的
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范畴算法
shardingAlgorithms: use_BOUNDARY_RANGE: type: BOUNDARY_RANGE props: sharding-ranges: 2,100 #多个节点是以逗号宰割 [是依据分的表联合配置节点] #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
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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距离 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 表与表的距离为 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 是依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
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HASH-CODE 算法【如果分片键是字符串类型,须要这种算法分表】
shardingAlgorithms: use_HASH_MOD: type: HASH_MOD props: sharding-count: '2' #分表数量,单引号必须要加
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依据工夫分表算法
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
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分布式 ID
config-sharding.yaml
# 3、创立客户端连贯库 schemaName: hmms #1、连贯 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、分片规定 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
表构造 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 '登录明码', `usestate` int(11) NULL DEFAULT 2 COMMENT '-1:删除 1:登记 2:失常 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 '增加人', `createbytime` datetime(0) NULL DEFAULT NULL COMMENT '增加工夫', `modifybyid` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT '批改人', `modifybytime` datetime(0) NULL DEFAULT NULL COMMENT '批改工夫', 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);
执行构造如下:
正文完