MyBatisPlus又在搞事了！发布神器，一个依赖轻松搞定权限问题

今天介绍一个 MyBatis – Plus 官方发布的神器：mybatis-mate 为 mp 企业级模块，支持分库分表，数据审计、数据敏感词过滤（AC算法），字段加密，字典回写（数据绑定），数据权限，表结构自动生成 SQL 维护等，旨在更敏捷优雅处理数据。

1. 主要功能

• 字典绑定
• 字段加密
• 数据脱敏
• 表结构动态维护
• 数据审计记录
• 数据范围（数据权限）
• 数据库分库分表、动态据源、读写分离、数- – 据库健康检查自动切换。

2.使用

2.1 依赖导入

Spring Boot 引入自动依赖注解包

com.baomidoumybatis-mate-starter1.0.8

注解（实体分包使用）

com.baomidoumybatis-mate-annotation1.0.8

2.2 字段数据绑定（字典回写）

例如 user_sex 类型 sex 字典结果映射到 sexText 属性

@FieldDict(type = “user_sex”, target = “sexText”)private Integer sex;private String sexText;

实现 IDataDict 接口提供字典数据源，注入到 Spring 容器即可。

@Componentpublic class DataDict implements IDataDict {/*** 从数据库或缓存中获取*/private Map SEX_MAP = new ConcurrentHashMap() {{put(“0”, “女”);put(“1”, “男”);}};@Overridepublic String getNameByCode(FieldDict fieldDict, String code) {System.err.println(“字段类型：” + fieldDict.type() + “，编码：” + code);return SEX_MAP.get(code);}}

2.3 字段加密

属性 @FieldEncrypt 注解即可加密存储，会自动解密查询结果，支持全局配置加密密钥算法，及注解密钥算法，可以实现 IEncryptor 注入自定义算法。

@FieldEncrypt(algorithm = Algorithm.PBEWithMD5AndDES)private String password;

2.4 字段脱敏

属性 @FieldSensitive 注解即可自动按照预设策略对源数据进行脱敏处理，默认 SensitiveType 内置 9 种常用脱敏策略。

例如：中文名、银行卡账号、手机号码等 脱敏策略。也可以自定义策略如下：

@FieldSensitive(type = “testStrategy”)private String username;@FieldSensitive(type = SensitiveType.mobile)private String mobile;

自定义脱敏策略 testStrategy 添加到默认策略中注入 Spring 容器即可。

@Configurationpublic class SensitiveStrategyConfig {/*** 注入脱敏策略*/@Beanpublic ISensitiveStrategy sensitiveStrategy() {// 自定义 testStrategy 类型脱敏处理return new SensitiveStrategy().addStrategy(“testStrategy”, t -> t + “***test***”);}}

例如：文章敏感词过滤

/*** 演示文章敏感词过滤*/@RestControllerpublic class ArticleController {@Autowiredprivate SensitiveWordsMapper sensitiveWordsMapper;// 测试访问下面地址观察请求地址、界面返回数据及控制台（ 普通参数 ）// 无敏感词 http://localhost:8080/info?content=tom&see=1&age=18// 英文敏感词 http://localhost:8080/info?content=my%20content%20is%20tomcat&see=1&age=18// 汉字敏感词 http://localhost:8080/info?content=%E7%8E%8B%E5%AE%89%E7%9F%B3%E5%94%90%E5%AE%8B%E5%85%AB%E5%A4%A7%E5%AE%B6&see=1// 多个敏感词 http://localhost:8080/info?content=%E7%8E%8B%E5%AE%89%E7%9F%B3%E6%9C%89%E4%B8%80%E5%8F%AA%E7%8C%ABtomcat%E6%B1%A4%E5%A7%86%E5%87%AF%E7%89%B9&see=1&size=6// 插入一个字变成非敏感词 http://localhost:8080/info?content=%E7%8E%8B%E7%8C%AB%E5%AE%89%E7%9F%B3%E6%9C%89%E4%B8%80%E5%8F%AA%E7%8C%ABtomcat%E6%B1%A4%E5%A7%86%E5%87%AF%E7%89%B9&see=1&size=6@GetMapping(“/info”)public String info(Article article) throws Exception {return ParamsConfig.toJson(article);}// 添加一个敏感词然后再去观察是否生效 http://localhost:8080/add// 观察【猫】这个词被过滤了 http://localhost:8080/info?content=%E7%8E%8B%E5%AE%89%E7%9F%B3%E6%9C%89%E4%B8%80%E5%8F%AA%E7%8C%ABtomcat%E6%B1%A4%E5%A7%86%E5%87%AF%E7%89%B9&see=1&size=6// 嵌套敏感词处理 http://localhost:8080/info?content=%E7%8E%8B%E7%8C%AB%E5%AE%89%E7%9F%B3%E6%9C%89%E4%B8%80%E5%8F%AA%E7%8C%ABtomcat%E6%B1%A4%E5%A7%86%E5%87%AF%E7%89%B9&see=1&size=6// 多层嵌套敏感词 http://localhost:8080/info?content=%E7%8E%8B%E7%8E%8B%E7%8C%AB%E5%AE%89%E7%9F%B3%E5%AE%89%E7%9F%B3%E6%9C%89%E4%B8%80%E5%8F%AA%E7%8C%ABtomcat%E6%B1%A4%E5%A7%86%E5%87%AF%E7%89%B9&see=1&size=6@GetMapping(“/add”)public String add() throws Exception {Long id = 3L;if (null == sensitiveWordsMapper.selectById(id)) {System.err.println(“插入一个敏感词：” + sensitiveWordsMapper.insert(new SensitiveWords(id, “猫”)));// 插入一个敏感词，刷新算法引擎敏感词SensitiveWordsProcessor.reloadSensitiveWords();}return “ok”;}// 测试访问下面地址观察控制台（ 请求json参数 ）// idea 执行 resources 目录 TestJson.http 文件测试@PostMapping(“/json”)public String json(@RequestBody Article article) throws Exception {return ParamsConfig.toJson(article);}}

2.5 DDL 数据结构自动维护

解决升级表结构初始化，版本发布更新 SQL 维护问题，目前支持 MySql、PostgreSQL。

@Componentpublic class PostgresDdl implements IDdl {/*** 执行 SQL 脚本方式*/@Overridepublic List getSqlFiles() {return Arrays.asList(// 内置包方式”db/tag-schema.sql”,// 文件绝对路径方式”D:dbtag-data.sql”);}}

不仅仅可以固定执行，也可以动态执行！！

ddlScript.run(new StringReader(“DELETE FROM user;” +”INSERT INTO user (id, username, password, sex, email) VALUES” +”(20, ‘Duo’, ‘123456’, 0, ‘Duo@baomidou.com’);”));

它还支持多数据源执行！！！

@Componentpublic class MysqlDdl implements IDdl {@Overridepublic void sharding(Consumer consumer) {// 多数据源指定，主库初始化从库自动同步String group = “mysql”;ShardingGroupProperty sgp = ShardingKey.getDbGroupProperty(group);if (null != sgp) {// 主库sgp.getMasterKeys().forEach(key -> {ShardingKey.change(group + key);consumer.accept(this);});// 从库sgp.getSlaveKeys().forEach(key -> {ShardingKey.change(group + key);consumer.accept(this);});}}/*** 执行 SQL 脚本方式*/@Overridepublic List getSqlFiles() {return Arrays.asList(“db/user-mysql.sql”);}}

2.6 动态多数据源主从自由切换

@Sharding 注解使数据源不限制随意使用切换，你可以在 mapper 层添加注解，按需求指哪打哪！！

@Mapper@Sharding(“mysql”)public interface UserMapper extends BaseMapper {@Sharding(“postgres”)Long selectByUsername(String username);}

你也可以自定义策略统一调兵遣将

@Componentpublic class MyShardingStrategy extends RandomShardingStrategy {/*** 决定切换数据源 key {@link ShardingDatasource}** @param group 动态数据库组* @param invocation {@link Invocation}* @param sqlCommandType {@link SqlCommandType}*/@Overridepublic void determineDatasourceKey(String group, Invocation invocation, SqlCommandType sqlCommandType) {// 数据源组 group 自定义选择即可， keys 为数据源组内主从多节点，可随机选择或者自己控制this.changeDatabaseKey(group, sqlCommandType, keys -> chooseKey(keys, invocation));}}

可以开启主从策略，当然也是可以开启健康检查！具体配置：

mybatis-mate:sharding:health: true # 健康检测primary: mysql # 默认选择数据源datasource:mysql: # 数据库组- key: node1…- key: node2cluster: slave # 从库读写分离时候负责 sql 查询操作，主库 master 默认可以不写…postgres:- key: node1 # 数据节点…

2.7 分布式事务日志打印

部分配置如下：

/***

* 性能分析拦截器，用于输出每条 SQL 语句及其执行时间*

*/@Slf4j@Component@Intercepts({@Signature(type = StatementHandler.class, method = “query”, args = {Statement.class, ResultHandler.class}),@Signature(type = StatementHandler.class, method = “update”, args = {Statement.class}),@Signature(type = StatementHandler.class, method = “batch”, args = {Statement.class})})public class PerformanceInterceptor implements Interceptor {/*** SQL 执行最大时长，超过自动停止运行，有助于发现问题。*/private long maxTime = 0;/*** SQL 是否格式化*/private boolean format = false;/*** 是否写入日志文件* true 写入日志文件，不阻断程序执行！* 超过设定的最大执行时长异常提示！*/private boolean writeInLog = false;@Overridepublic Object intercept(Invocation invocation) throws Throwable {Statement statement;Object firstArg = invocation.getArgs()[0];if (Proxy.isProxyClass(firstArg.getClass())) {statement = (Statement) SystemMetaObject.forObject(firstArg).getValue(“h.statement”);} else {statement = (Statement) firstArg;}MetaObject stmtMetaObj = SystemMetaObject.forObject(statement);try {statement = (Statement) stmtMetaObj.getValue(“stmt.statement”);} catch (Exception e) {// do nothing}if (stmtMetaObj.hasGetter(“delegate”)) {//Hikaritry {statement = (Statement) stmtMetaObj.getValue(“delegate”);} catch (Exception e) {}}String originalSql = null;if (originalSql == null) {originalSql = statement.toString();}originalSql = originalSql.replaceAll(“[s]+”, ” “);int index = indexOfSqlStart(originalSql);if (index > 0) {originalSql = originalSql.substring(index);}// 计算执行 SQL 耗时long start = SystemClock.now();Object result = invocation.proceed();long timing = SystemClock.now() – start;// 格式化 SQL 打印执行结果Object target = PluginUtils.realTarget(invocation.getTarget());MetaObject metaObject = SystemMetaObject.forObject(target);MappedStatement ms = (MappedStatement) metaObject.getValue(“delegate.mappedStatement”);StringBuilder formatSql = new StringBuilder();formatSql.append(” Time：”).append(timing);formatSql.append(” ms – ID：”).append(ms.getId());formatSql.append(” Execute SQL：”).append(sqlFormat(originalSql, format)).append(“”);if (this.isWriteInLog()) {if (this.getMaxTime() >= 1 && timing > this.getMaxTime()) {log.error(formatSql.toString());} else {log.debug(formatSql.toString());}} else {System.err.println(formatSql);if (this.getMaxTime() >= 1 && timing > this.getMaxTime()) {throw new RuntimeException(” The SQL execution time is too large, please optimize ! “);}}return result;}@Overridepublic Object plugin(Object target) {if (target instanceof StatementHandler) {return Plugin.wrap(target, this);}return target;}@Overridepublic void setProperties(Properties prop) {String maxTime = prop.getProperty(“maxTime”);String format = prop.getProperty(“format”);if (StringUtils.isNotEmpty(maxTime)) {this.maxTime = Long.parseLong(maxTime);}if (StringUtils.isNotEmpty(format)) {this.format = Boolean.valueOf(format);}}public long getMaxTime() {return maxTime;}public PerformanceInterceptor setMaxTime(long maxTime) {this.maxTime = maxTime;return this;}public boolean isFormat() {return format;}public PerformanceInterceptor setFormat(boolean format) {this.format = format;return this;}public boolean isWriteInLog() {return writeInLog;}public PerformanceInterceptor setWriteInLog(boolean writeInLog) {this.writeInLog = writeInLog;return this;}public Method getMethodRegular(Class clazz, String methodName) {if (Object.class.equals(clazz)) {return null;}for (Method method : clazz.getDeclaredMethods()) {if (method.getName().equals(methodName)) {return method;}}return getMethodRegular(clazz.getSuperclass(), methodName);}/*** 获取sql语句开头部分** @param sql* @return*/private int indexOfSqlStart(String sql) {String upperCaseSql = sql.toUpperCase();Set set = new HashSet();set.add(upperCaseSql.indexOf(“SELECT “));set.add(upperCaseSql.indexOf(“UPDATE “));set.add(upperCaseSql.indexOf(“INSERT “));set.add(upperCaseSql.indexOf(“DELETE “));set.remove(-1);if (CollectionUtils.isEmpty(set)) {return -1;}List list = new ArrayList(set);Collections.sort(list, Integer::compareTo);return list.get(0);}private final static SqlFormatter sqlFormatter = new SqlFormatter();/*** 格式sql** @param boundSql* @param format* @return*/public static String sqlFormat(String boundSql, boolean format) {if (format) {try {return sqlFormatter.format(boundSql);} catch (Exception ignored) {}}return boundSql;}}

使用：

@RestController@AllArgsConstructorpublic class TestController {private BuyService buyService;// 数据库 test 表 t_order 在事务一致情况无法插入数据，能够插入说明多数据源事务无效// 测试访问 http://localhost:8080/test// 制造事务回滚 http://localhost:8080/test?error=true 也可通过修改表结构制造错误// 注释 ShardingConfig 注入 dataSourceProvider 可测试事务无效情况@GetMapping(“/test”)public String test(Boolean error) {return buyService.buy(null != error && error);}}

2.8 数据权限

mapper 层添加注解:

// 测试 test 类型数据权限范围，混合分页模式@DataScope(type = “test”, value = {// 关联表 user 别名 u 指定部门字段权限@DataColumn(alias = “u”, name = “department_id”),// 关联表 user 别名 u 指定手机号字段（自己判断处理）@DataColumn(alias = “u”, name = “mobile”)})@Select(“select u.* from user u”)List selectTestList(IPage page, Long id, @Param(“name”) String username);

模拟业务处理逻辑：

@Beanpublic IDataScopeProvider dataScopeProvider() {return new AbstractDataScopeProvider() {@Overrideprotected void setWhere(PlainSelect plainSelect, Object[] args, DataScopeProperty dataScopeProperty) {// args 中包含 mapper 方法的请求参数，需要使用可以自行获取/*// 测试数据权限，最终执行 SQL 语句SELECT u.* FROM user u WHERE (u.department_id IN (‘1’, ‘2’, ‘3’, ‘5’))AND u.mobile LIKE ‘%1533%’*/if (“test”.equals(dataScopeProperty.getType())) {// 业务 test 类型List dataColumns = dataScopeProperty.getColumns();for (DataColumnProperty dataColumn : dataColumns) {if (“department_id”.equals(dataColumn.getName())) {// 追加部门字段 IN 条件，也可以是 SQL 语句Set deptIds = new HashSet();deptIds.add(“1”);deptIds.add(“2”);deptIds.add(“3”);deptIds.add(“5”);ItemsList itemsList = new ExpressionList(deptIds.stream().map(StringValue::new).collect(Collectors.toList()));InExpression inExpression = new InExpression(new Column(dataColumn.getAliasDotName()), itemsList);if (null == plainSelect.getWhere()) {// 不存在 where 条件plainSelect.setWhere(new Parenthesis(inExpression));} else {// 存在 where 条件 and 处理plainSelect.setWhere(new AndExpression(plainSelect.getWhere(), inExpression));}} else if (“mobile”.equals(dataColumn.getName())) {// 支持一个自定义条件LikeExpression likeExpression = new LikeExpression();likeExpression.setLeftExpression(new Column(dataColumn.getAliasDotName()));likeExpression.setRightExpression(new StringValue(“%1533%”));plainSelect.setWhere(new AndExpression(plainSelect.getWhere(), likeExpression));}}}}};}

最终执行 SQL 输出：

SELECT u.* FROM user uWHERE (u.department_id IN (‘1’, ‘2’, ‘3’, ‘5’))AND u.mobile LIKE ‘%1533%’ LIMIT 1, 10

目前仅有付费版本，了解更多 mybatis-mate 使用示例详见：

https://gitee.com/baomidou/mybatis-mate-example

原文链接：https://mp.weixin.qq.com/s/3Uim4i5YK4QWL4GHiNpjdA