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。
主要功能如下:
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。
使用:
| 依赖导入
Spring Boot 引入自动依赖注解包:
- <dependency>
- <groupId>com.baomidou</groupId>
- <artifactId>mybatis-mate-starter</artifactId>
- <version>1.0.8</version>
- </dependency>
注解(实体分包使用):
- <dependency>
- <groupId>com.baomidou</groupId>
- <artifactId>mybatis-mate-annotation</artifactId>
- <version>1.0.8</version>
- </dependency>
| 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。
- @Component
- public class DataDict implements IDataDict {
-
- /**
- * 从数据库或缓存中获取
- */
- private Map<String, String> SEX_MAP = new ConcurrentHashMap<String, String>() {{
- put("0", "女");
- put("1", "男");
- }};
-
- @Override
- public String getNameByCode(FieldDict fieldDict, String code) {
- System.err.println("字段类型:" + fieldDict.type() + ",编码:" + code);
- return SEX_MAP.get(code);
- }
- }
| 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;
| 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。
- @Configuration
- public class SensitiveStrategyConfig {
-
- /**
- * 注入脱敏策略
- */
- @Bean
- public 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
- */
- @RestController
- public class ArticleController {
- @Autowired
- private 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);
- }
- }
| 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。
- @Component
- public class PostgresDdl implements IDdl {
-
- /**
- * 执行 SQL 脚本方式
- */
- @Override
- public List<String> getSqlFiles() {
- return Arrays.asList(
- // 内置包方式
- "db/tag-schema.sql",
- // 文件绝对路径方式
- "D:\\db\\tag-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;\n" +
- "INSERT INTO user (id, username, password, sex, email) VALUES\n" +
- "(20, 'Duo', '123456', 0, 'Duo@baomidou.com');"));
它还支持多数据源执行!!!
- @Component
- public class MysqlDdl implements IDdl {
-
- @Override
- public void sharding(Consumer<IDdl> 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
- */
- @Override
- public List<String> getSqlFiles() {
- return Arrays.asList("db/user-mysql.sql");
- }
- }
| 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<User> {
-
- @Sharding("postgres")
- Long selectByUsername(String username);
- }
你也可以自定义策略统一调兵遣将:
- @Component
- public 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}
- */
- @Override
- public 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: node2
- cluster: 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
- ...
| 分布式事务日志打印
部分配置如下:
- /**
- * <p>
- * 性能分析拦截器,用于输出每条 SQL 语句及其执行时间
- * </p>
- */
- @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<br>
- * true 写入日志文件,不阻断程序执行!<br>
- * 超过设定的最大执行时长异常提示!
- */
- private boolean writeInLog = false;
-
- @Override
- public 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")) {//Hikari
- try {
- 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("\n Execute SQL:").append(sqlFormat(originalSql, format)).append("\n");
- 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;
- }
-
- @Override
- public Object plugin(Object target) {
- if (target instanceof StatementHandler) {
- return Plugin.wrap(target, this);
- }
- return target;
- }
-
- @Override
- public 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<Integer> 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<Integer> 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
- @AllArgsConstructor
- public 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);
- }
- }
| 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<User> selectTestList(IPage<User> page, Long id, @Param("name") String username);
模拟业务处理逻辑:
- @Bean
- public IDataScopeProvider dataScopeProvider() {
- return new AbstractDataScopeProvider() {
- @Override
- protected 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<DataColumnProperty> 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<String> 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 u
- WHERE (u.department_id IN ('1', '2', '3', '5'))
- AND u.mobile LIKE '%1533%' LIMIT 1, 10