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。
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>
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);
}
}
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;
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);
}
}
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");
}
}
@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
...
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);
}
}
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
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-examples
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