Java的ORM框架有很多,但由于Java语言的限制大部分都不够优雅也不够简单,所以作者只能另辟蹊径造*了。照旧先看示例代码了解个大概,然后再解释实现原理。
一、ORM示例
1. Insert
public CompletableFuture<Void> insert() {
var obj = new sys.entities.Demo("MyName"); //构造参数为主键
obj.Age = 100; //设置实体属性的值
return obj.saveAsync();
}
2. Update
- 更新单个实体(必须具备主键)
public CompletableFuture<Void> update(sys.entities.Demo obj) {
obj.Age = 200;
return obj.saveAsync();
}
- 根据条件更新(必须指定条件以防误操作)
public CompletableFuture<?> update() {
var cmd = new SqlUpdateCommand<sys.entities.Demo>();
cmd.update(e -> e.City = "Wuxi"); //更新字段
cmd.update(e -> e.Age = e.Age + 1); //更新累加字段
cmd.where(e -> e.Name == "Johne"); //更新的条件
var outs = cmd.output(e -> e.Age); //更新的同时返回指定字段
return cmd.execAsync().thenApply(rows -> {
System.out.println("更新记录数: " + rows);
System.out.println("返回的值: " + outs.get(0));
return "Done.";
});
}
3. Delete
- 删除单个实体(必须具备主键)
public CompletableFuture<Void> update(sys.entities.Demo obj) {
obj.markDeleted(); //先标记为删除状态
return obj.saveAsync(); //再调用保存方法
}
- 根据条件删除(必须指定条件以防误操作)
public CompletableFuture<?> delete() {
var cmd = new SqlDeleteCommand<sys.entities.Demo>();
cmd.where(e -> e.Age < 0 || e.Age > 200);
return cmd.execAsync();
}
4. Transaction
由于作者讨厌隐式事务,所以事务命令必须显式指定。
public CompletableFuture<?> transaction() {
var obj1 = new sys.entities.Demo("Demo1");
obj1.Age = 11;
var obj2 = new sys.entities.Demo("Demo2");
obj2.Age = 22;
return DataStore.DemoDB.beginTransaction().thenCompose(txn -> { //开始事务
return obj1.saveAsync(txn) //事务保存obj1
.thenCompose(r -> obj2.saveAsync(txn)) //事务保存obj2
.thenCompose(r -> txn.commitAsync()); //递交事务
}).thenApply(r -> "Done");
}
5. Sql查询
- Where条件
public CompletableFuture<?> query(String key) {
var q = new SqlQuery<sys.entities.Demo>();
q.where(e -> e.Age > 10 && e.Age < 80);
if (key != null)
q.andWhere(e -> e.Name.contains(key)); //拼接条件
return q.toListAsync(); //返回List<sys.entities.Demo>
}
- 分页查询
public CompletableFuture<?> query(int pageSize, int pageIndex) {
var q = new SqlQuery<sys.entities.Demo>();
return q.skip(pageSize * pageIndex)
.take(pageSize)
.toListAsync();
}
- 结果映射至匿名类
public CompletableFuture<?> query() {
var q = new SqlQuery<sys.entities.Demo>();
return q.toListAsync(e -> new Object() { //返回List<匿名类>
public final String Name = e.Name; //匿名类属性 = 实体属性表达式
public final int Age = e.Age + 10;
public final String Father = e.Parent.Name;
}).thenApply(appbox.data.JsonResult::new);
}
- 结果映射至继承的匿名类
public CompletableFuture<?> query() {
var q = new SqlQuery<sys.entities.Demo>();
q.where(e -> e.Parent.Name == "Rick");
return q.toListAsync(e -> new sys.entities.Demo() { //返回List<? extens Demo>
public final String Father = e.Parent.Name;
});
}
- 结果映射至树状结构列表
public CompletableFuture<?> tree() {
var q = new SqlQuery<sys.entities.Demo>();
q.where(t -> t.Name == "Rick");
return q.toTreeAsync(t -> t.Childs); //参数指向EntitySet(一对多成员)
}
- EntityRef(一对一引用的实体成员)自动Join
public CompletableFuture<?> query() {
var q = new SqlQuery<sys.entities.Customer>();
q.where(cus -> cus.City.Name == "Wuxi");
return q.toListAsync();
}
生成的Sql:
Select t.* From "Customer" t Left Join "City" j1 On j1."Code"=t."CityCode"
- 手工指定Join
public CompletableFuture<?> join() {
var q = new SqlQuery<sys.entities.Customer>();
var j = new SqlQueryJoin<sys.entities.City>();
q.leftJoin(j, (cus, city) -> cus.CityCode == city.Code);
q.where(j, (cus, city) -> city.Name == "Wuxi");
return q.toListAsync();
}
- 子查询
public CompletableFuture<?> subQuery() {
var sq = new SqlQuery<sys.entities.Demo>();
sq.where(s -> s.ParentName == "Rick");
var q = new SqlQuery<sys.entities.Demo>();
q.where(t -> DbFunc.in(t.Name, sq.toSubQuery(s -> s.Name)));
return q.toListAsync();
}
- GroupBy
public CompletableFuture<?> groupBy() {
var q = new SqlQuery<sys.entities.Demo>();
q.groupBy(t -> t.ParentName) //多个可重复
.having(t -> DbFunc.sum(t.Age) > 10);
return q.toListAsync(t -> new Object() {
public final String group = t.ParentName == null ? "可怜的孩子" : t.ParentName;
public final int totals = DbFunc.sum(t.Age);
}).thenApply(appbox.data.JsonResult::new);
}
二、实现原理
其实以上的示例代码并非最终运行的代码,作者利用Eclipse jdt将上述代码在编译发布服务模型时分析转换为最终的运行代码,具体过程如下:
1. jdt分析服务虚拟代码生成AST抽象语法树;
2. 遍历AST树,将实体对象的读写属性改写为getXXX(), setXXX();
var name = obj.Name; //读实体属性
obj.Name = "Rick"; //写实体属性
改写为:
var name = obj.getName();
obj.setName("Rick");
3. 遍历AST树,将查询相关方法的参数转换为运行时表达式;
public CompletableFuture<?> query(String key) {
var q = new SqlQuery<sys.entities.Employee>();
q.where(e -> e.Manager.Name + "a" == key + "b");
return q.toListAsync();
}
转换为:
public CompletableFuture<?> query(String key) {
var q = new appbox.store.query.SqlQuery<>(-7018111290459553788L, SYS_Employee.class);
q.where(e -> e.m("Manager").m("Name").plus("a").eq(key + "b"));
return q.toListAsync();
}
4. 根据服务模型使用到的实体模型生成相应实体的运行时代码;
5. 最后编译打包服务模型的字节码。
以上请参考源码的ServiceCodeGenerator及EntityCodeGenerator类。
三、性能与小结
作者写了个简单查询的服务,测试配置为MacBook主机(wrk压测 + 数据库)->4核I7虚拟机(服务端),测试结果如下所示qps可达1万,已包括实体映射转换及序列化传输等所有开销。这里顺便提一下,由于框架是全异步的,所以没有使用传统的JDBC驱动,而是使用了jasync-sql(底层为Netty)来驱动数据库。
wrk -c200 -t2 -d20s -s post_bin.lua http://10.211.55.8:8000/api
Running 20s test @ http://10.211.55.8:8000/api
2 threads and 200 connections
Thread Stats Avg Stdev Max +/- Stdev
Latency 18.97ms 5.84ms 89.15ms 81.55%
Req/Sec 5.32k 581.92 6.48k 65.00%
211812 requests in 20.02s, 36.76MB read
Requests/sec: 10578.90
Transfer/sec: 1.84MB
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