MongoDB中怎么实现关系运算

MongoDB中怎么实现关系运算，针对这个问题，这篇文章详细介绍了相对应的分析和解答，希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。

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在MongoDB里面支持的关系查询操作：大于（$gt），小于（$lt），大于等于（$gte）,小于等于（$lte）,不等于（$ne）,等于（key:value，$eq）。

范例：定义一个员工信息集合
db.emp.drop();
db.emp.insert({"name":"赵一","sex":"男","age":30,"sal":1000,"loc":"北京"});
db.emp.insert({"name":"钱二","sex":"女","age":22,"sal":5000,"loc":"上海"});
db.emp.insert({"name":"孙三","sex":"男","age":40,"sal":2000,"loc":"深圳"});
db.emp.insert({"name":"李四","sex":"女","age":30,"sal":7000,"loc":"北京"});
db.emp.insert({"name":"周五","sex":"女","age":30,"sal":6400,"loc":"北京"});
db.emp.insert({"name":"吴六","sex":"男","age":30,"sal":2500,"loc":"重庆"});
db.emp.insert({"name":"郑七","sex":"女","age":50,"sal":4700,"loc":"成都"});
db.emp.insert({"name":"王八","sex":"男","age":35,"sal":8000,"loc":"北京"});

> db.emp.find().pretty();
{
        "_id" : ObjectId("599108423268c8e84253be26"),
        "name" : "赵一",
        "sex" : "男",
        "age" : 30,
        "sal" : 1000,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be27"),
        "name" : "钱二",
        "sex" : "女",
        "age" : 22,
        "sal" : 5000,
        "loc" : "上海"
}
{
        "_id" : ObjectId("599108423268c8e84253be28"),
        "name" : "孙三",
        "sex" : "男",
        "age" : 40,
        "sal" : 2000,
        "loc" : "深圳"
}
{
        "_id" : ObjectId("599108423268c8e84253be29"),
        "name" : "李四",
        "sex" : "女",
        "age" : 30,
        "sal" : 7000,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be2a"),
        "name" : "周五",
        "sex" : "女",
        "age" : 30,
        "sal" : 6400,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be2b"),
        "name" : "吴六",
        "sex" : "男",
        "age" : 30,
        "sal" : 2500,
        "loc" : "重庆"
}
{
        "_id" : ObjectId("599108423268c8e84253be2c"),
        "name" : "郑七",
        "sex" : "女",
        "age" : 50,
        "sal" : 4700,
        "loc" : "成都"
}
{
        "_id" : ObjectId("599108433268c8e84253be2d"),
        "name" : "王八",
        "sex" : "男",
        "age" : 35,
        "sal" : 8000,
        "loc" : "北京"
}

范例：查询姓名为孙三的信息
> db.emp.find({"name":"孙三"}).pretty();
{
        "_id" : ObjectId("599108423268c8e84253be28"),
        "name" : "孙三",
        "sex" : "男",
        "age" : 40,
        "sal" : 2000,
        "loc" : "深圳"
}

范例：查询性别为男的人员信息
> db.emp.find({"sex":"男"}).pretty();
{
        "_id" : ObjectId("599108423268c8e84253be26"),
        "name" : "赵一",
        "sex" : "男",
        "age" : 30,
        "sal" : 1000,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be28"),
        "name" : "孙三",
        "sex" : "男",
        "age" : 40,
        "sal" : 2000,
        "loc" : "深圳"
}
{
        "_id" : ObjectId("599108423268c8e84253be2b"),
        "name" : "吴六",
        "sex" : "男",
        "age" : 30,
        "sal" : 2500,
        "loc" : "重庆"
}
{
        "_id" : ObjectId("599108433268c8e84253be2d"),
        "name" : "王八",
        "sex" : "男",
        "age" : 35,
        "sal" : 8000,
        "loc" : "北京"
}

范例：查询年龄大于30的人员
> db.emp.find({"age":{"$gt":30}}).pretty();
{
        "_id" : ObjectId("599108423268c8e84253be28"),
        "name" : "孙三",
        "sex" : "男",
        "age" : 40,
        "sal" : 2000,
        "loc" : "深圳"
}
{
        "_id" : ObjectId("599108423268c8e84253be2c"),
        "name" : "郑七",
        "sex" : "女",
        "age" : 50,
        "sal" : 4700,
        "loc" : "成都"
}
{
        "_id" : ObjectId("599108433268c8e84253be2d"),
        "name" : "王八",
        "sex" : "男",
        "age" : 35,
        "sal" : 8000,
        "loc" : "北京"
}

范例：查询薪水大于等于4700的人员
> db.emp.find({"sal":{"$gte":4700}}).pretty();
{
        "_id" : ObjectId("599108423268c8e84253be27"),
        "name" : "钱二",
        "sex" : "女",
        "age" : 22,
        "sal" : 5000,
        "loc" : "上海"
}
{
        "_id" : ObjectId("599108423268c8e84253be29"),
        "name" : "李四",
        "sex" : "女",
        "age" : 30,
        "sal" : 7000,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be2a"),
        "name" : "周五",
        "sex" : "女",
        "age" : 30,
        "sal" : 6400,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be2c"),
        "name" : "郑七",
        "sex" : "女",
        "age" : 50,
        "sal" : 4700,
        "loc" : "成都"
}
{
        "_id" : ObjectId("599108433268c8e84253be2d"),
        "name" : "王八",
        "sex" : "男",
        "age" : 35,
        "sal" : 8000,
        "loc" : "北京"
}

范例：查询姓名不是孙三的信息
> db.emp.find({"name":{"$ne":"孙三"}}).pretty();
{
        "_id" : ObjectId("599108423268c8e84253be26"),
        "name" : "赵一",
        "sex" : "男",
        "age" : 30,
        "sal" : 1000,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be27"),
        "name" : "钱二",
        "sex" : "女",
        "age" : 22,
        "sal" : 5000,
        "loc" : "上海"
}
{
        "_id" : ObjectId("599108423268c8e84253be29"),
        "name" : "李四",
        "sex" : "女",
        "age" : 30,
        "sal" : 7000,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be2a"),
        "name" : "周五",
        "sex" : "女",
        "age" : 30,
        "sal" : 6400,
        "loc" : "北京"
}
{
        "_id" : ObjectId("599108423268c8e84253be2b"),
        "name" : "吴六",
        "sex" : "男",
        "age" : 30,
        "sal" : 2500,
        "loc" : "重庆"
}
{
        "_id" : ObjectId("599108423268c8e84253be2c"),
        "name" : "郑七",
        "sex" : "女",
        "age" : 50,
        "sal" : 4700,
        "loc" : "成都"
}
{
        "_id" : ObjectId("599108433268c8e84253be2d"),
        "name" : "王八",
        "sex" : "男",
        "age" : 35,
        "sal" : 8000,
        "loc" : "北京"
此时与之前最大的区别就在于，在一个JSON结构里面需要定义其他的JSON结构，并且这种风格在进行程序操作的时候依然如此。

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