mongodb和mysql语法对比

Posted 2020-09-19 konami

mysql: 
SELECT * FROM user 
Mongo: 
db.user.find() 
—————————————— 
MySQl: 
SELECT * FROM user WHERE name = ‘foobar‘ 
Mongo: 
db.user.find({ ‘name‘ : ‘foobar‘ }) 
—————————————— 
MySql: 
INSERT INTO user (‘name‘,‘age‘) VALUES (‘foobar‘,25) 
Mongo: 
db.user.insert({ ‘name‘ : ‘foobar‘ , ‘age‘ : 25}) 
—————————————— 
如果想增加email这一列 
MySql: 
ALTER TABLE user ... 
Mongo: 
db.user.insert({ ‘name‘ : ‘foobar‘ , ‘age‘ : 25 , ‘email‘ : ‘[email protected]‘ }) 
—————————————— 
MySql: 
DELETE * FROM user 
Mongo: 
db.user.remove({}) 
—————————————— 
MySql: 
DELETE FROM user WHERE age < 30 
Mongo: 
db.user.remove({ ‘age‘ : {$lt : 30}}) 
$gt:> ; $gte:>= ; $lt:< ; $lte:<= ; $ne:!= 
—————————————— 
MySql: 
UPDATE user SET `age` = 36 WHERE `name` = ‘foobar‘ 
Mongo: 
db.user.update({ ‘name‘ : ‘foobar‘} , {$set : { ‘age‘ : 36}}) 
—————————————— 
MySQL: 
UPDATE user SET `age` = ‘age‘ + 3 WHERE `name` = ‘foobar‘ 
Mongo: 
db.user.update({ ‘name‘ : ‘foobar‘} , {$inc : {‘age‘ : 3}}) 
—————————————— 
MySQl: 
SELECT COUNT(*) FROM user WHERE `name` = ‘foobar‘ 
Mongo: 
db.user.find({ ‘name‘ : ‘foobar‘}).count() 
—————————————— 
MySql: 
SELECT * FROM user limit 10,20 
Mongo: 
db.user.find().skip(10).limit(20) 
—————————————— 
MySQl: 
SELECT * FROM user WHERE `age` IN (25,35,45) 
Mongo: 
db.user.find({ ‘age‘ : {$in : [25,35,45]}}) 
—————————————— 
MySql: 
SELECT * FROM user ORDER BY age DESC 
Mongo: 
db.user.find().sort({ ‘age‘ : -1}) 
—————————————— 
MySQL: 
SELECT DISTINCT(name) FROM user WHERE age > 20 
Mongo: 
db.user.distinct( ‘name‘,{‘age‘ : {$lt : 20}}) 
—————————————— 
MySQL: 
SELECT name, sum(marks) FROM  user GROUP BY name 
Mongo: 
db.user.group({ 
key:{‘name‘:true}, 
cond:{‘name‘:‘foo‘}, 
reduce:function(obj,prev){prev.msum += obj.marks;}, 
initial:{msum : 0} 
}) 
—————————————— 
MySQL: 
SELECT name FROM user WHERE age < 20 
Mongo: 
db.user.find(‘this.age < 20‘ , {name : 1})

db.users.find() select * from users
db.users.find({"age" : 27}) select * from users where age = 27
db.users.find({"username" : "joe", "age" : 27}) select * from users where "username" = "joe" and age = 27
db.users.find({}, {"username" : 1, "email" : 1}) select username, email from users
db.users.find({}, {"username" : 1, "_id" : 0}) // no case  // 即时加上了列筛选，_id也会返回；必须显式的阻止_id返回
db.users.find({"age" : {"$gte" : 18, "$lte" : 30}}) select * from users where age >=18 and age <= 30 // $lt(<) $lte(<=) $gt(>) $gte(>=)
db.users.find({"username" : {"$ne" : "joe"}}) select * from users where username <> "joe"
db.users.find({"ticket_no" : {"$in" : [725, 542, 390]}}) select * from users where ticket_no in (725, 542, 390)
db.users.find({"ticket_no" : {"$nin" : [725, 542, 390]}}) select * from users where ticket_no not in (725, 542, 390)
db.users.find({"$or" : [{"ticket_no" : 725}, {"winner" : true}]}) select * form users where ticket_no = 725 or winner = true
db.users.find({"id_num" : {"$mod" : [5, 1]}}) select * from users where (id_num mod 5) = 1
db.users.find({"$not": {"age" : 27}}) select * from users where not (age = 27)
db.users.find({"username" : {"$in" : [null], "$exists" : true}}) select * from users where username is null // 如果直接通过find({"username" : null})进行查询，那么连带"没有username"的纪录一并筛选出来
db.users.find({"name" : /joey?/i}) // 正则查询，value是符合PCRE的表达式
db.food.find({fruit : {$all : ["apple", "banana"]}}) // 对数组的查询, 字段fruit中，既包含"apple",又包含"banana"的纪录
db.food.find({"fruit.2" : "peach"}) // 对数组的查询, 字段fruit中，第3个(从0开始)元素是peach的纪录
db.food.find({"fruit" : {"$size" : 3}}) // 对数组的查询, 查询数组元素个数是3的记录，$size前面无法和其他的操作符复合使用
db.users.findOne(criteria, {"comments" : {"$slice" : 10}}) // 对数组的查询，只返回数组comments中的前十条，还可以{"$slice" : -10}， {"$slice" : [23, 10]}; 分别返回最后10条，和中间10条
db.people.find({"name.first" : "Joe", "name.last" : "Schmoe"})  // 嵌套查询
db.blog.find({"comments" : {"$elemMatch" : {"author" : "joe", "score" : {"$gte" : 5}}}}) // 嵌套查询，仅当嵌套的元素是数组时使用,
db.foo.find({"$where" : "this.x + this.y == 10"}) // 复杂的查询，$where当然是非常方便的，但效率低下。对于复杂查询，考虑的顺序应当是 正则 -> MapReduce -> $where
db.foo.find({"$where" : "function() { return this.x + this.y == 10; }"}) // $where可以支持javascript函数作为查询条件
db.foo.find().sort({"x" : 1}).limit(1).skip(10); // 返回第(10, 11]条，按"x"进行排序; 三个limit的顺序是任意的，应该尽量避免skip中使用large-number