——————————————
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這一列
MySql:
ALTER TABLE user ... 
Mongo:
db.user.insert({ 'name' : 'foobar' , 'age' : 25 , 'email' : 'foo@bar.com' })
——————————————
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  // 即時加上了列篩選，_id也會返回；必須顯式的阻止_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 // 如果直接通過find({"username" : null})進行查詢，那么連帶"沒有username"的紀(jì)錄一并篩選出來

db.users.find({"name" : /joey?/i}) // 正則查詢，value是符合PCRE的表達式

db.food.find({fruit : {$all : ["apple", "banana"]}}) // 對數(shù)組的查詢, 字段fruit中，既包含"apple",又包含"banana"的紀(jì)錄

db.food.find({"fruit.2" : "peach"}) // 對數(shù)組的查詢, 字段fruit中，第3個(從0開始)元素是peach的紀(jì)錄

db.food.find({"fruit" : {"$size" : 3}}) // 對數(shù)組的查詢, 查詢數(shù)組元素個數(shù)是3的記錄，$size前面無法和其他的操作符復(fù)合使用

db.users.findOne(criteria, {"comments" : {"$slice" : 10}}) // 對數(shù)組的查詢，只返回數(shù)組comments中的前十條，還可以{"$slice" : -10}， {"$slice" : [23, 10]}; 分別返回最后10條，和中間10條

db.people.find({"name.first" : "Joe", "name.last" : "Schmoe"})  // 嵌套查詢

db.blog.find({"comments" : {"$elemMatch" : {"author" : "joe", "score" : {"$gte" : 5}}}}) // 嵌套查詢，僅當(dāng)嵌套的元素是數(shù)組時使用,

db.foo.find({"$where" : "this.x + this.y == 10"}) // 復(fù)雜的查詢，$where當(dāng)然是非常方便的，但效率低下。對于復(fù)雜查詢，考慮的順序應(yīng)當(dāng)是 正則 -> MapReduce -> $where

db.foo.find({"$where" : "function() { return this.x + this.y == 10; }"}) // $where可以支持javascript函數(shù)作為查詢條件

db.foo.find().sort({"x" : 1}).limit(1).skip(10); // 返回第(10, 11]條，按"x"進行排序; 三個limit的順序是任意的，應(yīng)該盡量避免skip中使用large-number