前言:今天在整理笔记的时候发现前段时间处理的MongoDB数据处理的事情,作为一个MySQL DBA,在MySQL的世界里驰骋,却在MongoDB的阴沟里翻了船。
一、MongoDB与MySQL操作对比
MySQL | MongoDB | 说明 |
---|---|---|
mysqld | mongod | 服务器守护进程 |
mysql | mongo | 客户端工具 |
mysqldump | mongodump | 逻辑备份工具 |
mysql | mongorestore | 逻辑恢复工具 |
– | db.repairDatabase() | 修复数据库 |
mysqldump | mongoexport | 数据导出工具 |
source | mongoimport | 数据导入工具 |
grant * privileges on . to … | Db.addUser()Db.auth() | 新建用户并权限 |
show databases | show dbs | 显示库列表 |
Show tables | Show collections | 显示表列表 |
Show slave status | Rs.status | 查询主从状态 |
Create table users(a int, b int) | db.createCollection(“mycoll”, {capped:true,size:100000}) | 创建表,另:可隐式创建表。 |
Create INDEX idxname ON users(name) | db.users.ensureIndex({name:1}) | 创建索引 |
Create INDEX idxname ON users(name,ts DESC) | db.users.ensureIndex({name:1,ts:-1}) | 创建索引 |
Insert into users values(1, 1) | db.users.insert({a:1, b:1}) | 插入记录 |
Select a, b from users | db.users.find({},{a:1, b:1}) | 查询表 |
Select * from users | db.users.find() | 查询表 |
Select * from users where age=33 | db.users.find({age:33}) | 条件查询 |
Select a, b from users where age=33 | db.users.find({age:33},{a:1, b:1}) | 条件查询 |
select * from users where age<33 | db.users.find({‘age’:{$lt:33}}) | 条件查询 |
select * from users where age>33 and age<=40 | db.users.find({‘age’:{$gt:33,$lte:40}}) | 条件查询 |
select * from users where a=1 and b=’q’ | db.users.find({a:1,b:’q’}) | 条件查询 |
select * from users where a=1 or b=2 | db.users.find( { $or : [ { a : 1 } , { b : 2 } ] } ) | 条件查询 |
select * from users limit 1 | db.users.findOne() | 条件查询 |
select * from users where name like “%Joe%” | db.users.find({name:/Joe/}) | 模糊查询 |
select * from users where name like “Joe%” | db.users.find({name:/^Joe/}) | 模糊查询 |
select count(1) from users | Db.users.count() | 获取表记录数 |
select count(1) from users where age>30 | db.users.find({age: {‘$gt’: 30}}).count() | 获取表记录数 |
select DISTINCT last_name from users | db.users.distinct(‘last_name’) | 去掉重复值 |
select * from users ORDER BY name | db.users.find().sort({name:-1}) | 排序 |
select * from users ORDER BY name DESC | db.users.find().sort({name:-1}) | 排序 |
EXPLAIN select * from users where z=3 | db.users.find({z:3}).explain() | 获取存储路径 |
update users set a=1 where b=’q’ | db.users.update({b:’q’}, {$set:{a:1}}, false, true) | 更新记录 |
update users set a=a+2 where b=’q’ | db.users.update({b:’q’}, {$inc:{a:2}}, false, true) | 更新记录 |
delete from users where z=”abc” | db.users.remove({z:’abc’}) | 删除记录 |
delete from tb1; | db. users.remove() | 删除所有的记录 |
drop database IF EXISTS test; | use testdb.dropDatabase() | 删除数据库 |
drop table IF EXISTS test; | db.mytable.drop() | 删除表/collection |
grant xxx | db.addUser(‘test’, ’test’) | 添加用户readOnly–>false |
– | db.addUser(‘test’, ’test’, true) | 添加用户readOnly–>true |
set password for xx@xx = password(”); | db.addUser(“test”,”test222″) | 更改密码 |
drop user xx@xx; | db.system.users.remove({user:”test”})或者db.removeUser(‘test’) | 删除用户 |
root | use admin | 超级用户 |
grant | db.auth(‘test’, ‘test’) | 用户授权 |
select * from mysql.user | db.system.users.find() | 查看用户列表 |
select * from mysql.user | show users | 查看所有用户 |
show table status from t; | db.printCollectionStats() | 查看各collection的状态 |
show slave status; | db.printReplicationInfo() | 查看主从复制状态 |
show profiles; | show profile | 查看profiling |
– | db.copyDatabase(‘mail_addr’,’mail_addr_tmp’) | 拷贝数据库 |
查看information_schema | db.users.dataSize() | 查看collection数据的大小 |
查看information_schema | db. users.totalIndexSize() | 查询索引的大小 |
二、insert tab select怎么操作
var docs = db.tab1.find({"checked":false}).limit(0,500);
docs.forEach(function(d){db.tab2.insert(d)});
db.tab2.find({"checked":false}).count()
MongoDB需要做的是先声明一个变量,从tab1查询出你所需要插入的数据,然后利用构造函数循环插入tab2。
我们再来看下MySQL是怎么做的。
mysql> create table t1(id int);
Query OK, 0 rows affected (0.01 sec)
mysql> insert into t1 values(1);
Query OK, 1 row affected (0.01 sec)
mysql> insert into t1 values(2);
Query OK, 1 row affected (0.00 sec)
mysql> insert into t1 values(3);
Query OK, 1 row affected (0.00 sec)
mysql> create table t2(id int);
Query OK, 0 rows affected (0.01 sec)
mysql> insert into t2 select * from t1;
Query OK, 3 rows affected (0.00 sec)
Records: 3 Duplicates: 0 Warnings: 0
按照我们的思维,MySQL要形象得多,我们在这里做一下笔记。