MongoDB vs. mysql command comparison
The traditional relational database is usually composed of three hierarchical concepts of database, table, record, and MongoDB is made up of database, collection (collection), Three levels of document objects. MongoDB is for tables in relational databases, but there is no concept of columns, rows, and relationships in the collection, which embodies the nature of pattern freedom.
Mysql |
Mongodb |
Description |
Mysqld |
Mongod |
Server daemon |
Mysql |
Mongo |
Client Tools |
Mysqldump |
Mongodump |
Logical Backup tool |
Mysql |
Mongorestore |
Logical Recovery Tool |
|
Db.repairdatabase () |
Repairing the database |
Mysqldump |
Mongoexport |
Data Export Tool |
Source |
Mongoimport |
Data Import Tool |
Grant * privileges on *. |
Db.adduser () Db.auth () |
New User and Permissions |
Show databases |
Show DBS |
Show Library List |
Show tables |
Show Collections |
Show Table List |
Show slave status |
Rs.status |
Querying master-Slave status |
Create table Users (a int, b int) |
Db.createcollection ("Mycoll", {capped:true, size:100000}) Another: The table can be created implicitly. |
Create a table |
Create INDEX idxname on users (name) |
Db.users.ensureIndex ({name:1}) |
Create an index |
Create INDEX idxname on users (Name,ts DESC) |
Db.users.ensureIndex ({name:1,ts:-1}) |
Create an index |
Insert into users values (1, 1) |
Db.users.insert ({a:1, b:1}) |
Inserting records |
Select A, B from users |
Db.users.find ({},{a:1, b:1}) |
Query table |
Select * from users |
Db.users.find () |
Query table |
Select * from users where age=33 |
Db.users.find ({age:33}) |
Conditional query |
Select A, b from users where age=33 |
Db.users.find ({age:33},{a:1, b:1}) |
Conditional query |
SELECT * from Users where age<33 |
Db.users.find ({' age ': {$lt: 33}}) |
Conditional query |
SELECT * from users where age>33 and age<=40 |
Db.users.find ({' age ': {$gt:, $lte: 40}}) |
Conditional query |
SELECT * from users where a=1 and b= ' Q ' |
Db.users.find ({a:1,b: ' Q '}) |
Conditional query |
SELECT * from users where a=1 or b=2 |
Db.users.find ({$or: [{a:1}, {b:2}]}) |
Conditional query |
SELECT * from users limit 1 |
Db.users.findOne () |
Conditional query |
SELECT * from the users where name like "%joe%" |
Db.users.find ({name:/joe/}) |
Fuzzy query |
SELECT * from the users where name like "joe%" |
Db.users.find ({name:/^joe/}) |
Fuzzy query |
Select COUNT (1) from users |
Db.users.count () |
Get table Record Count |
Select COUNT (1) from users where age>30 |
Db.users.find ({age: {' $GT ': $}}). Count () |
Get table Record Count |
Select DISTINCT last_name from Users |
Db.users.distinct (' last_name ') |
Remove duplicate values |
SELECT * from the users ORDER by name |
Db.users.find (). Sort ({name:-1}) |
Sort |
SELECT * from Users ORDER by name DESC |
Db.users.find (). Sort ({name:-1}) |
Sort |
EXPLAIN SELECT * from Users where z=3 |
Db.users.find ({Z:3}). Explain () |
Get Storage Path |
Update users set a=1 where b= ' Q ' |
Db.users.update ({b: ' Q '}, {$set: {a:1}}, False, True) |
Update record |
Update users set a=a+2 where b= ' Q ' |
Db.users.update ({b: ' Q '}, {$inc: {a:2}}, False, True) |
Update record |
Delete from users where z= "abc" |
Db.users.remove ({z: ' abc '}) |
Deleting records |
|
Db. Users.remove () |
Delete all the records |
Drop database IF EXISTS test; |
Use test Db.dropdatabase () |
Deleting a database |
drop table IF EXISTS test; |
Db.mytable.drop () |
Delete Table/collection |
|
Db.adduser (' Test ', ' test ') |
Add user Readonly-->false |
|
Db.adduser (' Test ', ' test ', true) |
Add user Readonly-->true |
|
Db.adduser ("Test", "test222") |
Change Password |
|
Db.system.users.remove ({User: "Test"}) or Db.removeuser (' test ') |
Delete User |
|
|
MongoDB syntax
MongoDB benefits Quite a lot, such as multi-column index, query can use some statistical functions, support multi-conditional query, but the current multi-table query is not supported, you can find a way to solve the problem of multi-table query through data redundancy.
MongoDB is very rich in data manipulation, here are some examples, the content is mostly from official documents, in addition to some of their own understanding.
Query Colls all data
Db.colls.find ()//select * from Colls
Querying by specifying criteria
Db.colls.find ({' last_name ': ' Smith '}),//select * from Colls where last_name= ' Smith '
Specify a multi-criteria query
Db.colls.find ({x:3, y: "foo"}),//select * from Colls where x=3 and y= ' foo '
Specify criteria range Query
Db.colls.find ({j: {$ne: 3}, K: {$gt: ten}});//select * from Colls where j!=3 and k>10
Query does not include a content
Db.colls.find ({}, {a:0});//query all data except for a of 0
Support <, <=, >= query, with symbolic substitution for $lt, $lte, $GT, $gte
Db.colls.find ({"field": {$gt: Value}});
Db.colls.find ({"field": {$lt: Value}});
Db.colls.find ({"field": {$gte: Value}});
Db.colls.find ({"field": {$lte: Value}});
You can also make a range query for a field
Db.colls.find ({"field": {$gt: value1, $lt: value2}});
Not equal to query character $ne
Db.colls.find ({x: {$ne: 3}});
In query with character $in
Db.colls.find ({"field": {$in: Array}});
Db.colls.find ({j:{$in: [2,4,6]}});
Not in query with character $nin
Db.colls.find ({j:{$nin: [2,4,6]}});
Character $mod for modulo query
Db.colls.find ({A: {$mod: [ten, 1]}})//where a% 10 = = 1
$all Query
Db.colls.find ({A: {$all: [2, 3]}});//Specifies that a satisfies any value in the array
$size Query
Db.colls.find ({A: {$size: 1});//The number of objects queried, this query queries the number of child objects of a 1 record
$exists Query
Db.colls.find ({A: {$exists: true}}); There is data for the A object
Db.colls.find ({A: {$exists: false}}); There is no data for the A object
$type Query the type value of the $type value to bsonhttp://bsonspec.org/data
Db.colls.find ({A: {$type: 2}}); Match A to string type data
Db.colls.find ({A: {$type: 16}}); Match A to int type data
Using regular expression matching
Db.colls.find ({name:/acme.*corp/i});//similar to SQL
Inline Object Query
Db.colls.find ({"Author.name": "Joe"});
1.3.3 versions and later versions include $not queries
Db.colls.find ({name: {$not:/acme.*corp/i}});
Db.colls.find ({A: {$not: {$mod: [10, 1]}}});
Sort () sorting
Db.colls.find (). Sort ({ts:-1});//1 to ascending 2 to descending
Limit () returns the number of restricted query data
Db.colls.find (). Limit (10)
Skip () skips some data
Db.colls.find (). Skip (10)
Snapshot () snapshot guarantees no duplicate data return or object loss
Count () counts the number of query objects
Db.students.find ({' address.state ': ' CA '}). Count ();//High efficiency
Db.students.find ({' address.state ': ' CA '}). ToArray (). length;//is inefficient
Group () resembles the group by function in SQL by grouping query results
Distinct () returns non-repeating values
MongoDB command and SQL syntax comparison