21.SQL to MongoDB Mapping Chart-官方文档摘录

2022-12-19 15:11:53

有关关系型数据库跟Mongod的语法对比

In addition to the charts that follow, you might want to consider the Frequently Asked Questions section for a selection of common questions about MongoDB.

Terminology and Concepts

The following table presents the various SQL terminology and concepts and the corresponding MongoDB terminology and concepts.

SQL Terms/Concepts	MongoDB Terms/Concepts
database	database
table	collection
row	document or BSON document
column	field
index	index
table joins	`$lookup`, embedded documents
primary key Specify any unique column or column combination as primary key.	primary key In MongoDB, the primary key is automatically set to the _idfield.
aggregation (e.g. group by)	aggregation pipeline See the SQL to Aggregation Mapping Chart.

Executables

The following table presents some database executables and the corresponding MongoDB executables. This table is not meant to be exhaustive.

	MongoDB	MySQL	Oracle	Informix	DB2
Database Server	`mongod`	`mysqld`	`oracle`	`IDS`	`DB2 Server`
Database Client	`mongo`	`mysql`	`sqlplus`	`DB-Access`	`DB2 Client`

Examples

The following table presents the various SQL statements and the corresponding MongoDB statements. The examples in the table assume the following conditions:

The SQL examples assume a table named people.

The MongoDB examples assume a collection named people that contain documents of the following prototype:

{

  _id: ObjectId("509a8fb2f3f4948bd2f983a0"),

  user_id: "abc123",

  age: 55,

  status: 'A'

}

Create and Alter

The following table presents the various SQL statements related to table-level actions and the corresponding MongoDB statements.

SQL Schema Statements	MongoDB Schema Statements
CREATE TABLE people ( id MEDIUMINT NOT NULL AUTO_INCREMENT, user_id Varchar(30), age Number, status char(1), PRIMARY KEY (id) )	Implicitly created on first `insertOne()` or `insertMany()`operation. The primary key `_id` is automatically added if `_id` field is not specified. db.people.insertOne( { user_id: "abc123", age: 55, status: "A" } ) However, you can also explicitly create a collection: db.createCollection("people")
ALTER TABLE people ADD join_date DATETIME	Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, `updateMany()` operations can add fields to existing documents using the `$set` operator. db.people.updateMany( { }, { $set: { join_date: new Date() } } )
ALTER TABLE people DROP COLUMN join_date	Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, `updateMany()` operations can remove fields from documents using the `$unset` operator. db.people.updateMany( { }, { $unset: { "join_date": "" } } )
CREATE INDEX idx_user_id_asc ON people(user_id)	db.people.createIndex( { user_id: 1 } )
CREATE INDEX idx_user_id_asc_age_desc ON people(user_id, age DESC)	db.people.createIndex( { user_id: 1, age: -1 } )
DROP TABLE people	db.people.drop()

For more information, see:

Insert

The following table presents the various SQL statements related to inserting records into tables and the corresponding MongoDB statements.

SQL INSERT Statements	MongoDB insertOne() Statements
INSERT INTO people(user_id, age, status) VALUES ("bcd001", 45, "A")	db.people.insertOne( { user_id: "bcd001", age: 45, status: "A" } )

For more information, see db.collection.insertOne().

Select

The following table presents the various SQL statements related to reading records from tables and the corresponding MongoDB statements.

NOTE

The find() method always includes the _id field in the returned documents unless specifically excluded through projection. Some of the SQL queries below may include an _id field to reflect this, even if the field is not included in the corresponding find() query.

SQL SELECT Statements	MongoDB find() Statements
SELECT * FROM people	db.people.find()
SELECT id, user_id, status FROM people	db.people.find( { }, { user_id: 1, status: 1 } )
SELECT user_id, status FROM people	db.people.find( { }, { user_id: 1, status: 1, _id: 0 } )
SELECT * FROM people WHERE status = "A"	db.people.find( { status: "A" } )
SELECT user_id, status FROM people WHERE status = "A"	db.people.find( { status: "A" }, { user_id: 1, status: 1, _id: 0 } )
SELECT * FROM people WHERE status != "A"	db.people.find( { status: { $ne: "A" } } )
SELECT * FROM people WHERE status = "A" AND age = 50	db.people.find( { status: "A", age: 50 } )
SELECT * FROM people WHERE status = "A" OR age = 50	db.people.find( { $or: [ { status: "A" } , { age: 50 } ] } )
SELECT * FROM people WHERE age > 25	db.people.find( { age: { $gt: 25 } } )
SELECT * FROM people WHERE age < 25	db.people.find( { age: { $lt: 25 } } )
SELECT * FROM people WHERE age > 25 AND age <= 50	db.people.find( { age: { $gt: 25, $lte: 50 } } )
SELECT * FROM people WHERE user_id like "%bc%"	db.people.find( { user_id: /bc/ } ) -or- db.people.find( { user_id: { $regex: /bc/ } } )
SELECT * FROM people WHERE user_id like "bc%"	db.people.find( { user_id: /^bc/ } ) -or- db.people.find( { user_id: { $regex: /^bc/ } } )
SELECT * FROM people WHERE status = "A" ORDER BY user_id ASC	db.people.find( { status: "A" } ).sort( { user_id: 1 } )
SELECT * FROM people WHERE status = "A" ORDER BY user_id DESC	db.people.find( { status: "A" } ).sort( { user_id: -1 } )
SELECT COUNT(*) FROM people	db.people.count() or db.people.find().count()
SELECT COUNT(user_id) FROM people	db.people.count( { user_id: { $exists: true } } ) or db.people.find( { user_id: { $exists: true } } ).count()
SELECT COUNT(*) FROM people WHERE age > 30	db.people.count( { age: { $gt: 30 } } ) or db.people.find( { age: { $gt: 30 } } ).count()
SELECT DISTINCT(status) FROM people	db.people.distinct( "status" )
SELECT * FROM people LIMIT 1	db.people.findOne() or db.people.find().limit(1)
SELECT * FROM people LIMIT 5 SKIP 10	db.people.find().limit(5).skip(10)
EXPLAIN SELECT * FROM people WHERE status = "A"	db.people.find( { status: "A" } ).explain()

For more information, see:

db.collection.find()
db.collection.distinct()
db.collection.findOne()
Query operators: $ne, $and, $or, $gt, $lt, $exists, $lte, and $regex.
limit()
skip()
explain()
sort()
count()

Update Records

The following table presents the various SQL statements related to updating existing records in tables and the corresponding MongoDB statements.

SQL Update Statements	MongoDB updateMany() Statements
UPDATE people SET status = "C" WHERE age > 25	db.people.updateMany( { age: { $gt: 25 } }, { $set: { status: "C" } } )
UPDATE people SET age = age + 3 WHERE status = "A"	db.people.updateMany( { status: "A" } , { $inc: { age: 3 } } )

SQL Update Statements

MongoDB updateMany() Statements

UPDATE people

SET status = "C"

WHERE age > 25

db.people.updateMany(

   { age: { $gt: 25 } },

   { $set: { status: "C" } }

)

UPDATE people

SET age = age + 3

WHERE status = "A"

db.people.updateMany(

   { status: "A" } ,

   { $inc: { age: 3 } }

)

For more information, see db.collection.updateMany(), $set, $inc, and $gt.

Delete Records

The following table presents the various SQL statements related to deleting records from tables and the corresponding MongoDB statements.

SQL Delete Statements	MongoDB deleteMany() Statements
DELETE FROM people WHERE status = "D"	db.people.deleteMany( { status: "D" } )
DELETE FROM people	db.people.deleteMany({})

For more information, see db.collection.deleteMany().

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