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http://docs.mongodb.org/manual/reference/sql-comparison/
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.
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 | embedded documents and linking |
|
primary key Specify any unique column or column combination as primary key. |
In MongoDB, the primary key is automatically set to the _id field. |
| aggregation (e.g. group by) |
aggregation pipeline See the SQL to Aggregation Mapping Chart. |
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 |
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 users.
The MongoDB examples assume a collection named users that contain documents of the following prototype:
{
_id: ObjectId("509a8fb2f3f4948bd2f983a0"),
user_id: "abc123",
age: 55,
status: ‘A‘
}
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 users (
id MEDIUMINT NOT NULL
AUTO_INCREMENT,
user_id Varchar(30),
age Number,
status char(1),
PRIMARY KEY (id)
)
|
Implicitly created on first insert() operation. The primary key _id is automatically added if _id field is not specified. db.users.insert( {
user_id: "abc123",
age: 55,
status: "A"
} )
However, you can also explicitly create a collection: db.createCollection("users")
|
ALTER TABLE users
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, update() operations can add fields to existing documents using the $set operator. db.users.update(
{ },
{ $set: { join_date: new Date() } },
{ multi: true }
)
|
ALTER TABLE users
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, update() operations can remove fields from documents using the $unset operator. db.users.update(
{ },
{ $unset: { join_date: "" } },
{ multi: true }
)
|
CREATE INDEX idx_user_id_asc
ON users(user_id)
|
db.users.ensureIndex( { user_id: 1 } )
|
CREATE INDEX
idx_user_id_asc_age_desc
ON users(user_id, age DESC)
|
db.users.ensureIndex( { user_id: 1, age: -1 } )
|
DROP TABLE users
|
db.users.drop()
|
For more information, see db.collection.insert(), db.createCollection(), db.collection.update(), $set, $unset, db.collection.ensureIndex(), indexes, db.collection.drop(), and Data Modeling Concepts.
The following table presents the various SQL statements related to inserting records into tables and the corresponding MongoDB statements.
| SQL INSERT Statements | MongoDB insert() Statements |
|---|---|
INSERT INTO users(user_id,
age,
status)
VALUES ("bcd001",
45,
"A")
|
db.users.insert(
{ user_id: "bcd001", age: 45, status: "A" }
)
|
For more information, see db.collection.insert().
The following table presents the various SQL statements related to reading records from tables and the corresponding MongoDB statements.
| SQL SELECT Statements | MongoDB find() Statements |
|---|---|
SELECT *
FROM users
|
db.users.find()
|
SELECT id,
user_id,
status
FROM users
|
db.users.find(
{ },
{ user_id: 1, status: 1 }
)
|
SELECT user_id, status
FROM users
|
db.users.find(
{ },
{ user_id: 1, status: 1, _id: 0 }
)
|
SELECT *
FROM users
WHERE status = "A"
|
db.users.find(
{ status: "A" }
)
|
SELECT user_id, status
FROM users
WHERE status = "A"
|
db.users.find(
{ status: "A" },
{ user_id: 1, status: 1, _id: 0 }
)
|
SELECT *
FROM users
WHERE status != "A"
|
db.users.find(
{ status: { $ne: "A" } }
)
|
SELECT *
FROM users
WHERE status = "A"
AND age = 50
|
db.users.find(
{ status: "A",
age: 50 }
)
|
SELECT *
FROM users
WHERE status = "A"
OR age = 50
|
db.users.find(
{ $or: [ { status: "A" } ,
{ age: 50 } ] }
)
|
SELECT *
FROM users
WHERE age > 25
|
db.users.find(
{ age: { $gt: 25 } }
)
|
SELECT *
FROM users
WHERE age < 25
|
db.users.find(
{ age: { $lt: 25 } }
)
|
SELECT *
FROM users
WHERE age > 25
AND age <= 50
|
db.users.find(
{ age: { $gt: 25, $lte: 50 } }
)
|
SELECT *
FROM users
WHERE user_id like "%bc%"
|
db.users.find( { user_id: /bc/ } )
|
SELECT *
FROM users
WHERE user_id like "bc%"
|
db.users.find( { user_id: /^bc/ } )
|
SELECT *
FROM users
WHERE status = "A"
ORDER BY user_id ASC
|
db.users.find( { status: "A" } ).sort( { user_id: 1 } )
|
SELECT *
FROM users
WHERE status = "A"
ORDER BY user_id DESC
|
db.users.find( { status: "A" } ).sort( { user_id: -1 } )
|
SELECT COUNT(*)
FROM users
|
db.users.count()
or db.users.find().count()
|
SELECT COUNT(user_id)
FROM users
|
db.users.count( { user_id: { $exists: true } } )
or db.users.find( { user_id: { $exists: true } } ).count()
|
SELECT COUNT(*)
FROM users
WHERE age > 30
|
db.users.count( { age: { $gt: 30 } } )
or db.users.find( { age: { $gt: 30 } } ).count()
|
SELECT DISTINCT(status)
FROM users
|
db.users.distinct( "status" )
|
SELECT *
FROM users
LIMIT 1
|
db.users.findOne()
or db.users.find().limit(1)
|
SELECT *
FROM users
LIMIT 5
SKIP 10
|
db.users.find().limit(5).skip(10)
|
EXPLAIN SELECT *
FROM users
WHERE status = "A"
|
db.users.find( { status: "A" } ).explain()
|
For more information, see db.collection.find(), db.collection.distinct(), db.collection.findOne(), $ne $and, $or, $gt, $lt, $exists, $lte, $regex, limit(), skip(), explain(), sort(), and count().
The following table presents the various SQL statements related to updating existing records in tables and the corresponding MongoDB statements.
| SQL Update Statements | MongoDB update() Statements |
|---|---|
UPDATE users
SET status = "C"
WHERE age > 25
|
db.users.update(
{ age: { $gt: 25 } },
{ $set: { status: "C" } },
{ multi: true }
)
|
UPDATE users
SET age = age + 3
WHERE status = "A"
|
db.users.update(
{ status: "A" } ,
{ $inc: { age: 3 } },
{ multi: true }
)
|
For more information, see db.collection.update(), $set, $inc, and $gt.
The following table presents the various SQL statements related to deleting records from tables and the corresponding MongoDB statements.
| SQL Delete Statements | MongoDB remove() Statements |
|---|---|
DELETE FROM users
WHERE status = "D"
|
db.users.remove( { status: "D" } )
|
DELETE FROM users
|
db.users.remove({})
|
For more information, see db.collection.remove().
SQL to MongoDB Mapping Chart,布布扣,bubuko.com
标签：des class java http com width
原文地址：http://www.cnblogs.com/seasonzone/p/3796602.html
