Mongo db basics

DOCUMENT BASED DATABASE
(MongoDB)

INTRODUCTION
• MongoDB is a schema-free document database written in C++ and
developed in an open-source project which is mainly driven by the
company 10gen Inc that also offers professional services around
MongoDB.
• the main goal of MongoDB is to close the gap between the fast and
highly scalable key-/value-stores and feature-rich traditional RDBMSs
relational database management systems.
• A database contains one or more collections consisting of documents.
• MongoDB is schema-free the documents within a collection may be
heterogeneous although the
• Once the first document is inserted into a database, a collection is
created automatically and the inserted document is added to this
collection.
It store data (which is in BSON – “Binary Serialized Document Notation” ) format

Advantage
Documents are independent units which makes performance better
(related data is read contiguously off disk) and makes it easier to
distribute data across multiple servers.
Application logic is easier to write. You don’t have to translate between
objects in your application and SQL queries, you can just turn the object model
directly into a document
Non-relational databases are highly scalable than the relational databases.
Non-relational databases process data faster than the relational databases
because they do not use ACID properties.
Non-relational databases are very flexible than the relational databases
because they are schemaless.

Disadvantage
Non-relational databases are less reliable than the relational databases
because they compromise reliability for performance.
Non-relational databases alsocompromise consistency for performance
In many non-relational databases security is lesser than relational databases
which is a major concern.
Like Mongodb and Cassandra both databases have lack of encryption for data
files, they have very weak authentication system, and very simple
authorization .

INSTALLATION
Step 1:- Download the latest production release of
MongoDB
Step 2:- Extract the downloaded archive.
• In Windows Explorer, find the MongoDB download file, typically in the
default Downloads directory.
• Extract the archive to C: by right clicking on the archive and selecting
Extract All and
Step 3:- Move the MongoDB directory to another
location.
• cd
• move C:mongodb-win32-* C:mongodb

INSTALLATION(Cont…)
Step 4:- Set Up the Data Directory
Step 5:- Start MongoDB
The default location for the MongoDB data directory is C:datadb.
Create this folder using the Command Prompt. Go to the C: directory
and issue the following command sequence:
md data
md datadb
You can specify an alternate path for data files using the
C:mongodbbinmongod.exe --dbpath d:testmongodbdata
C:mongodbbinmongod.exe
This will start the main MongoDB database process. The waiting for
connections message in the console
output indicates that the mongod.exe process is running successfully.

INSTALLATION(Cont…)
Step 6:- Connect to MongoDB
Connect to MongoDB using the mongo.exe shell.
C:mongodbbinmongo.exe
The mongo.exe shell will connect to mongod.exe running on the
localhost interface and port 27017 by default.

BASIC OPERATIONS
Oper 1:- Related to Database
After starting the mongo shell your session will use the test database by
default.
• To show the name of current database -> DB
• To display list of database -> show dbs
• Switch to a new database named mydb or create new database -> use
mydb
NOTE:MongoDB will not permanently create a database until you
insert data into that database.

BASIC OPERATIONS(Cont…)
Oper 2:- Create a Collection and Insert Documents
• MongoDB uses dynamic schemas , you also need not specify the
structure of your documents before inserting them into the
collection.
• Insert documents in testDb collection
db.testDb.insert({x: 20})
db.testDb.insert({x: 25 , name: “mongo”})
• When you insert the first document, the mongod will create both a
mydb database and the testData collection.
• All MongoDB documents must have an _id field with a unique
value. These operations do not explicitly specify a value for the _id
field, so mongo creates a unique ObjectId value for the field before
inserting it into the collection.

• To show list of collections in current database -> show collections
• To show list of documents in collection -> db.testDb.find()
• Query for Specific Documents -> db.testDb.find({x: 18})
• Limit the Number of Documents in the Result Set ->
db.testDb.find().limit(3)
Oper 3:- Update an existing document
• In MongoDB, db.collection.update() and the db.collection.save() methods
perform update operations.

•By default, the db.collection.update() method updates a single document.
However, with the multi option, update() can update all documents in a collection
that match a query.
db.inventory.update(
{ type: "book", item : "journal" },
{ $set : { qty: 10 } },
{ upsert : true }
)
•Call the update() method with the upsert flag to create a new document if no
document matches the update’s query criteria.

By default, db.collection.remove() method removes all documents that match its
query. However, the method can accept a flag to limit the delete operation to a
single document.
Oper 4:- Delete an existing document
In MongoDB, db.collection.remove() method performs delete operations.

Oper 5:- Fetching documents from collections

Specifying an equality condition –> db.inventory.find( { type: "snacks" } )
Specify Conditions Using Query Operators -> db.inventory.find( { type: {
$in: [ 'food', 'snacks' ] } } )
Specify AND Conditions -> db.inventory.find( { type: 'food', price: { $lt:
9.95 } } )
Specify OR Conditions -> db.inventory.find({ $or: [{ qty: { $gt: 100 } },
{ price: { $lt: 9.95 } }]})

BASIC TERMS
• Queries in MongoDB return all fields in all matching documents by default. To
limit the amount of data that MongoDB sends to applications, include a projection
in the queries.
1:- Projection
Exclude One Field From a Result Set
db.records.find( { "user_id": { $lt: 42} }, { history: 0} )
NOTE : you cannot mix exclusive and inclusive projections , Except for excluding
the _id field in inclusive projections.
Return Two Fields and Exclude _id
db.records.find( { "user_id": { $lt: 42} }, { "_id": 0, "name": 1 , "email": 1 } )
2:- Cursors
In the mongo shell, the primary method for the read operation is the
db.collection.find() method. This method queries a collection and returns a
cursor to the returning documents.

SQL to MongoDB Mapping Chart
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.
primary key
In MongoDB, the primary key is
automatically set to the_id field.

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
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.
1:- Create and alter

SQL Schema Statements MongoDB Schema Statements
ALTER TABLE users DROP COLUMN
join_date
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_age_desc ON
users(user_id, age DESC)
db.users.ensureIndex( { user_id: 1,
age: -1 } )
DROP TABLE users db.users.drop()

2:- Insert
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" } )

3:- Select
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: { $ne: "A" } } )
= "A" AND age = 50
db.users.find( { status: "A", age: 50 } )
= "A" OR age = 50
db.users.find( { $or: [ { status: "A" } , {
age: 50 } ] } )
SELECT * FROM users WHERE age >
25 AND age <= 50
db.users.find( { age: { $gt: 25, $lte: 50 } } )

3:- Select(Cont…)
SELECT * FROM users WHERE user_id
like "bc%"
db.users.find( { user_id: /^bc/ } )
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()

3:- Select(Cont…)
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()

4:- Update records
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 } )

5:- Delete records
SQL Delete Statements MongoDB remove() Statements
DELETE FROM users WHERE
status = "D"
db.users.remove( { status: "D" } )
DELETE FROM users db.users.remove({})

THANK YOU FOR READING
Dhaval M!5trY

Mongo db basics

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