Introduction to 

Agenda

• Overview

• RDBMS mapping terminology

• Advantages

• Data Modelling

• Demonstration

• Aggregation

Overview

• open-source document database
• leading NoSQL database
• written in c++

RDBMS mapping terminology

Sample

document 

MongoDB Advantages

• Schema less

• No complex joins

• Structure of a single object is clear

• Conversion / mapping of application objects to database objects not needed

Data Modelling

• Combine objects into one document if you will use them together. 

• Duplicate the data (but limited).

• Do joins while write, not on read.

• Optimize your schema for most frequent use cases.

• Do complex aggregation in the schema

Data Modelling

RDBMS

MongoDB

Demonstration

• Start mongoDB service

C:\mongodb\bin>mongod.exe --dbpath 
"D:\workspace\mongodb\data"

• Run mongoDB shell

C:\mongodb\bin>mongo.exe

• Help & Statistics

db.help()

db.stats()

Demonstration (2)

• Create database

use DATABASE_NAME

• Create collection

db.createCollection(name, options)

• Insert document

db.employees.insert({"name" : "Su Tran"})

Demonstration (3)

• Query document

db.COLLECTION_NAME.find()

db.mycol.find({"likes":{$lt:50}})

where likes < 50

is equivalent to RDBMS Where clause

Demonstration (4)

• Query document

db.mycol.find({key1:value1, key2:value2})

RDBMS

AND

Mongo query

db.mycol.find({$or:
    [{"name":"Tuan"},{"name": "Su"}]})

OR

{$lt:50}

{$lte:50}

{$gt:50}

{$gte:50}

{$ne:50}

Aggregation

Aggregations operations process data records and return computed results

• Aggregation Pipelines
• Map-reduce
• Single Purpose Aggregation Operations

Aggregation Pipelines

Map-reduce

Single Purpose Aggregation Operations

References