The document is a presentation on MongoDB for developers by Ciro Donato Caiazzo. It introduces MongoDB as a non-relational database for storing JSON documents with a focus on speed, performance, flexibility and scalability. It discusses that MongoDB uses collections for storing groups of data like tables in a SQL database. It also covers how to start with MongoDB by downloading, installing, and running the mongod process before accessing the mongo shell to perform operations like insert, find, update and remove on databases and collections.

1. by Ciro Donato Caiazzo
Bologna, July 21, 2015
MongoDB for
Developers

2. {
"Name" : "Ciro Donato",
"Surname": "Caiazzo",
"I am": "Software Engineer",
"Working in": "SCAI Consulting",
"With Title": "Senior Developer Consultant",
"ContactMethods" : [
{"Type": "Twitter", "Value": "@CyrusD87"},
{"Type": "Linkedin", "Value": "Ciro Donato Caiazzo"},
{"Type": "Personal e-mail", "Value": "cd.caiazzo@gmail.com"},
{"Type": "Job e-mail",
"Value": "ciro.caiazzo@scai-consulting.grupposcai.it"}
],
"Some passions": ["Tecnology","Innovation","Agile","Big data"]
}

3. What are NoSQL?

4. NoSQL developed in response to a rise in the
volume of data…
…with a focus on speed, performance, flexibility
and scalability…
… for the new modern applications.

5.  NoSQL data model addresses issues that
relational model cannot achieve (ex. It
manage Large volumes of structured, semi-
structured, and unstructured data, etc…)
 NoSQL databases are more scalable and
provide superior performance

6. NoSQL
DOCUMENT
GRAPH
KEY-VALUE
WIDE-
COLUMN

7. What is?

8.  MongoDB is a non relational datastore for
JSON documents
 Written in C++
 License GNU AGPL v3.0 (more..)
MongoDBBSON
{
"skills":{
"database":[
{
"name":"Sql",
"years":"7"
},
{
"name":"MongoDB",
"years":"2"
}
]
}
}

9.  MongoDB uses collections for storing groups
of data.
 A collection can be thought as a table in a
relational database.
MongoDB
Collection 2
Collection 3
Collection 1
RDBMS
Table 1
Table 2
Table 3

10.  Schemaless means that two documents that
don't have the same schema can be stored in
the same collection.
{"_id" : "1", "skill" : {"web": [{"name": "html"}, {"name": "css"}]}}
{"_id" : "2", "skill" : {"database": [{"name": "mongoDB"}, {"name": "sql
server"}]}}
{"_id" : "3", "skill" : {"methodologies": ["scrum","kanban","xp"]}}

11. MongoDB does not support:
 Joins;
 Transactions across multiple collections
But each operation is atomic at level of single
document
Reason?? Scalability!

12. In MongoDB, documents stored in a collection
require a unique _id field that acts as a primary key
ObjectId is a 12-byte BSON type, constructed
using:
 a 4-byte value representing the seconds since
the Unix epoch,
 a 3-byte machine identifier,
 a 2-byte process id, and
 a 3-byte counter, starting with a random value.

13. What does it happen for date after the 2038?
(Year 2038 problem)
On Unix systems, dates are represented as seconds
from 1 January 1970 and usually stored in the
C time_t type.
MongoDB does not use time_t to represent dates
internally so do not suffer from this problem
http://api.mongodb.org/python/2.1.1/faq.html

14. Where to start?

15. InWindows
 Download and install MongoDB
 https://www.mongodb.org/downloads

16.  Include MongoDB (bin) path in the
environment variable ‘PATH’
 Open Command Prompt and run the
following command to create the directories
where MongoDB will save the data:

17. Run ‘mongod’
And now? Go to the Mongo Shell….

18. The mongo shell is an interactive JavaScript
shell for MongoDB
 Run ‘mongo’ command to start mongo shell

19.  use <your-database-name>
The above is supposed to create a database called <your-
database-name> but … MongoDB creates databases on-
demand. It will get created only when we add something to it
 db.<your-collection-name>.save(<your-json-document>)
The above statement will create a collection called <your-
collection-name>.under the database ‘<your-database-name>

20.  Insert
 Find

21.  Find (with filter)
 FindOne

22.  Update
 Remove

23. Performance

24. Indexes support the efficient execution of
queries in MongoDB (Default _id, Single Field,
Compound Index, Multikey Index, Geospatial
Indexes,Text Indexes,Hashed Indexes)

25. Aggregation

26. Documents enter a multi-stage pipeline that transforms the
documents into an aggregated results.
http://docs.mongodb.org/manual/core/aggregation-pipeline/

27. Map-reduce is a data processing paradigm for condensing large
volumes of data into useful aggregated results
http://docs.mongodb.org/manual/core/map-reduce/

28. Let's go over

29.  Replication
 Sharding

30.  Training
https://www.mongodb.org/
https://university.mongodb.com/
 Database-as-a-Service
https://mongolab.com
https://www.compose.io/

31. MongoDB for Developers
by Ciro Donato Caiazzo
Bologna, July 21, 2015