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Pizza "Quattro Shardoni"

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by Daniel Bartl on 14 November 2013

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Transcript of Pizza "Quattro Shardoni"

Stage 1:
Sales & Distribution

Super Mario's Pizza Ltd & Co. KG
Revolutionary pizza production system:
Sunbeaming
= Turning sunlight into pizza

Current production output:
- 500 Pizzas per second
- 1.8 Mio per hour
- 43,2 Mio per day
Mario hired Pasquale, Luigi, Marco, Enrico and the rest of his calabrian village to work as pizza boys.
Build a solution for managing Pizza orders: an Online-Shop for all kinds of end user devices!
Hungry
Münchner
Order
Sunbeam Pizza
Deliver Pizza
Process
Architecture
Web-Server
JSON
JSON
Application Server
Service
Mongos
JSON
Use Cases
Stage 2:
Online Sales Analytics

Mario needs insight:
- how many and which pizzas am I selling right NOW?
- where do the orders come from?
- how many pizzas have I sold so far?
Build a solution for real-time Online Sales Analytics
Architecture
Use Cases
Stage 3:
Controlling & Billing

Mario's revenue went down as the sales rose. He also received a letter from the tax office and then hired the Controller Fritz. Fritz decided to buy PAS - an integrated ERP solution used for billing and financial controlling
Architecture
Use Cases
Thank you for your attention!
Questions?

Hungry
Münchner
Order
Sunbeam Pizza
Deliver Pizza
Process
Presentation Layer
Wicket
Service Layer
Spring-Core
Data Access Layer Spring-Data
Presentation Layer
Spring-MVC (REST)
Integrate PAS Business Warehouse with Online Shop Orders
Hungry
Münchner
Order
Sunbeam Pizza
Deliver Pizza
Process
Web-Server
JSON
JSON
Application Server
Service
Mongos
JSON
PAS
Hadoop
Report Engine
Pizza "Quattro Shardoni"
at Super Mario's
Real Time
Analytics Engine
Mario's Goal
Aggregation
Framework
Map-Reduce
Pre-Aggregation
Real Time
Analytics Engine
Mario's Goal
Fritz
Mario
Mario
- Product Catalog
- High-Volume Data Feeds
- Large-scale Web Apps
- Database Transactions
- Operational Intelligence
- Real-time Dashboards
- Real-time Aggregation
- Recommendation Engine
- Large-scale batch processing
- Hadoop-Integration for large-scale batch processing
- agile, scalable and flexible addition to relational data stores
- MongoDB for every use case
All characters appeared in this
talk are fictitious.
Any resemblance to real persons
or companies is purely coincidental.

http://pizza.comsysto.com
Sharding + Replica Sets
{

"_id"
: ObjectId(
"4f886440744eab3cbfd4c2e8"
),

"orderId"
: NumberLong(
314064
),

"orderItems"
: [
{

"pizza"
: {

"_id"
: ObjectId(
"4f861500744e329ae6b2059b"
),

"articleId"
:
"6"
,

"description"
:
"mit Vorderschinken"
,

"name"
:
"Pizza Prosciutto"
,

"urlname"
:
"pizza-prosciutto"
,

"price"
:
4.9
},

"toppings"
: [
/* ... */
]
}
],

"orderDate"
: ISODate(
"2012-04-13T17:37:04.029Z"
),

"deliveryAddress"
: {

"firstname"
:
"Bernd"
,

"lastname"
:
"Zuther"
,

"street"
:
"Lindwurmstraße 97"
,

"zip"
:
"80337"
,

"city"
:
" München "
},

"user"
: {

"$ref"
:
"user"
,

"$id"
: ObjectId(
"4f861500744e329ae6b205b1"
)
}
}
@Document
public class
Pizza
implements
Serializable {


@Id

private
ObjectId
id
;

@Indexed
(unique =
true
)

private
String
articleId
;

private
String
description
;

private
String
name
;

@Indexed
(unique =
true
)

private
String
urlname
;

private

double

price
;


//Getter und Setter
}
Transform
on-demand
rollups
background
rollups
real-time
reporting
careers.comsysto.com
See the full transcript