- Java 8
- RabbitMQ installed and running
- Apache Maven 3.2.5
- Install requirements
cd python_trader
pip install -r requirements/requirements.txt-
TODO: configure trader.cfg with host where Consumer is being launched
-
Run the simluator
cd python_trader
python trader/simulate_trades.py- Trades simulator:
cd sparkjava_storm_websocket/python
source .venv/bin/activate
python trader_simulator/simulate_trades.py-
RabbitMQ:
-
SparkJava endpoint (message consumer):
-
Apache Storm topology (message processor):
-
Storm - RabbitMQ: https://github.com/ppat/storm-rabbitmq
+-----------+ +----------+ +--------------+ +----------+ +--------------+ Consumes RabbitMQ
+----> | Sparkjava +---> | RabbitMQ +---> | Apache Storm +--> | RabbitMQ +--> | Apache Camel | Publishes to
+-----------+ +----------+ +--------------+ +----------+ +-------+------+ Websocket
|
REST API RabbitMQ Spout. |
endpoint Aggregators and |
data processors +-----v-----+
| WEBSOCKET |
+-----^-----+
|
|
|
+-----+------+
| Javascript |
| (socket.io)|
+------------+
- Sparkjava for REST API endopint
- RabbitMQ for messaging
- Apache Storm for processing data
- Apache Camel for enrouting from RabbitMQ to websocket
- Websocket to publish real-time data
- Socket.io to generate the javascript frontend
JSON formatted:
{
"userId": "123456",
"currencyFrom": "EUR",
"currencyTo": "GBP",
"amountSell": 1000,
"amountBuy": 747.10,
"rate": 0.7471,
"timePlaced" : "24-JAN-15 10:27:44",
"originatingCountry" : "FR"
}TODO: fulfill this paragraph
Frontend will show a table with real-time data of the top X selled/bougth currencies during the last X minutes. The table could be something like the following example:
|--|--|--|
|Last X minutes sold|Last X minutes bought| |
|EUR: 1.250 (0.7564)|GBP: 820 (1.4322)| |
| FR (3x), US (2x), UK (1x) | SP (20x), UK (13x), NZ (2x) | # This are the top 3 sold from and bought from countries (and times) |
|GBP: 823 (0.8235)|USD: 2.234 (0.2341)| |
| FR (3x), US (2x), UK (1x) | SP (20x), UK (13x), NZ (2x) | # This are the top 3 sold from and bought from countries (and times) |
|...|...|...|
The json sent through websocket has the following format:
{
"accumulated_since": "24-JAN-15 10:17:44",
"sell": [
{
"curr": "EUR", "amount": 1000, "avr_rate": 1.8224,
"top": [{"country": "FR", "qtt": 3}, {"country": "US", "qtt": 2}, {"country": "UK", "qtt": 1}]
},
{
"curr": "GBP", "amount": 500, "avr_rate": 1.2234,
"top": [{"country": "FR", "qtt": 3}, {"country": "US", "qtt": 2}, {"country": "UK", "qtt": 1}]
},
...
],
"buy": [
{
"curr": "EUR", "amount": 1000, "avr_rate": 1.8224,
"top": [{"country": "FR", "qtt": 3}, {"country": "US", "qtt": 2}, {"country": "UK", "qtt": 1}]
},
{
"curr": "GBP", "amount": 500, "avr_rate": 1.2234,
"top": [{"country": "FR", "qtt": 3}, {"country": "US", "qtt": 2}, {"country": "UK", "qtt": 1}]
},
...
]
}- TODO: validate received fields (existing currencies, existing original country, well formatted dated, etc.)
- TODO: better authentication, not hardcoded
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