Hello_PredictionIO.md

Hello Apache PredictionIO!

• Installation

Start event server:

$ pio eventserver &

Create new application:

$ pio app new MyApp1

$ export ACCESS_KEY=<ACCESS_KEY>

Test event server by importing event data:

$ curl -i -X POST http://localhost:7070/events.json?accessKey=$ACCESS_KEY \
-H "Content-Type: application/json" \
-d '{
  "event" : "rate",
  "entityType" : "user",
  "entityId" : "u0",
  "targetEntityType" : "item",
  "targetEntityId" : "i0",
  "properties" : {
    "rating" : 5
  }
  "eventTime" : "2014-11-02T09:39:45.618-08:00"
}'

$ curl -i -X POST http://localhost:7070/events.json?accessKey=$ACCESS_KEY \
-H "Content-Type: application/json" \
-d '{
  "event" : "buy",
  "entityType" : "user",
  "entityId" : "u1",
  "targetEntityType" : "item",
  "targetEntityId" : "i2",
  "eventTime" : "2014-11-10T12:34:56.123-08:00"
}'

$ curl "http://localhost:7070/events.json?accessKey=$ACCESS_KEY"

Clone engine template:

$ git clone https://github.com/apache/predictionio-template-recommender.git
$ cd predictionio-template-recommender

Edit engine.json:

...
"datasource": {
  "params" : {
    "appName": "MyApp1" // <- Edit appName
  }
},
...

Edit src/main/scala/ALSAlgorithm.scala:

sc.setCheckpointDir("checkpoint") // <- activate this line to avoid StackOverflowError

Import event data in bulk:

$ curl https://raw.githubusercontent.com/apache/spark/master/data/mllib/sample_movielens_data.txt --create-dirs -o data/sample_movielens_data.txt
$ python data/import_eventserver.py --access_key $ACCESS_KEY

Build engine:

$ pio build

Train model:

$ pio train

Deploy model as Web API:

$ pio deploy

Access to http://localhost:8000 to see the status of Web API.

Test prediction Web API:

$ curl http://localhost:8000/queries.json -H "Content-Type: application/json" -d '{ "user": "1", "num": 4 }'