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A SDK should provide convenient methods for client applications to easily record users' behaviors in Apache PredictionIO's Event Server and also query recommendations from machine learning Engines. Therefore, a SDK typically has 2 corresponding clients: Event Client and Engine Client.

The following guideline bases on the REST API provided by Apache PredictionIO's Event Client which details can be found here.

Event Client

Because the Event Server has only 1 connection point, the Event Client needs to implement this core request first. The core request has the following rules.

  • URL: <base URL>/events.json?accessKey=<your access key> (e.g. http://localhost:7070/events.json?accessKey=1234567890)

  • Request: POST + JSON data. Please refer to the Event Creation API for the details on the fields of the JSON data object.

  • Response:

    • Success: status code 201 with a JSON result containing the eventId.
    • Failure: a JSON result containing a message field describing the error.
      • Status code 401: invalid access key.
      • Status code 400: fail to parse the JSON request e.g. missing required fields like event, or invalid eventTime format.

Other convenient methods are just shortcut. They could simply build the event's parameters and call the core request. Event Client should support the following 7 shorthand operations:

  • User entities

    • Sets properties of a user: with the JSON object

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      {
          "event": "$set",
          "entityType": "user",
          "entityId": <user_ID>,
          "properties": <properties>
      }
      
    • Unsets some properties of a user: with the JSON object

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      {
          "event": "$unset",
          "entityType": "user",
          "entityId": <user_ID>,
          "properties": <properties>
      }
      
    • Delete a user: with the JSON object

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      {
          "event": "$delete",
          "entityType": "user",
          "entityId": <user_ID>
      }
      
  • Item entities

    • Sets properties of an item: with the JSON object

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      {
          "event": "$set",
          "entityType": "item",
          "entityId": <item_ID>,
          "properties": <properties>
      }
      
    • Unsets some properties of an item: with the JSON object

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      {
          "event": "$unset",
          "entityType": "item",
          "entityId": <item_ID>,
          "properties": <properties>
      }
      
    • Delete an item: with the JSON object

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      {
          "event": "$delete",
          "entityType": "item",
          "entityId": <item_ID>
      }
      
  • Others

    • Record a user's action on some item: with the JSON object

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      {
          "event": <event_name>,
          "entityType": "user",
          "entityId": <user_ID>,
          "targetEntityType": "item",
          "targetEntityId": <item_ID>,
          "properties": <properties>
      }
      

Again, please refer to the API documentation for explanations on the reversed events like $set, $unset or $delete.

The eventTime is optional but it is recommended that the client application should include time in the request. Therefore, it is best that the Event Client includes the time field if missing, before sending the event to the server.

Engine Client

Engine Client's main job is to retrieve recommendation or prediction results from Apache PredictionIO's Engines. It has only a few rules on the request and response type.

  • URL: <base URL>/queries.json (e.g. http://localhost:8000/queries.json)

  • Request: POST + JSON data. For example,

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    {
        "user": 1,
        "num": 4
    }
    
  • Response:

    • Success: status code 200 with a JSON result object. For example,

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      {
          "itemScores": [
              {
                  "item": 39,
                  "score": "6.177719297832409"
              },
              {
                  "item": 79,
                  "score": "5.931687319083594"
              },
              ...
          ]
      }
      
    • Failure: status code 400 e.g. fail to parse the query.

The formats of JSON objects in both the request and response must be defined by the Apache PredictionIO's Engine and are different across applications. The above examples are taken from the Recommendation Engine template in which the query and prediction results are defined as following.

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case class Query(
  user: String,
  num: Int
) extends Serializable

case class PredictedResult(
  itemScores: Array[ItemScore]
) extends Serializable

Testing Your SDK

You can set up a local host Apache PredictionIO environment to test your SDK. However, it is hard to set it up online to test your SDK automatically using services like Travis CI. In that case, you should consider using these lightweight mock servers. Please see the instructions in the repo how to use it. It takes less than 5 minutes!

That's it! We are looking forward to see your SDK!