| --- |
| title: App Integration Overview |
| --- |
| |
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| |
| Apache PredictionIO is designed as a machine learning server that |
| integrates with your applications on production environments. |
| |
| A web or mobile app normally: |
| |
| 1. Send event data to Apache PredictionIO's Event Server for model |
| training |
| 2. Send dynamic queries to deployed engine(s) to retrieve predicted results |
| |
|  |
| |
| ## Sending Event Data |
| |
| Apache PredictionIO's Event Server receives event data from your |
| application. The data can be used by engines as training data to build predictive |
| models. |
| |
| Event Server listens to port 7070 by default. You can change the port with the |
| [--port arg](/cli/#event-server-commands) when you launch the Event Server. |
| |
| For further information, please read: |
| |
| * [Event Server Overview](/datacollection/) |
| * [Collecting Data with REST/SDKs](/datacollection/eventapi) |
| |
| ## Sending Query |
| |
| After you deploy an engine as a web service, it will wait for queries from your |
| application and return predicted results in JSON format. An engine listens to |
| port 8000 by default. If you want to deploy multiple engines, you can specific a |
| different port for each of them. |
| |
| For further information, please read: |
| |
| * [Deploying an Engine as a Web Service](/deploy/) |
