Making Predictions via PMML Model¶ Purpose¶ This application demonstrates how to configure a pretrained PMML model to predict required raw materials from sweet production events and view the output on the console. Prerequisites¶ Download siddhi-gpl-execution-pmml-x.x.x.jar from the following link and copy the jar to /lib https://maven.wso2.org/nexus/content/repositories/wso2gpl/org/wso2/extension/siddhi/gpl/execution/pmml/siddhi-gpl-execution-pmml/ Save this sample. If there is no syntax error, the following message is shown on the console: Siddhi App PmmlModelProcessor successfully deployed. Executing the Sample¶ Replace with the SweetProductionRatePrediction.pmml file's absolute path - /samples/artifacts/PMMLModelProcessorSample/SweetProductionRatePrediction.pmml Start the Siddhi application by clicking on 'Run'. If the Siddhi application starts successfully, the following messages would be shown on the console. PmmlModelProcessor.siddhi - Started Successfully! Notes¶ If you edit this application while it's running, stop the application -> Save -> Start. * Stop this Siddhi application (Click 'Run' on menu bar -> 'Stop') * Start the application and check whether the specified events from the jms provider appear on the console. Testing the Sample¶ Send events through one or more of the following methods. * You may send events to SweetProductionStream, via event simulator: 1. Open the event simulator by clicking on the second icon or pressing Ctrl+Shift+I. 2. In the Single Simulation tab of the panel, specify the values as follows: * Siddhi App Name : PmmlModelProcessor * Stream Name : SweetProductionStream 3. In the name and amount fields, enter 'candy', 20, 23 respectively and then click Send to send the event. 4. Send more events as desired. Send events to the http endpoint defined by 'publish.url' in the Sink configuration through the curl command: Open a new terminal and issue the following command: curl -X POST -d '{"streamName": "SweetProductionStream", "siddhiAppName": "PmmlModelProcessor","data": ["candy", 20, 23]}' http://localhost:9390/simulation/single -H 'content-type: text/plain' If there is no error, the following messages are shown on the terminal: {"status":"OK","message":"Single Event simulation started successfully"} Publish events with Postman: Install Postman from https://www.postman.com/downloads/. Launch the application. Make a 'Post' request to the 'http://localhost:9390/simulation/single' endpoint. Set the Content-Type to 'text/plain' and set the request body in text as follows: Click 'send'. If there is no error, the following messages are shown on the console: "status": "OK", "message": "Single Event simulation started successfully" Notes¶ Accepted values for the 'name' field should be either candy, caramel-bar, peanut-butter-cup or truffle for the specific pretrained PMML model. Viewing the Results¶ See the prediction as output on the in the console. Note¶ Stop this Siddhi application, once you are done with the execution. -- Please refer to https://docs.wso2.com/display/SP400/Quick+Start+Guide on getting started with SP editor. @App:name("PmmlModelProcessor") @App:description('Use a pretrained PMML model to predict required raw materials. View the output on the console.') @Source(type = 'tcp', context='SweetProductionStream', @map(type='binary')) define stream SweetProductionStream (name string, currentHourAmount double, previousHourAmount double ); @sink(type='log') define stream PredictionStream (name string, currentHourAmount double, previousHourAmount double, Predicted_nextHourAmount string); from SweetProductionStream#pmml:predict('<SweetProductionRatePrediction_model_path>') select * insert into PredictionStream;