multi-AD sample (Azure#20807)

* multi-AD sample

* rename placeholder

Author: hangzhao-microsoft

sdk/anomalydetector/azure-ai-anomalydetector/src/samples/java/com/azure/ai/anomalydetector/MultivariateSample.java

@@ -0,0 +1,189 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+package com.azure.ai.anomalydetector;
+
+import com.azure.ai.anomalydetector.models.*;
+import com.azure.core.credential.AzureKeyCredential;
+import com.azure.core.http.*;
+import com.azure.core.http.policy.*;
+import com.azure.core.http.rest.PagedIterable;
+import com.azure.core.http.rest.PagedResponse;
+import com.azure.core.http.rest.Response;
+import com.azure.core.http.rest.StreamResponse;
+import com.azure.core.util.Context;
+import reactor.core.publisher.Flux;
+
+import java.io.FileNotFoundException;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.io.UncheckedIOException;
+import java.nio.ByteBuffer;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+import java.time.*;
+import java.time.format.DateTimeFormatter;
+import java.util.Iterator;
+import java.util.List;
+import java.util.UUID;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Collectors;
+
+
+public class MultivariateSample {
+    private static void close(FileOutputStream fos) {
+        try {
+            fos.close();
+            System.out.println("closed");
+        } catch (IOException e) {
+            throw new UncheckedIOException(e);
+        }
+    }
+
+    private static void write(FileOutputStream fos, ByteBuffer b) {
+        try {
+            fos.write(b.array());
+        } catch (IOException e) {
+            throw new UncheckedIOException(e);
+        }
+    }
+
+    private static AnomalyDetectorClient getClient(String endpoint, String key) {
+        HttpHeaders headers = new HttpHeaders()
+            .put("Accept", ContentType.APPLICATION_JSON);
+
+        HttpPipelinePolicy authPolicy = new AzureKeyCredentialPolicy("Ocp-Apim-Subscription-Key",
+            new AzureKeyCredential(key));
+        AddHeadersPolicy addHeadersPolicy = new AddHeadersPolicy(headers);
+
+        HttpPipeline httpPipeline = new HttpPipelineBuilder().httpClient(HttpClient.createDefault())
+            .policies(authPolicy, addHeadersPolicy).build();
+        // Instantiate a client that will be used to call the service.
+        HttpLogOptions httpLogOptions = new HttpLogOptions();
+        httpLogOptions.setLogLevel(HttpLogDetailLevel.BODY_AND_HEADERS);
+
+        AnomalyDetectorClient anomalyDetectorClient = new AnomalyDetectorClientBuilder()
+            .pipeline(httpPipeline)
+            .endpoint(endpoint)
+            .httpLogOptions(httpLogOptions)
+            .buildClient();
+        return anomalyDetectorClient;
+    }
+
+    private static UUID getMetricId(AnomalyDetectorClient client, ModelInfo request) {
+        TrainMultivariateModelResponse trainMultivariateModelResponse = client.trainMultivariateModelWithResponse(request, Context.NONE);
+        String header = trainMultivariateModelResponse.getDeserializedHeaders().getLocation();
+        String[] model_ids = header.split("/");
+        UUID model_id = UUID.fromString(model_ids[model_ids.length - 1]);
+        return model_id;
+    }
+
+    private static ModelStatus getModelStatus(AnomalyDetectorClient client, UUID model_id) {
+        Response<Model> response = client.getMultivariateModelWithResponse(model_id, Context.NONE);
+        UUID model = response.getValue().getModelId();
+        System.out.println("training");
+        return response.getValue().getModelInfo().getStatus();
+    }
+
+    private static UUID getResultId(AnomalyDetectorClient client, UUID modelId, DetectionRequest detectionRequest) {
+        DetectAnomalyResponse detectAnomalyResponse = client.detectAnomalyWithResponse(modelId, detectionRequest, Context.NONE);
+        String response = detectAnomalyResponse.getDeserializedHeaders().getLocation();
+        String[] result = response.split("/");
+        UUID resultId = UUID.fromString(result[result.length - 1]);
+        return resultId;
+    }
+
+    private static DetectionStatus getInferenceStatus(AnomalyDetectorClient client, UUID resultId) {
+        DetectionResult response = client.getDetectionResult(resultId);
+        DetectionStatus status = response.getSummary().getStatus();
+        return status;
+    }
+
+    private static void ExportResult(AnomalyDetectorClient client, UUID modelId, String path) throws FileNotFoundException {
+        StreamResponse response = client.exportModelWithResponse(modelId, Context.NONE);
+        Flux<ByteBuffer> value = response.getValue();
+        FileOutputStream bw = new FileOutputStream(path);
+        value.subscribe(s -> write(bw, s), (e) -> close(bw), () -> close(bw));
+    }
+
+    private static void GetModelList(AnomalyDetectorClient client, Integer skip, Integer top){
+        PagedIterable<ModelSnapshot> response = client.listMultivariateModel(skip, top);
+        Iterator<PagedResponse<ModelSnapshot>> ite = response.iterableByPage().iterator();
+        int i =1;
+        while(ite.hasNext()){
+            PagedResponse<ModelSnapshot> items= ite.next();
+            System.out.println("The result in the page "+i);
+            i++;
+            for (ModelSnapshot item: items.getValue()
+            ) {
+                System.out.println("\t"+item.getModelId());
+            }
+            break;
+        }
+    }
+
+
+    public static void main(final String[] args) throws IOException, InterruptedException {
+        String endpoint = "<anomaly-detector-resource-endpoint>";
+        String key = "<anomaly-detector-resource-key>";
+        //Get multivariate client
+        AnomalyDetectorClient client = getClient(endpoint, key);
+
+
+        //Start training and get Model ID
+        Integer window = 28;
+        AlignMode alignMode = AlignMode.OUTER;
+        FillNAMethod fillNAMethod = FillNAMethod.LINEAR;
+        Integer paddingValue = 0;
+        AlignPolicy alignPolicy = new AlignPolicy().setAlignMode(alignMode).setFillNAMethod(fillNAMethod).setPaddingValue(paddingValue);
+        String source = "<Your own data source>";
+        OffsetDateTime startTime = OffsetDateTime.of(2021, 1, 1, 0, 0, 0, 0, ZoneOffset.UTC);
+        ;
+        OffsetDateTime endTime = OffsetDateTime.of(2021, 1, 2, 12, 0, 0, 0, ZoneOffset.UTC);
+        ;
+        String displayName = "<placeholder>";
+        ModelInfo request = new ModelInfo().setSlidingWindow(window).setAlignPolicy(alignPolicy).setSource(source).setStartTime(startTime).setEndTime(endTime).setDisplayName(displayName);
+        UUID modelId = getMetricId(client, request);
+        System.out.println(modelId);
+
+        //Check model status util the model get ready
+        while (true) {
+            ModelStatus modelStatus = getModelStatus(client, modelId);
+            TimeUnit.SECONDS.sleep(5);
+            assert modelStatus != ModelStatus.FAILED;
+            if (modelStatus == ModelStatus.READY) {
+                break;
+            }
+        }
+
+        //Start inference and get the Result ID
+        DetectionRequest detectionRequest = new DetectionRequest().setSource(source).setStartTime(startTime).setEndTime(endTime);
+        UUID resultId = getResultId(client, modelId, detectionRequest);
+
+
+        //Check inference status util the result get ready
+        while (true) {
+            DetectionStatus detectionStatus = getInferenceStatus(client, resultId);
+            TimeUnit.SECONDS.sleep(5);
+            assert detectionStatus != DetectionStatus.FAILED;
+            if (detectionStatus == DetectionStatus.READY) {
+                break;
+            }
+        }
+
+        //Export result files to local
+        String path = "<path for the saving zip file>";
+        ExportResult(client, modelId, path);
+
+
+        //Delete model
+        Response<Void> deleteMultivariateModelWithResponse = client.deleteMultivariateModelWithResponse(modelId, Context.NONE);
+
+
+        //Get model list
+        Integer skip = 0;
+        Integer top = 5;
+        GetModelList(client, skip, top);
+    }
+}