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Posted to commits@ambari.apache.org by av...@apache.org on 2017/09/21 22:41:34 UTC

[3/4] ambari git commit: AMBARI-21686 : Implement a test driver that provides a set of metric series with different kinds of metric behavior. (avijayan)

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricSparkConsumer.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricSparkConsumer.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricSparkConsumer.java
new file mode 100644
index 0000000..7735d6c
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+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricSparkConsumer.java
@@ -0,0 +1,178 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+import org.apache.ambari.metrics.alertservice.prototype.methods.MetricAnomaly;
+import org.apache.ambari.metrics.alertservice.prototype.methods.ema.EmaTechnique;
+import org.apache.commons.lang.StringUtils;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetrics;
+import org.apache.spark.SparkConf;
+import org.apache.spark.api.java.function.Function;
+import org.apache.spark.broadcast.Broadcast;
+import org.apache.spark.streaming.Duration;
+import org.apache.spark.streaming.api.java.JavaDStream;
+import org.apache.spark.streaming.api.java.JavaPairDStream;
+import org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream;
+import org.apache.spark.streaming.api.java.JavaStreamingContext;
+import org.apache.spark.streaming.kafka.KafkaUtils;
+import scala.Tuple2;
+
+import java.util.*;
+
+public class MetricSparkConsumer {
+
+  private static final Log LOG = LogFactory.getLog(MetricSparkConsumer.class);
+  private static String groupId = "ambari-metrics-group";
+  private static String topicName = "ambari-metrics-topic";
+  private static int numThreads = 1;
+  private static long pitStartTime = System.currentTimeMillis();
+  private static long ksStartTime = pitStartTime;
+  private static long hdevStartTime = ksStartTime;
+
+  public MetricSparkConsumer() {
+  }
+
+  public static void main(String[] args) throws InterruptedException {
+
+    if (args.length < 5) {
+      System.err.println("Usage: MetricSparkConsumer <appid1,appid2> <collector_host> <port> <protocol> <zkQuorum>");
+      System.exit(1);
+    }
+
+    List<String> appIds = Arrays.asList(args[0].split(","));
+    String collectorHost = args[1];
+    String collectorPort = args[2];
+    String collectorProtocol = args[3];
+    String zkQuorum = args[4];
+
+    double emaW = StringUtils.isNotEmpty(args[5]) ? Double.parseDouble(args[5]) : 0.5;
+    double emaN = StringUtils.isNotEmpty(args[8]) ? Double.parseDouble(args[6]) : 3;
+    double tukeysN = StringUtils.isNotEmpty(args[7]) ? Double.parseDouble(args[7]) : 3;
+
+    long pitTestInterval = StringUtils.isNotEmpty(args[8]) ? Long.parseLong(args[8]) : 5 * 60 * 1000;
+    long pitTrainInterval = StringUtils.isNotEmpty(args[9]) ? Long.parseLong(args[9]) : 15 * 60 * 1000;
+
+    String fileName = args[10];
+    long ksTestInterval = StringUtils.isNotEmpty(args[11]) ? Long.parseLong(args[11]) : 10 * 60 * 1000;
+    long ksTrainInterval = StringUtils.isNotEmpty(args[12]) ? Long.parseLong(args[12]) : 10 * 60 * 1000;
+    int hsdevNhp = StringUtils.isNotEmpty(args[13]) ? Integer.parseInt(args[13]) : 3;
+    long hsdevInterval = StringUtils.isNotEmpty(args[14]) ? Long.parseLong(args[14]) : 30 * 60 * 1000;
+
+    String ambariServerHost = args[15];
+    String clusterName = args[16];
+
+    MetricsCollectorInterface metricsCollectorInterface = new MetricsCollectorInterface(collectorHost, collectorProtocol, collectorPort);
+
+    SparkConf sparkConf = new SparkConf().setAppName("AmbariMetricsAnomalyDetector");
+
+    JavaStreamingContext jssc = new JavaStreamingContext(sparkConf, new Duration(10000));
+
+    EmaTechnique emaTechnique = new EmaTechnique(emaW, emaN);
+    PointInTimeADSystem pointInTimeADSystem = new PointInTimeADSystem(metricsCollectorInterface,
+      tukeysN,
+      pitTestInterval,
+      pitTrainInterval,
+      ambariServerHost,
+      clusterName);
+
+    TrendADSystem trendADSystem = new TrendADSystem(metricsCollectorInterface,
+      ksTestInterval,
+      ksTrainInterval,
+      hsdevNhp,
+      fileName);
+
+    Broadcast<EmaTechnique> emaTechniqueBroadcast = jssc.sparkContext().broadcast(emaTechnique);
+    Broadcast<PointInTimeADSystem> pointInTimeADSystemBroadcast = jssc.sparkContext().broadcast(pointInTimeADSystem);
+    Broadcast<TrendADSystem> trendADSystemBroadcast = jssc.sparkContext().broadcast(trendADSystem);
+    Broadcast<MetricsCollectorInterface> metricsCollectorInterfaceBroadcast = jssc.sparkContext().broadcast(metricsCollectorInterface);
+
+    JavaPairReceiverInputDStream<String, String> messages =
+      KafkaUtils.createStream(jssc, zkQuorum, groupId, Collections.singletonMap(topicName, numThreads));
+
+    //Convert JSON string to TimelineMetrics.
+    JavaDStream<TimelineMetrics> timelineMetricsStream = messages.map(new Function<Tuple2<String, String>, TimelineMetrics>() {
+      @Override
+      public TimelineMetrics call(Tuple2<String, String> message) throws Exception {
+        ObjectMapper mapper = new ObjectMapper();
+        TimelineMetrics metrics = mapper.readValue(message._2, TimelineMetrics.class);
+        return metrics;
+      }
+    });
+
+    timelineMetricsStream.print();
+
+    //Group TimelineMetric by AppId.
+    JavaPairDStream<String, TimelineMetrics> appMetricStream = timelineMetricsStream.mapToPair(
+      timelineMetrics -> timelineMetrics.getMetrics().isEmpty()  ?  new Tuple2<>("TEST", new TimelineMetrics()) : new Tuple2<String, TimelineMetrics>(timelineMetrics.getMetrics().get(0).getAppId(), timelineMetrics)
+    );
+
+    appMetricStream.print();
+
+    //Filter AppIds that are not needed.
+    JavaPairDStream<String, TimelineMetrics> filteredAppMetricStream = appMetricStream.filter(new Function<Tuple2<String, TimelineMetrics>, Boolean>() {
+      @Override
+      public Boolean call(Tuple2<String, TimelineMetrics> appMetricTuple) throws Exception {
+        return appIds.contains(appMetricTuple._1);
+      }
+    });
+
+    filteredAppMetricStream.print();
+
+    filteredAppMetricStream.foreachRDD(rdd -> {
+      rdd.foreach(
+        tuple2 -> {
+          long currentTime = System.currentTimeMillis();
+          EmaTechnique ema = emaTechniqueBroadcast.getValue();
+          if (currentTime > pitStartTime + pitTestInterval) {
+            LOG.info("Running Tukeys....");
+            pointInTimeADSystemBroadcast.getValue().runTukeysAndRefineEma(ema, currentTime);
+            pitStartTime = pitStartTime + pitTestInterval;
+          }
+
+          if (currentTime > ksStartTime + ksTestInterval) {
+            LOG.info("Running KS Test....");
+            trendADSystemBroadcast.getValue().runKSTest(currentTime);
+            ksStartTime = ksStartTime + ksTestInterval;
+          }
+
+          if (currentTime > hdevStartTime + hsdevInterval) {
+            LOG.info("Running HSdev Test....");
+            trendADSystemBroadcast.getValue().runHsdevMethod();
+            hdevStartTime = hdevStartTime + hsdevInterval;
+          }
+
+          TimelineMetrics metrics = tuple2._2();
+          for (TimelineMetric timelineMetric : metrics.getMetrics()) {
+            List<MetricAnomaly> anomalies = ema.test(timelineMetric);
+            metricsCollectorInterfaceBroadcast.getValue().publish(anomalies);
+          }
+        });
+    });
+
+    jssc.start();
+    jssc.awaitTermination();
+  }
+}
+
+
+
+

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricsCollectorInterface.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricsCollectorInterface.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricsCollectorInterface.java
new file mode 100644
index 0000000..7b3f63d
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+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/MetricsCollectorInterface.java
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+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+import org.apache.ambari.metrics.alertservice.prototype.methods.MetricAnomaly;
+import org.apache.commons.collections.CollectionUtils;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetrics;
+import org.codehaus.jackson.map.AnnotationIntrospector;
+import org.codehaus.jackson.map.ObjectMapper;
+import org.codehaus.jackson.map.ObjectReader;
+import org.codehaus.jackson.map.annotate.JsonSerialize;
+import org.codehaus.jackson.xc.JaxbAnnotationIntrospector;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.io.OutputStream;
+import java.io.Serializable;
+import java.net.HttpURLConnection;
+import java.net.InetAddress;
+import java.net.URL;
+import java.net.UnknownHostException;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.TreeMap;
+
+public class MetricsCollectorInterface implements Serializable {
+
+  private static String hostName = null;
+  private String instanceId = null;
+  public final static String serviceName = "anomaly-engine";
+  private String collectorHost;
+  private String protocol;
+  private String port;
+  private static final String WS_V1_TIMELINE_METRICS = "/ws/v1/timeline/metrics";
+  private static final Log LOG = LogFactory.getLog(MetricsCollectorInterface.class);
+  private static ObjectMapper mapper;
+  private final static ObjectReader timelineObjectReader;
+
+  static {
+    mapper = new ObjectMapper();
+    AnnotationIntrospector introspector = new JaxbAnnotationIntrospector();
+    mapper.setAnnotationIntrospector(introspector);
+    mapper.getSerializationConfig()
+      .withSerializationInclusion(JsonSerialize.Inclusion.NON_NULL);
+    timelineObjectReader = mapper.reader(TimelineMetrics.class);
+  }
+
+  public MetricsCollectorInterface(String collectorHost, String protocol, String port) {
+    this.collectorHost = collectorHost;
+    this.protocol = protocol;
+    this.port = port;
+    this.hostName = getDefaultLocalHostName();
+  }
+
+  public static String getDefaultLocalHostName() {
+
+    if (hostName != null) {
+      return hostName;
+    }
+
+    try {
+      return InetAddress.getLocalHost().getCanonicalHostName();
+    } catch (UnknownHostException e) {
+      LOG.info("Error getting host address");
+    }
+    return null;
+  }
+
+  public void publish(List<MetricAnomaly> metricAnomalies) {
+    if (CollectionUtils.isNotEmpty(metricAnomalies)) {
+      LOG.info("Sending metric anomalies of size : " + metricAnomalies.size());
+      List<TimelineMetric> metricList = getTimelineMetricList(metricAnomalies);
+      if (!metricList.isEmpty()) {
+        TimelineMetrics timelineMetrics = new TimelineMetrics();
+        timelineMetrics.setMetrics(metricList);
+        emitMetrics(timelineMetrics);
+      }
+    } else {
+      LOG.info("No anomalies to send.");
+    }
+  }
+
+  private List<TimelineMetric> getTimelineMetricList(List<MetricAnomaly> metricAnomalies) {
+    List<TimelineMetric> metrics = new ArrayList<>();
+
+    if (metricAnomalies.isEmpty()) {
+      return metrics;
+    }
+
+    for (MetricAnomaly anomaly : metricAnomalies) {
+      TimelineMetric timelineMetric = new TimelineMetric();
+      timelineMetric.setMetricName(anomaly.getMetricKey());
+      timelineMetric.setAppId(serviceName + "-" + anomaly.getMethodType());
+      timelineMetric.setInstanceId(null);
+      timelineMetric.setHostName(getDefaultLocalHostName());
+      timelineMetric.setStartTime(anomaly.getTimestamp());
+      HashMap<String, String> metadata = new HashMap<>();
+      metadata.put("method", anomaly.getMethodType());
+      metadata.put("anomaly-score", String.valueOf(anomaly.getAnomalyScore()));
+      timelineMetric.setMetadata(metadata);
+      TreeMap<Long,Double> metricValues = new TreeMap<>();
+      metricValues.put(anomaly.getTimestamp(), anomaly.getMetricValue());
+      timelineMetric.setMetricValues(metricValues);
+
+      metrics.add(timelineMetric);
+    }
+    return metrics;
+  }
+
+  public boolean emitMetrics(TimelineMetrics metrics) {
+    String connectUrl = constructTimelineMetricUri();
+    String jsonData = null;
+    LOG.info("EmitMetrics connectUrl = " + connectUrl);
+    try {
+      jsonData = mapper.writeValueAsString(metrics);
+      LOG.info(jsonData);
+    } catch (IOException e) {
+      LOG.error("Unable to parse metrics", e);
+    }
+    if (jsonData != null) {
+      return emitMetricsJson(connectUrl, jsonData);
+    }
+    return false;
+  }
+
+  private HttpURLConnection getConnection(String spec) throws IOException {
+    return (HttpURLConnection) new URL(spec).openConnection();
+  }
+
+  private boolean emitMetricsJson(String connectUrl, String jsonData) {
+    int timeout = 10000;
+    HttpURLConnection connection = null;
+    try {
+      if (connectUrl == null) {
+        throw new IOException("Unknown URL. Unable to connect to metrics collector.");
+      }
+      connection = getConnection(connectUrl);
+
+      connection.setRequestMethod("POST");
+      connection.setRequestProperty("Content-Type", "application/json");
+      connection.setRequestProperty("Connection", "Keep-Alive");
+      connection.setConnectTimeout(timeout);
+      connection.setReadTimeout(timeout);
+      connection.setDoOutput(true);
+
+      if (jsonData != null) {
+        try (OutputStream os = connection.getOutputStream()) {
+          os.write(jsonData.getBytes("UTF-8"));
+        }
+      }
+
+      int statusCode = connection.getResponseCode();
+
+      if (statusCode != 200) {
+        LOG.info("Unable to POST metrics to collector, " + connectUrl + ", " +
+          "statusCode = " + statusCode);
+      } else {
+        LOG.info("Metrics posted to Collector " + connectUrl);
+      }
+      return true;
+    } catch (IOException ioe) {
+      LOG.error(ioe.getMessage());
+    }
+    return false;
+  }
+
+  private String constructTimelineMetricUri() {
+    StringBuilder sb = new StringBuilder(protocol);
+    sb.append("://");
+    sb.append(collectorHost);
+    sb.append(":");
+    sb.append(port);
+    sb.append(WS_V1_TIMELINE_METRICS);
+    return sb.toString();
+  }
+
+  public TimelineMetrics fetchMetrics(String metricName,
+                                      String appId,
+                                      String hostname,
+                                      long startime,
+                                      long endtime) {
+
+    String url = constructTimelineMetricUri() + "?metricNames=" + metricName + "&appId=" + appId +
+      "&hostname=" + hostname + "&startTime=" + startime + "&endTime=" + endtime;
+    LOG.info("Fetch metrics URL : " + url);
+
+    URL obj = null;
+    BufferedReader in = null;
+    TimelineMetrics timelineMetrics = new TimelineMetrics();
+
+    try {
+      obj = new URL(url);
+      HttpURLConnection con = (HttpURLConnection) obj.openConnection();
+      con.setRequestMethod("GET");
+      int responseCode = con.getResponseCode();
+      LOG.info("Sending 'GET' request to URL : " + url);
+      LOG.info("Response Code : " + responseCode);
+
+      in = new BufferedReader(
+        new InputStreamReader(con.getInputStream()));
+      timelineMetrics = timelineObjectReader.readValue(in);
+    } catch (Exception e) {
+      LOG.error(e);
+    } finally {
+      if (in != null) {
+        try {
+          in.close();
+        } catch (IOException e) {
+          LOG.warn(e);
+        }
+      }
+    }
+
+    LOG.info("Fetched " + timelineMetrics.getMetrics().size() + " metrics.");
+    return timelineMetrics;
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/PointInTimeADSystem.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/PointInTimeADSystem.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/PointInTimeADSystem.java
new file mode 100644
index 0000000..b4a8593
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+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/PointInTimeADSystem.java
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+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+import org.apache.ambari.metrics.alertservice.prototype.common.DataSeries;
+import org.apache.ambari.metrics.alertservice.prototype.common.ResultSet;
+import org.apache.ambari.metrics.alertservice.prototype.methods.ema.EmaModel;
+import org.apache.ambari.metrics.alertservice.prototype.methods.ema.EmaTechnique;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetrics;
+
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Date;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.TreeMap;
+
+public class PointInTimeADSystem implements Serializable {
+
+  //private EmaTechnique emaTechnique;
+  private MetricsCollectorInterface metricsCollectorInterface;
+  private Map<String, Double> tukeysNMap;
+  private double defaultTukeysN = 3;
+
+  private long testIntervalMillis = 5*60*1000; //10mins
+  private long trainIntervalMillis = 15*60*1000; //1hour
+
+  private static final Log LOG = LogFactory.getLog(PointInTimeADSystem.class);
+
+  private AmbariServerInterface ambariServerInterface;
+  private int sensitivity = 50;
+  private int minSensitivity = 0;
+  private int maxSensitivity = 10;
+
+  public PointInTimeADSystem(MetricsCollectorInterface metricsCollectorInterface, double defaultTukeysN,
+                             long testIntervalMillis, long trainIntervalMillis, String ambariServerHost, String clusterName) {
+    this.metricsCollectorInterface = metricsCollectorInterface;
+    this.defaultTukeysN = defaultTukeysN;
+    this.tukeysNMap = new HashMap<>();
+    this.testIntervalMillis = testIntervalMillis;
+    this.trainIntervalMillis = trainIntervalMillis;
+    this.ambariServerInterface = new AmbariServerInterface(ambariServerHost, clusterName);
+    LOG.info("Starting PointInTimeADSystem...");
+  }
+
+  public void runTukeysAndRefineEma(EmaTechnique emaTechnique, long startTime) {
+    LOG.info("Running Tukeys for test data interval [" + new Date(startTime - testIntervalMillis) + " : " + new Date(startTime) + "], with train data period [" + new Date(startTime  - testIntervalMillis - trainIntervalMillis) + " : " + new Date(startTime - testIntervalMillis) + "]");
+
+    int requiredSensivity = ambariServerInterface.getPointInTimeSensitivity();
+    if (requiredSensivity == -1 || requiredSensivity == sensitivity) {
+      LOG.info("No change in sensitivity needed.");
+    } else {
+      LOG.info("Current tukey's N value = " + defaultTukeysN);
+      if (requiredSensivity > sensitivity) {
+        int targetSensitivity = Math.min(maxSensitivity, requiredSensivity);
+        while (sensitivity < targetSensitivity) {
+          defaultTukeysN = defaultTukeysN + defaultTukeysN * 0.1;
+          sensitivity++;
+        }
+      } else {
+        int targetSensitivity = Math.max(minSensitivity, requiredSensivity);
+        while (sensitivity > targetSensitivity) {
+          defaultTukeysN = defaultTukeysN - defaultTukeysN * 0.1;
+          sensitivity--;
+        }
+      }
+      LOG.info("New tukey's N value = " + defaultTukeysN);
+    }
+
+    TimelineMetrics timelineMetrics = new TimelineMetrics();
+    for (String metricKey : emaTechnique.getTrackedEmas().keySet()) {
+      LOG.info("EMA key = " + metricKey);
+      EmaModel emaModel = emaTechnique.getTrackedEmas().get(metricKey);
+      String metricName = emaModel.getMetricName();
+      String appId = emaModel.getAppId();
+      String hostname = emaModel.getHostname();
+
+      TimelineMetrics tukeysData = metricsCollectorInterface.fetchMetrics(metricName, appId, hostname, startTime - (testIntervalMillis + trainIntervalMillis),
+        startTime);
+
+      if (tukeysData.getMetrics().isEmpty()) {
+        LOG.info("No metrics fetched for Tukeys, metricKey = " + metricKey);
+        continue;
+      }
+
+      List<Double> trainTsList = new ArrayList<>();
+      List<Double> trainDataList = new ArrayList<>();
+      List<Double> testTsList = new ArrayList<>();
+      List<Double> testDataList = new ArrayList<>();
+
+      for (TimelineMetric metric : tukeysData.getMetrics()) {
+        for (Long timestamp : metric.getMetricValues().keySet()) {
+          if (timestamp <= (startTime - testIntervalMillis)) {
+            trainDataList.add(metric.getMetricValues().get(timestamp));
+            trainTsList.add((double)timestamp);
+          } else {
+            testDataList.add(metric.getMetricValues().get(timestamp));
+            testTsList.add((double)timestamp);
+          }
+        }
+      }
+
+      if (trainDataList.isEmpty() || testDataList.isEmpty() || trainDataList.size() < testDataList.size()) {
+        LOG.info("Not enough train/test data to perform analysis.");
+        continue;
+      }
+
+      String tukeysTrainSeries = "tukeysTrainSeries";
+      double[] trainTs = new double[trainTsList.size()];
+      double[] trainData = new double[trainTsList.size()];
+      for (int i = 0; i < trainTs.length; i++) {
+        trainTs[i] = trainTsList.get(i);
+        trainData[i] = trainDataList.get(i);
+      }
+
+      String tukeysTestSeries = "tukeysTestSeries";
+      double[] testTs = new double[testTsList.size()];
+      double[] testData = new double[testTsList.size()];
+      for (int i = 0; i < testTs.length; i++) {
+        testTs[i] = testTsList.get(i);
+        testData[i] = testDataList.get(i);
+      }
+
+      LOG.info("Train Size = " + trainTs.length + ", Test Size = " + testTs.length);
+
+      DataSeries tukeysTrainData = new DataSeries(tukeysTrainSeries, trainTs, trainData);
+      DataSeries tukeysTestData = new DataSeries(tukeysTestSeries, testTs, testData);
+
+      if (!tukeysNMap.containsKey(metricKey)) {
+        tukeysNMap.put(metricKey, defaultTukeysN);
+      }
+
+      Map<String, String> configs = new HashMap<>();
+      configs.put("tukeys.n", String.valueOf(tukeysNMap.get(metricKey)));
+
+      ResultSet rs = RFunctionInvoker.tukeys(tukeysTrainData, tukeysTestData, configs);
+
+      List<TimelineMetric> tukeysMetrics = getAsTimelineMetric(rs, metricName, appId, hostname);
+      LOG.info("Tukeys anomalies size : " + tukeysMetrics.size());
+      TreeMap<Long, Double> tukeysMetricValues = new TreeMap<>();
+
+      for (TimelineMetric tukeysMetric : tukeysMetrics) {
+        tukeysMetricValues.putAll(tukeysMetric.getMetricValues());
+        timelineMetrics.addOrMergeTimelineMetric(tukeysMetric);
+      }
+
+      TimelineMetrics emaData = metricsCollectorInterface.fetchMetrics(metricKey, MetricsCollectorInterface.serviceName+"-ema", MetricsCollectorInterface.getDefaultLocalHostName(), startTime - testIntervalMillis, startTime);
+      TreeMap<Long, Double> emaMetricValues = new TreeMap();
+      if (!emaData.getMetrics().isEmpty()) {
+        emaMetricValues = emaData.getMetrics().get(0).getMetricValues();
+      }
+
+      LOG.info("Ema anomalies size : " + emaMetricValues.size());
+      int tp = 0;
+      int tn = 0;
+      int fp = 0;
+      int fn = 0;
+
+      for (double ts : testTs) {
+        long timestamp = (long) ts;
+        if (tukeysMetricValues.containsKey(timestamp)) {
+          if (emaMetricValues.containsKey(timestamp)) {
+            tp++;
+          } else {
+            fn++;
+          }
+        } else {
+          if (emaMetricValues.containsKey(timestamp)) {
+            fp++;
+          } else {
+            tn++;
+          }
+        }
+      }
+
+      double recall = (double) tp / (double) (tp + fn);
+      double precision = (double) tp / (double) (tp + fp);
+      LOG.info("----------------------------");
+      LOG.info("Precision Recall values for " + metricKey);
+      LOG.info("tp=" + tp + ", fp=" + fp + ", tn=" + tn + ", fn=" + fn);
+      LOG.info("----------------------------");
+
+      if (recall < 0.5) {
+        LOG.info("Increasing EMA sensitivity by 10%");
+        emaModel.updateModel(true, 10);
+      } else if (precision < 0.5) {
+        LOG.info("Decreasing EMA sensitivity by 10%");
+        emaModel.updateModel(false, 10);
+      }
+
+    }
+
+    if (emaTechnique.getTrackedEmas().isEmpty()){
+      LOG.info("No EMA Technique keys tracked!!!!");
+    }
+
+    if (!timelineMetrics.getMetrics().isEmpty()) {
+      metricsCollectorInterface.emitMetrics(timelineMetrics);
+    }
+  }
+
+  private static List<TimelineMetric> getAsTimelineMetric(ResultSet result, String metricName, String appId, String hostname) {
+
+    List<TimelineMetric> timelineMetrics = new ArrayList<>();
+
+    if (result == null) {
+      LOG.info("ResultSet from R call is null!!");
+      return null;
+    }
+
+    if (result.resultset.size() > 0) {
+      double[] ts = result.resultset.get(0);
+      double[] metrics = result.resultset.get(1);
+      double[] anomalyScore = result.resultset.get(2);
+      for (int i = 0; i < ts.length; i++) {
+        TimelineMetric timelineMetric = new TimelineMetric();
+        timelineMetric.setMetricName(metricName + "_" + appId + "_" + hostname);
+        timelineMetric.setHostName(MetricsCollectorInterface.getDefaultLocalHostName());
+        timelineMetric.setAppId(MetricsCollectorInterface.serviceName + "-tukeys");
+        timelineMetric.setInstanceId(null);
+        timelineMetric.setStartTime((long) ts[i]);
+        TreeMap<Long, Double> metricValues = new TreeMap<>();
+        metricValues.put((long) ts[i], metrics[i]);
+
+        HashMap<String, String> metadata = new HashMap<>();
+        metadata.put("method", "tukeys");
+        metadata.put("anomaly-score", String.valueOf(anomalyScore[i]));
+        timelineMetric.setMetadata(metadata);
+
+        timelineMetric.setMetricValues(metricValues);
+        timelineMetrics.add(timelineMetric);
+      }
+    }
+
+    return timelineMetrics;
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/RFunctionInvoker.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/RFunctionInvoker.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/RFunctionInvoker.java
new file mode 100644
index 0000000..4fdf27d
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/RFunctionInvoker.java
@@ -0,0 +1,222 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+
+import org.apache.ambari.metrics.alertservice.prototype.common.ResultSet;
+import org.apache.ambari.metrics.alertservice.prototype.common.DataSeries;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.rosuda.JRI.REXP;
+import org.rosuda.JRI.RVector;
+import org.rosuda.JRI.Rengine;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+
+public class RFunctionInvoker {
+
+  static final Log LOG = LogFactory.getLog(RFunctionInvoker.class);
+  public static Rengine r = new Rengine(new String[]{"--no-save"}, false, null);
+  private static String rScriptDir = "/usr/lib/ambari-metrics-collector/R-scripts";
+
+  private static void loadDataSets(Rengine r, DataSeries trainData, DataSeries testData) {
+    r.assign("train_ts", trainData.ts);
+    r.assign("train_x", trainData.values);
+    r.eval("train_data <- data.frame(train_ts,train_x)");
+    r.eval("names(train_data) <- c(\"TS\", " + trainData.seriesName + ")");
+
+    r.assign("test_ts", testData.ts);
+    r.assign("test_x", testData.values);
+    r.eval("test_data <- data.frame(test_ts,test_x)");
+    r.eval("names(test_data) <- c(\"TS\", " + testData.seriesName + ")");
+  }
+
+  public static void setScriptsDir(String dir) {
+    rScriptDir = dir;
+  }
+
+  public static ResultSet executeMethod(String methodType, DataSeries trainData, DataSeries testData, Map<String, String> configs) {
+
+    ResultSet result;
+    switch (methodType) {
+      case "tukeys":
+        result = tukeys(trainData, testData, configs);
+        break;
+      case "ema":
+        result = ema_global(trainData, testData, configs);
+        break;
+      case "ks":
+        result = ksTest(trainData, testData, configs);
+        break;
+      case "hsdev":
+        result = hsdev(trainData, testData, configs);
+        break;
+      default:
+        result = tukeys(trainData, testData, configs);
+        break;
+    }
+    return result;
+  }
+
+  public static ResultSet tukeys(DataSeries trainData, DataSeries testData, Map<String, String> configs) {
+    try {
+
+      REXP exp1 = r.eval("source('" + rScriptDir + "/tukeys.r" + "')");
+
+      double n = Double.parseDouble(configs.get("tukeys.n"));
+      r.eval("n <- " + n);
+
+      loadDataSets(r, trainData, testData);
+
+      r.eval("an <- ams_tukeys(train_data, test_data, n)");
+      REXP exp = r.eval("an");
+      RVector cont = (RVector) exp.getContent();
+      List<double[]> result = new ArrayList();
+      for (int i = 0; i < cont.size(); i++) {
+        result.add(cont.at(i).asDoubleArray());
+      }
+      return new ResultSet(result);
+    } catch (Exception e) {
+      LOG.error(e);
+    } finally {
+      r.end();
+    }
+    return null;
+  }
+
+  public static ResultSet ema_global(DataSeries trainData, DataSeries testData, Map<String, String> configs) {
+    try {
+      r.eval("source('" + rScriptDir + "/ema.r" + "')");
+
+      int n = Integer.parseInt(configs.get("ema.n"));
+      r.eval("n <- " + n);
+
+      double w = Double.parseDouble(configs.get("ema.w"));
+      r.eval("w <- " + w);
+
+      loadDataSets(r, trainData, testData);
+
+      r.eval("an <- ema_global(train_data, test_data, w, n)");
+      REXP exp = r.eval("an");
+      RVector cont = (RVector) exp.getContent();
+      List<double[]> result = new ArrayList();
+      for (int i = 0; i < cont.size(); i++) {
+        result.add(cont.at(i).asDoubleArray());
+      }
+      return new ResultSet(result);
+
+    } catch (Exception e) {
+      LOG.error(e);
+    } finally {
+      r.end();
+    }
+    return null;
+  }
+
+  public static ResultSet ema_daily(DataSeries trainData, DataSeries testData, Map<String, String> configs) {
+    try {
+      r.eval("source('" + rScriptDir + "/ema.r" + "')");
+
+      int n = Integer.parseInt(configs.get("ema.n"));
+      r.eval("n <- " + n);
+
+      double w = Double.parseDouble(configs.get("ema.w"));
+      r.eval("w <- " + w);
+
+      loadDataSets(r, trainData, testData);
+
+      r.eval("an <- ema_daily(train_data, test_data, w, n)");
+      REXP exp = r.eval("an");
+      RVector cont = (RVector) exp.getContent();
+      List<double[]> result = new ArrayList();
+      for (int i = 0; i < cont.size(); i++) {
+        result.add(cont.at(i).asDoubleArray());
+      }
+      return new ResultSet(result);
+
+    } catch (Exception e) {
+      LOG.error(e);
+    } finally {
+      r.end();
+    }
+    return null;
+  }
+
+  public static ResultSet ksTest(DataSeries trainData, DataSeries testData, Map<String, String> configs) {
+    try {
+      r.eval("source('" + rScriptDir + "/kstest.r" + "')");
+
+      double p_value = Double.parseDouble(configs.get("ks.p_value"));
+      r.eval("p_value <- " + p_value);
+
+      loadDataSets(r, trainData, testData);
+
+      r.eval("an <- ams_ks(train_data, test_data, p_value)");
+      REXP exp = r.eval("an");
+      RVector cont = (RVector) exp.getContent();
+      List<double[]> result = new ArrayList();
+      for (int i = 0; i < cont.size(); i++) {
+        result.add(cont.at(i).asDoubleArray());
+      }
+      return new ResultSet(result);
+
+    } catch (Exception e) {
+      LOG.error(e);
+    } finally {
+      r.end();
+    }
+    return null;
+  }
+
+  public static ResultSet hsdev(DataSeries trainData, DataSeries testData, Map<String, String> configs) {
+    try {
+      r.eval("source('" + rScriptDir + "/hsdev.r" + "')");
+
+      int n = Integer.parseInt(configs.get("hsdev.n"));
+      r.eval("n <- " + n);
+
+      int nhp = Integer.parseInt(configs.get("hsdev.nhp"));
+      r.eval("nhp <- " + nhp);
+
+      long interval = Long.parseLong(configs.get("hsdev.interval"));
+      r.eval("interval <- " + interval);
+
+      long period = Long.parseLong(configs.get("hsdev.period"));
+      r.eval("period <- " + period);
+
+      loadDataSets(r, trainData, testData);
+
+      r.eval("an2 <- hsdev_daily(train_data, test_data, n, nhp, interval, period)");
+      REXP exp = r.eval("an2");
+      RVector cont = (RVector) exp.getContent();
+
+      List<double[]> result = new ArrayList();
+      for (int i = 0; i < cont.size(); i++) {
+        result.add(cont.at(i).asDoubleArray());
+      }
+      return new ResultSet(result);
+    } catch (Exception e) {
+      LOG.error(e);
+    } finally {
+      r.end();
+    }
+    return null;
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TestSeriesInputRequest.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TestSeriesInputRequest.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TestSeriesInputRequest.java
new file mode 100644
index 0000000..7485f01
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TestSeriesInputRequest.java
@@ -0,0 +1,88 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+import org.apache.htrace.fasterxml.jackson.core.JsonProcessingException;
+import org.apache.htrace.fasterxml.jackson.databind.ObjectMapper;
+
+import javax.xml.bind.annotation.XmlRootElement;
+import java.util.Collections;
+import java.util.Map;
+
+@XmlRootElement
+public class TestSeriesInputRequest {
+
+  private String seriesName;
+  private String seriesType;
+  private Map<String, String> configs;
+
+  public TestSeriesInputRequest() {
+  }
+
+  public TestSeriesInputRequest(String seriesName, String seriesType, Map<String, String> configs) {
+    this.seriesName = seriesName;
+    this.seriesType = seriesType;
+    this.configs = configs;
+  }
+
+  public String getSeriesName() {
+    return seriesName;
+  }
+
+  public void setSeriesName(String seriesName) {
+    this.seriesName = seriesName;
+  }
+
+  public String getSeriesType() {
+    return seriesType;
+  }
+
+  public void setSeriesType(String seriesType) {
+    this.seriesType = seriesType;
+  }
+
+  public Map<String, String> getConfigs() {
+    return configs;
+  }
+
+  public void setConfigs(Map<String, String> configs) {
+    this.configs = configs;
+  }
+
+  @Override
+  public boolean equals(Object o) {
+    TestSeriesInputRequest anotherInput = (TestSeriesInputRequest)o;
+    return anotherInput.getSeriesName().equals(this.getSeriesName());
+  }
+
+  @Override
+  public int hashCode() {
+    return seriesName.hashCode();
+  }
+
+  public static void main(String[] args) {
+
+    ObjectMapper objectMapper = new ObjectMapper();
+    TestSeriesInputRequest testSeriesInputRequest = new TestSeriesInputRequest("test", "ema", Collections.singletonMap("key","value"));
+    try {
+      System.out.print(objectMapper.writeValueAsString(testSeriesInputRequest));
+    } catch (JsonProcessingException e) {
+      e.printStackTrace();
+    }
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendADSystem.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendADSystem.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendADSystem.java
new file mode 100644
index 0000000..1534b55
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendADSystem.java
@@ -0,0 +1,331 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+import org.apache.ambari.metrics.alertservice.prototype.common.DataSeries;
+import org.apache.ambari.metrics.alertservice.prototype.methods.MetricAnomaly;
+import org.apache.ambari.metrics.alertservice.prototype.methods.hsdev.HsdevTechnique;
+import org.apache.ambari.metrics.alertservice.prototype.methods.kstest.KSTechnique;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetrics;
+
+import java.io.BufferedReader;
+import java.io.FileReader;
+import java.io.IOException;
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.Date;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.TreeMap;
+
+public class TrendADSystem implements Serializable {
+
+  private MetricsCollectorInterface metricsCollectorInterface;
+  private List<TrendMetric> trendMetrics;
+
+  private long ksTestIntervalMillis = 10 * 60 * 1000;
+  private long ksTrainIntervalMillis = 10 * 60 * 1000;
+  private KSTechnique ksTechnique;
+
+  private HsdevTechnique hsdevTechnique;
+  private int hsdevNumHistoricalPeriods = 3;
+
+  private Map<KsSingleRunKey, MetricAnomaly> trackedKsAnomalies = new HashMap<>();
+  private static final Log LOG = LogFactory.getLog(TrendADSystem.class);
+  private String inputFile = "";
+
+  public TrendADSystem(MetricsCollectorInterface metricsCollectorInterface,
+                       long ksTestIntervalMillis,
+                       long ksTrainIntervalMillis,
+                       int hsdevNumHistoricalPeriods,
+                       String inputFileName) {
+
+    this.metricsCollectorInterface = metricsCollectorInterface;
+    this.ksTestIntervalMillis = ksTestIntervalMillis;
+    this.ksTrainIntervalMillis = ksTrainIntervalMillis;
+    this.hsdevNumHistoricalPeriods = hsdevNumHistoricalPeriods;
+
+    this.ksTechnique = new KSTechnique();
+    this.hsdevTechnique = new HsdevTechnique();
+
+    trendMetrics = new ArrayList<>();
+    this.inputFile = inputFileName;
+    readInputFile(inputFileName);
+  }
+
+  public void runKSTest(long currentEndTime) {
+    readInputFile(inputFile);
+
+    long ksTestIntervalStartTime = currentEndTime - ksTestIntervalMillis;
+    LOG.info("Running KS Test for test data interval [" + new Date(ksTestIntervalStartTime) + " : " +
+      new Date(currentEndTime) + "], with train data period [" + new Date(ksTestIntervalStartTime - ksTrainIntervalMillis)
+      + " : " + new Date(ksTestIntervalStartTime) + "]");
+
+    for (TrendMetric metric : trendMetrics) {
+      String metricName = metric.metricName;
+      String appId = metric.appId;
+      String hostname = metric.hostname;
+      String key = metricName + "_" + appId + "_" + hostname;
+
+      TimelineMetrics ksData = metricsCollectorInterface.fetchMetrics(metricName, appId, hostname, ksTestIntervalStartTime - ksTrainIntervalMillis,
+        currentEndTime);
+
+      if (ksData.getMetrics().isEmpty()) {
+        LOG.info("No metrics fetched for KS, metricKey = " + key);
+        continue;
+      }
+
+      List<Double> trainTsList = new ArrayList<>();
+      List<Double> trainDataList = new ArrayList<>();
+      List<Double> testTsList = new ArrayList<>();
+      List<Double> testDataList = new ArrayList<>();
+
+      for (TimelineMetric timelineMetric : ksData.getMetrics()) {
+        for (Long timestamp : timelineMetric.getMetricValues().keySet()) {
+          if (timestamp <= ksTestIntervalStartTime) {
+            trainDataList.add(timelineMetric.getMetricValues().get(timestamp));
+            trainTsList.add((double) timestamp);
+          } else {
+            testDataList.add(timelineMetric.getMetricValues().get(timestamp));
+            testTsList.add((double) timestamp);
+          }
+        }
+      }
+
+      if (trainDataList.isEmpty() || testDataList.isEmpty() || trainDataList.size() < testDataList.size()) {
+        LOG.info("Not enough train/test data to perform KS analysis.");
+        continue;
+      }
+
+      String ksTrainSeries = "KSTrainSeries";
+      double[] trainTs = new double[trainTsList.size()];
+      double[] trainData = new double[trainTsList.size()];
+      for (int i = 0; i < trainTs.length; i++) {
+        trainTs[i] = trainTsList.get(i);
+        trainData[i] = trainDataList.get(i);
+      }
+
+      String ksTestSeries = "KSTestSeries";
+      double[] testTs = new double[testTsList.size()];
+      double[] testData = new double[testTsList.size()];
+      for (int i = 0; i < testTs.length; i++) {
+        testTs[i] = testTsList.get(i);
+        testData[i] = testDataList.get(i);
+      }
+
+      LOG.info("Train Size = " + trainTs.length + ", Test Size = " + testTs.length);
+
+      DataSeries ksTrainData = new DataSeries(ksTrainSeries, trainTs, trainData);
+      DataSeries ksTestData = new DataSeries(ksTestSeries, testTs, testData);
+
+      MetricAnomaly metricAnomaly = ksTechnique.runKsTest(key, ksTrainData, ksTestData);
+      if (metricAnomaly == null) {
+        LOG.info("No anomaly from KS test.");
+      } else {
+        LOG.info("Found Anomaly in KS Test. Publishing KS Anomaly metric....");
+        TimelineMetric timelineMetric = getAsTimelineMetric(metricAnomaly,
+          ksTestIntervalStartTime, currentEndTime, ksTestIntervalStartTime - ksTrainIntervalMillis, ksTestIntervalStartTime);
+        TimelineMetrics timelineMetrics = new TimelineMetrics();
+        timelineMetrics.addOrMergeTimelineMetric(timelineMetric);
+        metricsCollectorInterface.emitMetrics(timelineMetrics);
+
+        trackedKsAnomalies.put(new KsSingleRunKey(ksTestIntervalStartTime, currentEndTime, metricName, appId, hostname), metricAnomaly);
+      }
+    }
+
+    if (trendMetrics.isEmpty()) {
+      LOG.info("No Trend metrics tracked!!!!");
+    }
+
+  }
+
+  private TimelineMetric getAsTimelineMetric(MetricAnomaly metricAnomaly,
+                                   long testStart,
+                                   long testEnd,
+                                   long trainStart,
+                                   long trainEnd) {
+
+    TimelineMetric timelineMetric = new TimelineMetric();
+    timelineMetric.setMetricName(metricAnomaly.getMetricKey());
+    timelineMetric.setAppId(MetricsCollectorInterface.serviceName + "-" + metricAnomaly.getMethodType());
+    timelineMetric.setInstanceId(null);
+    timelineMetric.setHostName(MetricsCollectorInterface.getDefaultLocalHostName());
+    timelineMetric.setStartTime(testEnd);
+    HashMap<String, String> metadata = new HashMap<>();
+    metadata.put("method", metricAnomaly.getMethodType());
+    metadata.put("anomaly-score", String.valueOf(metricAnomaly.getAnomalyScore()));
+    metadata.put("test-start-time", String.valueOf(testStart));
+    metadata.put("train-start-time", String.valueOf(trainStart));
+    metadata.put("train-end-time", String.valueOf(trainEnd));
+    timelineMetric.setMetadata(metadata);
+    TreeMap<Long,Double> metricValues = new TreeMap<>();
+    metricValues.put(testEnd, metricAnomaly.getMetricValue());
+    timelineMetric.setMetricValues(metricValues);
+    return timelineMetric;
+
+  }
+  public void runHsdevMethod() {
+
+    List<TimelineMetric> hsdevMetricAnomalies = new ArrayList<>();
+
+    for (KsSingleRunKey ksSingleRunKey : trackedKsAnomalies.keySet()) {
+
+      long hsdevTestEnd = ksSingleRunKey.endTime;
+      long hsdevTestStart = ksSingleRunKey.startTime;
+
+      long period = hsdevTestEnd - hsdevTestStart;
+
+      long hsdevTrainStart = hsdevTestStart - (hsdevNumHistoricalPeriods) * period;
+      long hsdevTrainEnd = hsdevTestStart;
+
+      LOG.info("Running HSdev Test for test data interval [" + new Date(hsdevTestStart) + " : " +
+        new Date(hsdevTestEnd) + "], with train data period [" + new Date(hsdevTrainStart)
+        + " : " + new Date(hsdevTrainEnd) + "]");
+
+      String metricName = ksSingleRunKey.metricName;
+      String appId = ksSingleRunKey.appId;
+      String hostname = ksSingleRunKey.hostname;
+      String key = metricName + "_" + appId + "_" + hostname;
+
+      TimelineMetrics hsdevData = metricsCollectorInterface.fetchMetrics(
+        metricName,
+        appId,
+        hostname,
+        hsdevTrainStart,
+        hsdevTestEnd);
+
+      if (hsdevData.getMetrics().isEmpty()) {
+        LOG.info("No metrics fetched for HSDev, metricKey = " + key);
+        continue;
+      }
+
+      List<Double> trainTsList = new ArrayList<>();
+      List<Double> trainDataList = new ArrayList<>();
+      List<Double> testTsList = new ArrayList<>();
+      List<Double> testDataList = new ArrayList<>();
+
+      for (TimelineMetric timelineMetric : hsdevData.getMetrics()) {
+        for (Long timestamp : timelineMetric.getMetricValues().keySet()) {
+          if (timestamp <= hsdevTestStart) {
+            trainDataList.add(timelineMetric.getMetricValues().get(timestamp));
+            trainTsList.add((double) timestamp);
+          } else {
+            testDataList.add(timelineMetric.getMetricValues().get(timestamp));
+            testTsList.add((double) timestamp);
+          }
+        }
+      }
+
+      if (trainDataList.isEmpty() || testDataList.isEmpty() || trainDataList.size() < testDataList.size()) {
+        LOG.info("Not enough train/test data to perform Hsdev analysis.");
+        continue;
+      }
+
+      String hsdevTrainSeries = "HsdevTrainSeries";
+      double[] trainTs = new double[trainTsList.size()];
+      double[] trainData = new double[trainTsList.size()];
+      for (int i = 0; i < trainTs.length; i++) {
+        trainTs[i] = trainTsList.get(i);
+        trainData[i] = trainDataList.get(i);
+      }
+
+      String hsdevTestSeries = "HsdevTestSeries";
+      double[] testTs = new double[testTsList.size()];
+      double[] testData = new double[testTsList.size()];
+      for (int i = 0; i < testTs.length; i++) {
+        testTs[i] = testTsList.get(i);
+        testData[i] = testDataList.get(i);
+      }
+
+      LOG.info("Train Size = " + trainTs.length + ", Test Size = " + testTs.length);
+
+      DataSeries hsdevTrainData = new DataSeries(hsdevTrainSeries, trainTs, trainData);
+      DataSeries hsdevTestData = new DataSeries(hsdevTestSeries, testTs, testData);
+
+      MetricAnomaly metricAnomaly = hsdevTechnique.runHsdevTest(key, hsdevTrainData, hsdevTestData);
+      if (metricAnomaly == null) {
+        LOG.info("No anomaly from Hsdev test. Mismatch between KS and HSDev. ");
+        ksTechnique.updateModel(key, false, 10);
+      } else {
+        LOG.info("Found Anomaly in Hsdev Test. This confirms KS anomaly.");
+        hsdevMetricAnomalies.add(getAsTimelineMetric(metricAnomaly,
+          hsdevTestStart, hsdevTestEnd, hsdevTrainStart, hsdevTrainEnd));
+      }
+    }
+    clearTrackedKsRunKeys();
+
+    if (!hsdevMetricAnomalies.isEmpty()) {
+      LOG.info("Publishing Hsdev Anomalies....");
+      TimelineMetrics timelineMetrics = new TimelineMetrics();
+      timelineMetrics.setMetrics(hsdevMetricAnomalies);
+      metricsCollectorInterface.emitMetrics(timelineMetrics);
+    }
+  }
+
+  private void clearTrackedKsRunKeys() {
+    trackedKsAnomalies.clear();
+  }
+
+  private void readInputFile(String fileName) {
+    trendMetrics.clear();
+    try (BufferedReader br = new BufferedReader(new FileReader(fileName))) {
+      for (String line; (line = br.readLine()) != null; ) {
+        String[] splits = line.split(",");
+        LOG.info("Adding a new metric to track in Trend AD system : " + splits[0]);
+        trendMetrics.add(new TrendMetric(splits[0], splits[1], splits[2]));
+      }
+    } catch (IOException e) {
+      LOG.error("Error reading input file : " + e);
+    }
+  }
+
+  class KsSingleRunKey implements Serializable{
+
+    long startTime;
+    long endTime;
+    String metricName;
+    String appId;
+    String hostname;
+
+    public KsSingleRunKey(long startTime, long endTime, String metricName, String appId, String hostname) {
+      this.startTime = startTime;
+      this.endTime = endTime;
+      this.metricName = metricName;
+      this.appId = appId;
+      this.hostname = hostname;
+    }
+  }
+
+  /*
+          boolean isPresent = false;
+        for (TrendMetric trendMetric : trendMetrics) {
+          if (trendMetric.metricName.equalsIgnoreCase(splits[0])) {
+            isPresent = true;
+          }
+        }
+        if (!isPresent) {
+          LOG.info("Adding a new metric to track in Trend AD system : " + splits[0]);
+          trendMetrics.add(new TrendMetric(splits[0], splits[1], splits[2]));
+        }
+   */
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendMetric.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendMetric.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendMetric.java
new file mode 100644
index 0000000..3bead8b
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/TrendMetric.java
@@ -0,0 +1,33 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype;
+
+import java.io.Serializable;
+
+public class TrendMetric implements Serializable {
+
+  String metricName;
+  String appId;
+  String hostname;
+
+  public TrendMetric(String metricName, String appId, String hostname) {
+    this.metricName = metricName;
+    this.appId = appId;
+    this.hostname = hostname;
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/DataSeries.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/DataSeries.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/DataSeries.java
new file mode 100644
index 0000000..eb19857
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/DataSeries.java
@@ -0,0 +1,38 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.common;
+
+import java.util.Arrays;
+
+public class DataSeries {
+
+    public String seriesName;
+    public double[] ts;
+    public double[] values;
+
+    public DataSeries(String seriesName, double[] ts, double[] values) {
+        this.seriesName = seriesName;
+        this.ts = ts;
+        this.values = values;
+    }
+
+    @Override
+    public String toString() {
+        return seriesName + Arrays.toString(ts) + Arrays.toString(values);
+    }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/ResultSet.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/ResultSet.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/ResultSet.java
new file mode 100644
index 0000000..101b0e9
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/ResultSet.java
@@ -0,0 +1,43 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.common;
+
+
+import java.util.ArrayList;
+import java.util.List;
+
+public class ResultSet {
+
+    public List<double[]> resultset = new ArrayList<>();
+
+    public ResultSet(List<double[]> resultset) {
+        this.resultset = resultset;
+    }
+
+    public void print() {
+        System.out.println("Result : ");
+        if (!resultset.isEmpty()) {
+            for (int i = 0; i<resultset.get(0).length;i++) {
+                for (double[] entity : resultset) {
+                    System.out.print(entity[i] + " ");
+                }
+                System.out.println();
+            }
+        }
+    }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/StatisticUtils.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/StatisticUtils.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/StatisticUtils.java
new file mode 100644
index 0000000..4ea4ac5
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/common/StatisticUtils.java
@@ -0,0 +1,62 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.common;
+
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.Collections;
+
+public class StatisticUtils {
+
+  public static double mean(double[] values) {
+    double sum = 0;
+    for (double d : values) {
+      sum += d;
+    }
+    return sum / values.length;
+  }
+
+  public static double variance(double[] values) {
+    double avg =  mean(values);
+    double variance = 0;
+    for (double d : values) {
+      variance += Math.pow(d - avg, 2.0);
+    }
+    return variance;
+  }
+
+  public static double sdev(double[]  values, boolean useBesselsCorrection) {
+    double variance = variance(values);
+    int n = (useBesselsCorrection) ? values.length - 1 : values.length;
+    return Math.sqrt(variance / n);
+  }
+
+  public static double median(double[] values) {
+    double[] clonedValues = Arrays.copyOf(values, values.length);
+    Arrays.sort(clonedValues);
+    int n = values.length;
+
+    if (n % 2 != 0) {
+      return clonedValues[(n-1)/2];
+    } else {
+      return ( clonedValues[(n-1)/2] + clonedValues[n/2] ) / 2;
+    }
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/AnomalyDetectionTechnique.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/AnomalyDetectionTechnique.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/AnomalyDetectionTechnique.java
new file mode 100644
index 0000000..0b10b4b
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/AnomalyDetectionTechnique.java
@@ -0,0 +1,32 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.methods;
+
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
+
+import java.sql.Time;
+import java.util.List;
+import java.util.Map;
+
+public abstract class AnomalyDetectionTechnique {
+
+  protected String methodType;
+
+  public abstract List<MetricAnomaly> test(TimelineMetric metric);
+
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/MetricAnomaly.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/MetricAnomaly.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/MetricAnomaly.java
new file mode 100644
index 0000000..da4f030
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/MetricAnomaly.java
@@ -0,0 +1,86 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.methods;
+
+import java.io.Serializable;
+import java.util.HashMap;
+import java.util.Map;
+
+public class MetricAnomaly implements Serializable{
+
+  private String methodType;
+  private double anomalyScore;
+  private String metricKey;
+  private long timestamp;
+  private double metricValue;
+
+
+  public MetricAnomaly(String metricKey, long timestamp, double metricValue, String methodType, double anomalyScore) {
+    this.metricKey = metricKey;
+    this.timestamp = timestamp;
+    this.metricValue = metricValue;
+    this.methodType = methodType;
+    this.anomalyScore = anomalyScore;
+
+  }
+
+  public String getMethodType() {
+    return methodType;
+  }
+
+  public void setMethodType(String methodType) {
+    this.methodType = methodType;
+  }
+
+  public double getAnomalyScore() {
+    return anomalyScore;
+  }
+
+  public void setAnomalyScore(double anomalyScore) {
+    this.anomalyScore = anomalyScore;
+  }
+
+  public void setMetricKey(String metricKey) {
+    this.metricKey = metricKey;
+  }
+
+  public String getMetricKey() {
+    return metricKey;
+  }
+
+  public void setMetricName(String metricName) {
+    this.metricKey = metricName;
+  }
+
+  public long getTimestamp() {
+    return timestamp;
+  }
+
+  public void setTimestamp(long timestamp) {
+    this.timestamp = timestamp;
+  }
+
+  public double getMetricValue() {
+    return metricValue;
+  }
+
+  public void setMetricValue(double metricValue) {
+    this.metricValue = metricValue;
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModel.java
----------------------------------------------------------------------
diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModel.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModel.java
new file mode 100644
index 0000000..5e1f76b
--- /dev/null
+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModel.java
@@ -0,0 +1,124 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.methods.ema;
+
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+
+import javax.xml.bind.annotation.XmlRootElement;
+import java.io.Serializable;
+
+@XmlRootElement
+public class EmaModel implements Serializable {
+
+  private String metricName;
+  private String hostname;
+  private String appId;
+  private double ema;
+  private double ems;
+  private double weight;
+  private double timessdev;
+
+  private int ctr = 0;
+  private static final int suppressAnomaliesTheshold = 30;
+
+  private static final Log LOG = LogFactory.getLog(EmaModel.class);
+
+  public EmaModel(String name, String hostname, String appId, double weight, double timessdev) {
+    this.metricName = name;
+    this.hostname = hostname;
+    this.appId = appId;
+    this.weight = weight;
+    this.timessdev = timessdev;
+    this.ema = 0.0;
+    this.ems = 0.0;
+  }
+
+  public String getMetricName() {
+    return metricName;
+  }
+
+  public String getHostname() {
+    return hostname;
+  }
+
+  public String getAppId() {
+    return appId;
+  }
+
+  public double testAndUpdate(double metricValue) {
+
+    double anomalyScore = 0.0;
+    if (ctr > suppressAnomaliesTheshold) {
+      anomalyScore = test(metricValue);
+    }
+    if (Math.abs(anomalyScore) < 2 * timessdev) {
+      update(metricValue);
+    } else {
+      LOG.info("Not updating model for this value");
+    }
+    ctr++;
+    LOG.info("Counter : " + ctr);
+    LOG.info("Anomaly Score for " + metricValue + " : " + anomalyScore);
+    return anomalyScore;
+  }
+
+  public void update(double metricValue) {
+    ema = weight * ema + (1 - weight) * metricValue;
+    ems = Math.sqrt(weight * Math.pow(ems, 2.0) + (1 - weight) * Math.pow(metricValue - ema, 2.0));
+    LOG.info("In update : ema = " + ema + ", ems = " + ems);
+  }
+
+  public double test(double metricValue) {
+    LOG.info("In test : ema = " + ema + ", ems = " + ems);
+    double diff = Math.abs(ema - metricValue) - (timessdev * ems);
+    LOG.info("diff = " + diff);
+    if (diff > 0) {
+      return Math.abs((metricValue - ema) / ems); //Z score
+    } else {
+      return 0.0;
+    }
+  }
+
+  public void updateModel(boolean increaseSensitivity, double percent) {
+    LOG.info("Updating model for " + metricName + " with increaseSensitivity = " + increaseSensitivity + ", percent = " + percent);
+    double delta = percent / 100;
+    if (increaseSensitivity) {
+      delta = delta * -1;
+    }
+    this.timessdev = timessdev + delta * timessdev;
+    this.weight = Math.min(1.0, weight + delta * weight);
+    LOG.info("New model parameters " + metricName + " : timessdev = " + timessdev + ", weight = " + weight);
+  }
+
+  public double getWeight() {
+    return weight;
+  }
+
+  public void setWeight(double weight) {
+    this.weight = weight;
+  }
+
+  public double getTimessdev() {
+    return timessdev;
+  }
+
+  public void setTimessdev(double timessdev) {
+    this.timessdev = timessdev;
+  }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModelLoader.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModelLoader.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModelLoader.java
new file mode 100644
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+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaModelLoader.java
@@ -0,0 +1,46 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.methods.ema;
+
+import com.google.gson.Gson;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.spark.SparkContext;
+import org.apache.spark.mllib.util.Loader;
+
+import java.io.IOException;
+import java.nio.charset.StandardCharsets;
+import java.nio.file.Files;
+import java.nio.file.Paths;
+
+public class EmaModelLoader implements Loader<EmaTechnique> {
+    private static final Log LOG = LogFactory.getLog(EmaModelLoader.class);
+
+    @Override
+    public EmaTechnique load(SparkContext sc, String path) {
+        return new EmaTechnique(0.5,3);
+//        Gson gson = new Gson();
+//        try {
+//            String fileString = new String(Files.readAllBytes(Paths.get(path)), StandardCharsets.UTF_8);
+//            return gson.fromJson(fileString, EmaTechnique.class);
+//        } catch (IOException e) {
+//            LOG.error(e);
+//        }
+//        return null;
+    }
+}

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaTechnique.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaTechnique.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaTechnique.java
new file mode 100644
index 0000000..c005e6f
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+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/ema/EmaTechnique.java
@@ -0,0 +1,142 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * <p>
+ * http://www.apache.org/licenses/LICENSE-2.0
+ * <p>
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.methods.ema;
+
+import com.google.gson.Gson;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.ambari.metrics.alertservice.prototype.methods.MetricAnomaly;
+import org.apache.ambari.metrics.alertservice.prototype.methods.AnomalyDetectionTechnique;
+import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
+import org.apache.spark.SparkContext;
+import org.apache.spark.mllib.util.Saveable;
+
+import javax.xml.bind.annotation.XmlElement;
+import javax.xml.bind.annotation.XmlRootElement;
+import java.io.BufferedWriter;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.io.OutputStreamWriter;
+import java.io.Serializable;
+import java.io.Writer;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+@XmlRootElement
+public class EmaTechnique extends AnomalyDetectionTechnique implements Serializable, Saveable {
+
+  @XmlElement(name = "trackedEmas")
+  private Map<String, EmaModel> trackedEmas;
+  private static final Log LOG = LogFactory.getLog(EmaTechnique.class);
+
+  private double startingWeight = 0.5;
+  private double startTimesSdev = 3.0;
+  private String methodType = "ema";
+
+  public EmaTechnique(double startingWeight, double startTimesSdev) {
+    trackedEmas = new HashMap<>();
+    this.startingWeight = startingWeight;
+    this.startTimesSdev = startTimesSdev;
+    LOG.info("New EmaTechnique......");
+  }
+
+  public List<MetricAnomaly> test(TimelineMetric metric) {
+    String metricName = metric.getMetricName();
+    String appId = metric.getAppId();
+    String hostname = metric.getHostName();
+    String key = metricName + "_" + appId + "_" + hostname;
+
+    EmaModel emaModel = trackedEmas.get(key);
+    if (emaModel == null) {
+      LOG.info("EmaModel not present for " + key);
+      LOG.info("Number of tracked Emas : " + trackedEmas.size());
+      emaModel  = new EmaModel(metricName, hostname, appId, startingWeight, startTimesSdev);
+      trackedEmas.put(key, emaModel);
+    } else {
+      LOG.info("EmaModel already present for " + key);
+    }
+
+    List<MetricAnomaly> anomalies = new ArrayList<>();
+
+    for (Long timestamp : metric.getMetricValues().keySet()) {
+      double metricValue = metric.getMetricValues().get(timestamp);
+      double anomalyScore = emaModel.testAndUpdate(metricValue);
+      if (anomalyScore > 0.0) {
+        LOG.info("Found anomaly for : " + key);
+        MetricAnomaly metricAnomaly = new MetricAnomaly(key, timestamp, metricValue, methodType, anomalyScore);
+        anomalies.add(metricAnomaly);
+      } else {
+        LOG.info("Discarding non-anomaly for : " + key);
+      }
+    }
+    return anomalies;
+  }
+
+  public boolean updateModel(TimelineMetric timelineMetric, boolean increaseSensitivity, double percent) {
+    String metricName = timelineMetric.getMetricName();
+    String appId = timelineMetric.getAppId();
+    String hostname = timelineMetric.getHostName();
+    String key = metricName + "_" + appId + "_" + hostname;
+
+
+    EmaModel emaModel = trackedEmas.get(key);
+
+    if (emaModel == null) {
+      LOG.warn("EMA Model for " + key + " not found");
+      return false;
+    }
+    emaModel.updateModel(increaseSensitivity, percent);
+
+    return true;
+  }
+
+  @Override
+  public void save(SparkContext sc, String path) {
+    Gson gson = new Gson();
+    try {
+      String json = gson.toJson(this);
+      try (Writer writer = new BufferedWriter(new OutputStreamWriter(
+        new FileOutputStream(path), "utf-8"))) {
+        writer.write(json);
+      }
+    } catch (IOException e) {
+      LOG.error(e);
+    }
+  }
+
+  @Override
+  public String formatVersion() {
+    return "1.0";
+  }
+
+  public Map<String, EmaModel> getTrackedEmas() {
+    return trackedEmas;
+  }
+
+  public double getStartingWeight() {
+    return startingWeight;
+  }
+
+  public double getStartTimesSdev() {
+    return startTimesSdev;
+  }
+
+}
+

http://git-wip-us.apache.org/repos/asf/ambari/blob/63e74355/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/hsdev/HsdevTechnique.java
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diff --git a/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/hsdev/HsdevTechnique.java b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/hsdev/HsdevTechnique.java
new file mode 100644
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+++ b/ambari-metrics/ambari-metrics-alertservice/src/main/java/org/apache/ambari/metrics/alertservice/prototype/methods/hsdev/HsdevTechnique.java
@@ -0,0 +1,77 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.ambari.metrics.alertservice.prototype.methods.hsdev;
+
+import org.apache.ambari.metrics.alertservice.prototype.common.DataSeries;
+import org.apache.ambari.metrics.alertservice.prototype.methods.MetricAnomaly;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import static org.apache.ambari.metrics.alertservice.prototype.common.StatisticUtils.median;
+import static org.apache.ambari.metrics.alertservice.prototype.common.StatisticUtils.sdev;
+
+import java.io.Serializable;
+import java.util.Date;
+import java.util.HashMap;
+import java.util.Map;
+
+public class HsdevTechnique implements Serializable {
+
+  private Map<String, Double> hsdevMap;
+  private String methodType = "hsdev";
+  private static final Log LOG = LogFactory.getLog(HsdevTechnique.class);
+
+  public HsdevTechnique() {
+    hsdevMap = new HashMap<>();
+  }
+
+  public MetricAnomaly runHsdevTest(String key, DataSeries trainData, DataSeries testData) {
+    int testLength = testData.values.length;
+    int trainLength = trainData.values.length;
+
+    if (trainLength < testLength) {
+      LOG.info("Not enough train data.");
+      return null;
+    }
+
+    if (!hsdevMap.containsKey(key)) {
+      hsdevMap.put(key, 3.0);
+    }
+
+    double n = hsdevMap.get(key);
+
+    double historicSd = sdev(trainData.values, false);
+    double historicMedian = median(trainData.values);
+    double currentMedian = median(testData.values);
+
+    double diff = Math.abs(currentMedian - historicMedian);
+    LOG.info("Found anomaly for metric : " + key + " in the period ending " + new Date((long)testData.ts[testLength - 1]));
+    LOG.info("Current median = " + currentMedian + ", Historic Median = " + historicMedian + ", HistoricSd = " + historicSd);
+
+    if (diff > n * historicSd) {
+      double zScore = diff / historicSd;
+      LOG.info("Z Score of current series : " + zScore);
+      return new MetricAnomaly(key,
+        (long) testData.ts[testLength - 1],
+        testData.values[testLength - 1],
+        methodType,
+        zScore);
+    }
+    return null;
+  }
+
+}