YARN-6363. Extending SLS: Synthetic Load Generator. (Carlo Curino via wangda)

hadoop-tools/hadoop-rumen/src/main/java/org/apache/hadoop/tools/rumen/TaskInfo.java

@@ -23,21 +23,37 @@ public class TaskInfo {
   private final long bytesOut;
   private final int recsOut;
   private final long maxMemory;
+  private final long maxVcores;
   private final ResourceUsageMetrics metrics;
 
+
+  public TaskInfo(long bytesIn, int recsIn, long bytesOut, int recsOut,
+                  long maxMemory) {
+    this(bytesIn, recsIn, bytesOut, recsOut, maxMemory, 1,
+        new ResourceUsageMetrics());
+  }
+
   public TaskInfo(long bytesIn, int recsIn, long bytesOut, int recsOut,
-      long maxMemory) {
-    this(bytesIn, recsIn, bytesOut, recsOut, maxMemory, 
+                  long maxMemory, ResourceUsageMetrics
+                      metrics) {
+    this(bytesIn, recsIn, bytesOut, recsOut, maxMemory, 1, metrics);
+  }
+
+  public TaskInfo(long bytesIn, int recsIn, long bytesOut, int recsOut,
+      long maxMemory, long maxVcores) {
+    this(bytesIn, recsIn, bytesOut, recsOut, maxMemory, maxVcores,
          new ResourceUsageMetrics());
   }
   
   public TaskInfo(long bytesIn, int recsIn, long bytesOut, int recsOut,
-                  long maxMemory, ResourceUsageMetrics metrics) {
+                  long maxMemory, long maxVcores, ResourceUsageMetrics
+                      metrics) {
     this.bytesIn = bytesIn;
     this.recsIn = recsIn;
     this.bytesOut = bytesOut;
     this.recsOut = recsOut;
     this.maxMemory = maxMemory;
+    this.maxVcores = maxVcores;
     this.metrics = metrics;
   }
 
@@ -78,6 +94,13 @@ public class TaskInfo {
     return maxMemory;
   }
 
+  /**
+   * @return Vcores used by the task.
+   */
+  public long getTaskVCores() {
+    return maxVcores;
+  }
+
   /**
    * @return Resource usage metrics
    */

hadoop-tools/hadoop-rumen/src/main/java/org/apache/hadoop/tools/rumen/ZombieJob.java

@@ -426,7 +426,7 @@ public class ZombieJob implements JobStory {
     LoggedTask loggedTask = getLoggedTask(taskType, taskNumber);
     if (loggedTask == null) {
       // TODO insert parameters
-      TaskInfo taskInfo = new TaskInfo(0, 0, 0, 0, 0);
+      TaskInfo taskInfo = new TaskInfo(0, 0, 0, 0, 0, 0);
       return makeUpTaskAttemptInfo(taskType, taskInfo, taskAttemptNumber,
           taskNumber, locality);
     }
@@ -473,7 +473,7 @@ public class ZombieJob implements JobStory {
     LoggedTask loggedTask = getLoggedTask(taskType, taskNumber);
     if (loggedTask == null) {
       // TODO insert parameters
-      TaskInfo taskInfo = new TaskInfo(0, 0, 0, 0, 0);
+      TaskInfo taskInfo = new TaskInfo(0, 0, 0, 0, 0, 0);
       return makeUpTaskAttemptInfo(taskType, taskInfo, taskAttemptNumber,
           taskNumber, locality);
     }
@@ -639,7 +639,7 @@ public class ZombieJob implements JobStory {
 
   private TaskInfo getTaskInfo(LoggedTask loggedTask) {
     if (loggedTask == null) {
-      return new TaskInfo(0, 0, 0, 0, 0);
+      return new TaskInfo(0, 0, 0, 0, 0, 0);
     }
     List<LoggedTaskAttempt> attempts = loggedTask.getAttempts();
 
@@ -688,9 +688,10 @@ public class ZombieJob implements JobStory {
       break;
     }
 
+    //note: hardcoding vCores, as they are not collected
     TaskInfo taskInfo =
         new TaskInfo(inputBytes, (int) inputRecords, outputBytes,
-            (int) outputRecords, (int) heapMegabytes,
+            (int) outputRecords, (int) heapMegabytes, 1,
             metrics);
     return taskInfo;
   }

hadoop-tools/hadoop-sls/pom.xml

@@ -132,6 +132,9 @@
             <exclude>src/test/resources/simulate.html.template</exclude>
             <exclude>src/test/resources/simulate.info.html.template</exclude>
             <exclude>src/test/resources/track.html.template</exclude>
+            <exclude>src/test/resources/syn.json</exclude>
+            <exclude>src/test/resources/inputsls.json</exclude>
+            <exclude>src/test/resources/nodes.json</exclude>
           </excludes>
         </configuration>
       </plugin>

hadoop-tools/hadoop-sls/src/main/bin/slsrun.sh

@@ -16,7 +16,9 @@
 function hadoop_usage()
 {
   echo "Usage: slsrun.sh <OPTIONS> "
-  echo "                 --input-rumen=<FILE1,FILE2,...>  | --input-sls=<FILE1,FILE2,...>"
+  echo "                 --tracetype=<SYNTH | SLS | RUMEN>"
+  echo "                 --tracelocation=<FILE1,FILE2,...>"
+  echo "                 (deprecated --input-rumen=<FILE1,FILE2,...>  | --input-sls=<FILE1,FILE2,...>)"
   echo "                 --output-dir=<SLS_SIMULATION_OUTPUT_DIRECTORY>"
   echo "                 [--nodes=<SLS_NODES_FILE>]"
   echo "                 [--track-jobs=<JOBID1,JOBID2,...>]"
@@ -33,6 +35,12 @@ function parse_args()
       --input-sls=*)
         inputsls=${i#*=}
       ;;
+      --tracetype=*)
+        tracetype=${i#*=}
+      ;;
+      --tracelocation=*)
+        tracelocation=${i#*=}
+      ;;
       --output-dir=*)
         outputdir=${i#*=}
       ;;
@@ -52,14 +60,12 @@ function parse_args()
     esac
   done
 
-  if [[ -z "${inputrumen}" && -z "${inputsls}" ]] ; then
-    hadoop_error "ERROR: Either --input-rumen or --input-sls must be specified."
-    hadoop_exit_with_usage 1
+  if [[ -z "${inputrumen}" && -z "${inputsls}" && -z "${tracetype}" ]] ; then
+    hadoop_error "ERROR: Either --input-rumen, --input-sls, or --tracetype (with --tracelocation) must be specified."
   fi
 
-  if [[ -n "${inputrumen}" && -n "${inputsls}" ]] ; then
-    hadoop_error "ERROR: Only specify one of --input-rumen or --input-sls."
-    hadoop_exit_with_usage 1
+  if [[ -n "${inputrumen}" && -n "${inputsls}" && -n "${tracetype}" ]] ; then
+    hadoop_error "ERROR: Only specify one of --input-rumen, --input-sls, or --tracetype (with --tracelocation)"
   fi
 
   if [[ -z "${outputdir}" ]] ; then
@@ -74,11 +80,17 @@ function calculate_classpath
 }
 
 function run_simulation() {
-  if [[ "${inputsls}" == "" ]] ; then
-    hadoop_add_param args -inputrumen "-inputrumen ${inputrumen}"
-  else
-    hadoop_add_param args -inputsls "-inputsls ${inputsls}"
-  fi
+
+   if [[ "${inputsls}" != "" ]] ; then
+        hadoop_add_param args -inputsls "-inputsls ${inputsls}"
+   fi
+   if [[ "${inputrumen}" != "" ]] ; then
+        hadoop_add_param args -inputrumen "-inputrumen ${inputrumen}"
+   fi
+   if [[ "${tracetype}" != "" ]] ; then
+        hadoop_add_param args -tracetype "-tracetype ${tracetype}"
+        hadoop_add_param args -tracelocation "-tracelocation ${tracelocation}"
+   fi
 
   hadoop_add_param args -output "-output ${outputdir}"
 

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/ReservationClientUtil.java

@@ -0,0 +1,78 @@
+/**
+ * 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.hadoop.yarn.sls;
+
+import org.apache.hadoop.yarn.api.protocolrecords.ReservationSubmissionRequest;
+import org.apache.hadoop.yarn.api.records.*;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * Simple support class, used to create reservation requests.
+ */
+public final class ReservationClientUtil {
+
+  private ReservationClientUtil(){
+    //avoid instantiation
+  }
+
+  /**
+   * Creates a request that envelopes a MR jobs, picking max number of maps and
+   * reducers, max durations, and max resources per container.
+   *
+   * @param reservationId the id of the reservation
+   * @param name the name of a reservation
+   * @param maxMapRes maximum resources used by any mapper
+   * @param numberMaps number of mappers
+   * @param maxMapDur maximum duration of any mapper
+   * @param maxRedRes maximum resources used by any reducer
+   * @param numberReduces number of reducers
+   * @param maxRedDur maximum duration of any reducer
+   * @param arrival start time of valid range for reservation
+   * @param deadline deadline for this reservation
+   * @param queueName queue to submit to
+   * @return a submission request
+   */
+  @SuppressWarnings("checkstyle:parameternumber")
+  public static ReservationSubmissionRequest createMRReservation(
+      ReservationId reservationId, String name, Resource maxMapRes,
+      int numberMaps, long maxMapDur, Resource maxRedRes, int numberReduces,
+      long maxRedDur, long arrival, long deadline, String queueName) {
+
+    ReservationRequest mapRR = ReservationRequest.newInstance(maxMapRes,
+        numberMaps, numberMaps, maxMapDur);
+    ReservationRequest redRR = ReservationRequest.newInstance(maxRedRes,
+        numberReduces, numberReduces, maxRedDur);
+
+    List<ReservationRequest> listResReq = new ArrayList<ReservationRequest>();
+    listResReq.add(mapRR);
+    listResReq.add(redRR);
+
+    ReservationRequests reservationRequests = ReservationRequests
+        .newInstance(listResReq, ReservationRequestInterpreter.R_ORDER_NO_GAP);
+    ReservationDefinition resDef = ReservationDefinition.newInstance(arrival,
+        deadline, reservationRequests, name);
+
+    // outermost request
+    ReservationSubmissionRequest request = ReservationSubmissionRequest
+        .newInstance(resDef, queueName, reservationId);
+
+    return request;
+  }
+}

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/SLSRunner.java

@@ -41,17 +41,25 @@ import org.apache.commons.cli.CommandLine;
 import org.apache.commons.cli.CommandLineParser;
 import org.apache.commons.cli.GnuParser;
 import org.apache.commons.cli.Options;
+import org.apache.commons.cli.ParseException;
 import org.apache.hadoop.classification.InterfaceAudience.Private;
 import org.apache.hadoop.classification.InterfaceStability.Unstable;
 import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.conf.Configured;
 import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.mapreduce.TaskType;
 import org.apache.hadoop.tools.rumen.JobTraceReader;
 import org.apache.hadoop.tools.rumen.LoggedJob;
 import org.apache.hadoop.tools.rumen.LoggedTask;
 import org.apache.hadoop.tools.rumen.LoggedTaskAttempt;
+import org.apache.hadoop.tools.rumen.TaskAttemptInfo;
 import org.apache.hadoop.util.ReflectionUtils;
+import org.apache.hadoop.util.Tool;
+import org.apache.hadoop.util.ToolRunner;
+import org.apache.hadoop.yarn.api.protocolrecords.ReservationSubmissionRequest;
 import org.apache.hadoop.yarn.api.records.NodeId;
 import org.apache.hadoop.yarn.api.records.NodeState;
+import org.apache.hadoop.yarn.api.records.ReservationId;
 import org.apache.hadoop.yarn.api.records.Resource;
 import org.apache.hadoop.yarn.conf.YarnConfiguration;
 import org.apache.hadoop.yarn.exceptions.YarnException;
@@ -67,25 +75,27 @@ import org.apache.hadoop.yarn.sls.conf.SLSConfiguration;
 import org.apache.hadoop.yarn.sls.nodemanager.NMSimulator;
 import org.apache.hadoop.yarn.sls.resourcemanager.MockAMLauncher;
 import org.apache.hadoop.yarn.sls.scheduler.*;
+import org.apache.hadoop.yarn.sls.synthetic.SynthJob;
+import org.apache.hadoop.yarn.sls.synthetic.SynthTraceJobProducer;
 import org.apache.hadoop.yarn.sls.utils.SLSUtils;
+import org.apache.hadoop.yarn.util.UTCClock;
 import org.apache.hadoop.yarn.util.resource.Resources;
 import org.apache.log4j.Logger;
 
 @Private
 @Unstable
-public class SLSRunner {
+public class SLSRunner extends Configured implements Tool {
   // RM, Runner
   private ResourceManager rm;
   private static TaskRunner runner = new TaskRunner();
   private String[] inputTraces;
-  private Configuration conf;
   private Map<String, Integer> queueAppNumMap;
-  
+
   // NM simulator
   private HashMap<NodeId, NMSimulator> nmMap;
   private int nmMemoryMB, nmVCores;
   private String nodeFile;
-  
+
   // AM simulator
   private int AM_ID;
   private Map<String, AMSimulator> amMap;
@@ -106,43 +116,64 @@ public class SLSRunner {
   // logger
   public final static Logger LOG = Logger.getLogger(SLSRunner.class);
 
-  // input traces, input-rumen or input-sls
-  private boolean isSLS;
-  
-  public SLSRunner(boolean isSLS, String inputTraces[], String nodeFile,
-                   String outputDir, Set<String> trackedApps,
-                   boolean printsimulation)
-          throws IOException, ClassNotFoundException {
-    this.isSLS = isSLS;
-    this.inputTraces = inputTraces.clone();
-    this.nodeFile = nodeFile;
-    this.trackedApps = trackedApps;
-    this.printSimulation = printsimulation;
-    metricsOutputDir = outputDir;
-    
+  /**
+   * The type of trace in input.
+   */
+  public enum TraceType {
+    SLS, RUMEN, SYNTH
+  }
+
+  private TraceType inputType;
+  private SynthTraceJobProducer stjp;
+
+  public SLSRunner() throws ClassNotFoundException {
+    Configuration tempConf = new Configuration(false);
+    init(tempConf);
+  }
+
+  public SLSRunner(Configuration tempConf) throws ClassNotFoundException {
+    init(tempConf);
+  }
+
+  private void init(Configuration tempConf) throws ClassNotFoundException {
     nmMap = new HashMap<>();
     queueAppNumMap = new HashMap<>();
     amMap = new ConcurrentHashMap<>();
     amClassMap = new HashMap<>();
-    
+
     // runner configuration
-    conf = new Configuration(false);
-    conf.addResource("sls-runner.xml");
+    tempConf.addResource("sls-runner.xml");
+    super.setConf(tempConf);
+
     // runner
-    int poolSize = conf.getInt(SLSConfiguration.RUNNER_POOL_SIZE, 
-                                SLSConfiguration.RUNNER_POOL_SIZE_DEFAULT); 
+    int poolSize = tempConf.getInt(SLSConfiguration.RUNNER_POOL_SIZE,
+        SLSConfiguration.RUNNER_POOL_SIZE_DEFAULT);
     SLSRunner.runner.setQueueSize(poolSize);
     // <AMType, Class> map
-    for (Map.Entry e : conf) {
+    for (Map.Entry e : tempConf) {
       String key = e.getKey().toString();
       if (key.startsWith(SLSConfiguration.AM_TYPE)) {
         String amType = key.substring(SLSConfiguration.AM_TYPE.length());
-        amClassMap.put(amType, Class.forName(conf.get(key)));
+        amClassMap.put(amType, Class.forName(tempConf.get(key)));
       }
     }
   }
-  
-  public void start() throws Exception {
+
+  public void setSimulationParams(TraceType inType, String[] inTraces,
+      String nodes, String outDir, Set<String> trackApps,
+      boolean printsimulation) throws IOException, ClassNotFoundException {
+
+    this.inputType = inType;
+    this.inputTraces = inTraces.clone();
+    this.nodeFile = nodes;
+    this.trackedApps = trackApps;
+    this.printSimulation = printsimulation;
+    metricsOutputDir = outDir;
+
+  }
+
+  public void start() throws IOException, ClassNotFoundException, YarnException,
+      InterruptedException {
     // start resource manager
     startRM();
     // start node managers
@@ -151,9 +182,9 @@ public class SLSRunner {
     startAM();
     // set queue & tracked apps information
     ((SchedulerWrapper) rm.getResourceScheduler()).getTracker()
-                            .setQueueSet(this.queueAppNumMap.keySet());
+        .setQueueSet(this.queueAppNumMap.keySet());
     ((SchedulerWrapper) rm.getResourceScheduler()).getTracker()
-                            .setTrackedAppSet(this.trackedApps);
+        .setTrackedAppSet(this.trackedApps);
     // print out simulation info
     printSimulationInfo();
     // blocked until all nodes RUNNING
@@ -162,23 +193,23 @@ public class SLSRunner {
     runner.start();
   }
 
-  private void startRM() throws Exception {
-    Configuration rmConf = new YarnConfiguration();
+  private void startRM() throws ClassNotFoundException, YarnException {
+    Configuration rmConf = new YarnConfiguration(getConf());
     String schedulerClass = rmConf.get(YarnConfiguration.RM_SCHEDULER);
 
     // For CapacityScheduler we use a sub-classing instead of wrapping
     // to allow scheduler-specific invocations from monitors to work
     // this can be used for other schedulers as well if we care to
     // exercise/track behaviors that are not common to the scheduler api
-    if(Class.forName(schedulerClass) == CapacityScheduler.class) {
+    if (Class.forName(schedulerClass) == CapacityScheduler.class) {
       rmConf.set(YarnConfiguration.RM_SCHEDULER,
           SLSCapacityScheduler.class.getName());
     } else if (Class.forName(schedulerClass) == FairScheduler.class) {
       rmConf.set(YarnConfiguration.RM_SCHEDULER,
           SLSFairScheduler.class.getName());
-    } else if (Class.forName(schedulerClass) == FifoScheduler.class){
+    } else if (Class.forName(schedulerClass) == FifoScheduler.class) {
       // TODO add support for FifoScheduler
-      throw new Exception("Fifo Scheduler is not supported yet.");
+      throw new YarnException("Fifo Scheduler is not supported yet.");
     }
 
     rmConf.set(SLSConfiguration.METRICS_OUTPUT_DIR, metricsOutputDir);
@@ -196,37 +227,47 @@ public class SLSRunner {
 
   private void startNM() throws YarnException, IOException {
     // nm configuration
-    nmMemoryMB = conf.getInt(SLSConfiguration.NM_MEMORY_MB,
-            SLSConfiguration.NM_MEMORY_MB_DEFAULT);
-    nmVCores = conf.getInt(SLSConfiguration.NM_VCORES,
-            SLSConfiguration.NM_VCORES_DEFAULT);
-    int heartbeatInterval = conf.getInt(
-            SLSConfiguration.NM_HEARTBEAT_INTERVAL_MS,
+    nmMemoryMB = getConf().getInt(SLSConfiguration.NM_MEMORY_MB,
+        SLSConfiguration.NM_MEMORY_MB_DEFAULT);
+    nmVCores = getConf().getInt(SLSConfiguration.NM_VCORES,
+        SLSConfiguration.NM_VCORES_DEFAULT);
+    int heartbeatInterval =
+        getConf().getInt(SLSConfiguration.NM_HEARTBEAT_INTERVAL_MS,
             SLSConfiguration.NM_HEARTBEAT_INTERVAL_MS_DEFAULT);
     // nm information (fetch from topology file, or from sls/rumen json file)
     Set<String> nodeSet = new HashSet<String>();
     if (nodeFile.isEmpty()) {
-      if (isSLS) {
-        for (String inputTrace : inputTraces) {
+      for (String inputTrace : inputTraces) {
+
+        switch (inputType) {
+        case SLS:
           nodeSet.addAll(SLSUtils.parseNodesFromSLSTrace(inputTrace));
-        }
-      } else {
-        for (String inputTrace : inputTraces) {
+          break;
+        case RUMEN:
           nodeSet.addAll(SLSUtils.parseNodesFromRumenTrace(inputTrace));
+          break;
+        case SYNTH:
+          stjp = new SynthTraceJobProducer(getConf(), new Path(inputTraces[0]));
+          nodeSet.addAll(SLSUtils.generateNodesFromSynth(stjp.getNumNodes(),
+              stjp.getNodesPerRack()));
+          break;
+        default:
+          throw new YarnException("Input configuration not recognized, "
+              + "trace type should be SLS, RUMEN, or SYNTH");
         }
       }
-
     } else {
       nodeSet.addAll(SLSUtils.parseNodesFromNodeFile(nodeFile));
     }
+
     // create NM simulators
     Random random = new Random();
     Set<String> rackSet = new HashSet<String>();
     for (String hostName : nodeSet) {
       // we randomize the heartbeat start time from zero to 1 interval
       NMSimulator nm = new NMSimulator();
-      nm.init(hostName, nmMemoryMB, nmVCores, 
-          random.nextInt(heartbeatInterval), heartbeatInterval, rm);
+      nm.init(hostName, nmMemoryMB, nmVCores, random.nextInt(heartbeatInterval),
+          heartbeatInterval, rm);
       nmMap.put(nm.getNode().getNodeID(), nm);
       runner.schedule(nm);
       rackSet.add(nm.getNode().getRackName());
@@ -241,39 +282,50 @@ public class SLSRunner {
       int numRunningNodes = 0;
       for (RMNode node : rm.getRMContext().getRMNodes().values()) {
         if (node.getState() == NodeState.RUNNING) {
-          numRunningNodes ++;
+          numRunningNodes++;
         }
       }
       if (numRunningNodes == numNMs) {
         break;
       }
-      LOG.info(MessageFormat.format("SLSRunner is waiting for all " +
-              "nodes RUNNING. {0} of {1} NMs initialized.",
-              numRunningNodes, numNMs));
+      LOG.info(MessageFormat.format(
+          "SLSRunner is waiting for all "
+              + "nodes RUNNING. {0} of {1} NMs initialized.",
+          numRunningNodes, numNMs));
       Thread.sleep(1000);
     }
     LOG.info(MessageFormat.format("SLSRunner takes {0} ms to launch all nodes.",
-            (System.currentTimeMillis() - startTimeMS)));
+        (System.currentTimeMillis() - startTimeMS)));
   }
 
   @SuppressWarnings("unchecked")
   private void startAM() throws YarnException, IOException {
     // application/container configuration
-    int heartbeatInterval = conf.getInt(
-            SLSConfiguration.AM_HEARTBEAT_INTERVAL_MS,
+    int heartbeatInterval =
+        getConf().getInt(SLSConfiguration.AM_HEARTBEAT_INTERVAL_MS,
             SLSConfiguration.AM_HEARTBEAT_INTERVAL_MS_DEFAULT);
-    int containerMemoryMB = conf.getInt(SLSConfiguration.CONTAINER_MEMORY_MB,
+    int containerMemoryMB =
+        getConf().getInt(SLSConfiguration.CONTAINER_MEMORY_MB,
             SLSConfiguration.CONTAINER_MEMORY_MB_DEFAULT);
-    int containerVCores = conf.getInt(SLSConfiguration.CONTAINER_VCORES,
-            SLSConfiguration.CONTAINER_VCORES_DEFAULT);
+    int containerVCores = getConf().getInt(SLSConfiguration.CONTAINER_VCORES,
+        SLSConfiguration.CONTAINER_VCORES_DEFAULT);
     Resource containerResource =
-            BuilderUtils.newResource(containerMemoryMB, containerVCores);
+        BuilderUtils.newResource(containerMemoryMB, containerVCores);
 
     // application workload
-    if (isSLS) {
+    switch (inputType) {
+    case SLS:
       startAMFromSLSTraces(containerResource, heartbeatInterval);
-    } else {
+      break;
+    case RUMEN:
       startAMFromRumenTraces(containerResource, heartbeatInterval);
+      break;
+    case SYNTH:
+      startAMFromSynthGenerator(heartbeatInterval);
+      break;
+    default:
+      throw new YarnException("Input configuration not recognized, "
+          + "trace type should be SLS, RUMEN, or SYNTH");
     }
     numAMs = amMap.size();
     remainingApps = numAMs;
@@ -284,7 +336,7 @@ public class SLSRunner {
    */
   @SuppressWarnings("unchecked")
   private void startAMFromSLSTraces(Resource containerResource,
-                                    int heartbeatInterval) throws IOException {
+      int heartbeatInterval) throws IOException {
     // parse from sls traces
     JsonFactory jsonF = new JsonFactory();
     ObjectMapper mapper = new ObjectMapper();
@@ -292,26 +344,28 @@ public class SLSRunner {
       Reader input =
           new InputStreamReader(new FileInputStream(inputTrace), "UTF-8");
       try {
-        Iterator<Map> i = mapper.readValues(jsonF.createParser(input),
-                Map.class);
+        Iterator<Map> i =
+            mapper.readValues(jsonF.createParser(input), Map.class);
         while (i.hasNext()) {
           Map jsonJob = i.next();
 
           // load job information
-          long jobStartTime = Long.parseLong(
-                  jsonJob.get("job.start.ms").toString());
-          long jobFinishTime = Long.parseLong(
-                  jsonJob.get("job.end.ms").toString());
+          long jobStartTime =
+              Long.parseLong(jsonJob.get("job.start.ms").toString());
+          long jobFinishTime =
+              Long.parseLong(jsonJob.get("job.end.ms").toString());
 
           String user = (String) jsonJob.get("job.user");
-          if (user == null)  user = "default";
+          if (user == null) {
+            user = "default";
+          }
           String queue = jsonJob.get("job.queue.name").toString();
 
           String oldAppId = jsonJob.get("job.id").toString();
           boolean isTracked = trackedApps.contains(oldAppId);
-          int queueSize = queueAppNumMap.containsKey(queue) ?
-                  queueAppNumMap.get(queue) : 0;
-          queueSize ++;
+          int queueSize =
+              queueAppNumMap.containsKey(queue) ? queueAppNumMap.get(queue) : 0;
+          queueSize++;
           queueAppNumMap.put(queue, queueSize);
           // tasks
           List tasks = (List) jsonJob.get("job.tasks");
@@ -319,45 +373,45 @@ public class SLSRunner {
             continue;
           }
           List<ContainerSimulator> containerList =
-                  new ArrayList<ContainerSimulator>();
+              new ArrayList<ContainerSimulator>();
           for (Object o : tasks) {
             Map jsonTask = (Map) o;
             String hostname = jsonTask.get("container.host").toString();
-            long taskStart = Long.parseLong(
-                    jsonTask.get("container.start.ms").toString());
-            long taskFinish = Long.parseLong(
-                    jsonTask.get("container.end.ms").toString());
+            long taskStart =
+                Long.parseLong(jsonTask.get("container.start.ms").toString());
+            long taskFinish =
+                Long.parseLong(jsonTask.get("container.end.ms").toString());
             long lifeTime = taskFinish - taskStart;
 
             // Set memory and vcores from job trace file
             Resource res = Resources.clone(containerResource);
             if (jsonTask.containsKey("container.memory")) {
-              int containerMemory = Integer.parseInt(
-                  jsonTask.get("container.memory").toString());
+              int containerMemory =
+                  Integer.parseInt(jsonTask.get("container.memory").toString());
               res.setMemorySize(containerMemory);
             }
 
             if (jsonTask.containsKey("container.vcores")) {
-              int containerVCores = Integer.parseInt(
-                  jsonTask.get("container.vcores").toString());
+              int containerVCores =
+                  Integer.parseInt(jsonTask.get("container.vcores").toString());
               res.setVirtualCores(containerVCores);
             }
 
-            int priority = Integer.parseInt(
-                    jsonTask.get("container.priority").toString());
+            int priority =
+                Integer.parseInt(jsonTask.get("container.priority").toString());
             String type = jsonTask.get("container.type").toString();
-            containerList.add(new ContainerSimulator(res,
-                    lifeTime, hostname, priority, type));
+            containerList.add(new ContainerSimulator(res, lifeTime, hostname,
+                priority, type));
           }
 
           // create a new AM
           String amType = jsonJob.get("am.type").toString();
-          AMSimulator amSim = (AMSimulator) ReflectionUtils.newInstance(
-                  amClassMap.get(amType), new Configuration());
+          AMSimulator amSim = (AMSimulator) ReflectionUtils
+              .newInstance(amClassMap.get(amType), new Configuration());
           if (amSim != null) {
-            amSim.init(AM_ID++, heartbeatInterval, containerList, rm,
-                    this, jobStartTime, jobFinishTime, user, queue,
-                    isTracked, oldAppId);
+            amSim.init(AM_ID++, heartbeatInterval, containerList, rm, this,
+                jobStartTime, jobFinishTime, user, queue, isTracked, oldAppId,
+                null, runner.getStartTimeMS());
             runner.schedule(amSim);
             maxRuntime = Math.max(maxRuntime, jobFinishTime);
             numTasks += containerList.size();
@@ -375,22 +429,21 @@ public class SLSRunner {
    */
   @SuppressWarnings("unchecked")
   private void startAMFromRumenTraces(Resource containerResource,
-                                      int heartbeatInterval)
-          throws IOException {
+      int heartbeatInterval) throws IOException {
     Configuration conf = new Configuration();
     conf.set("fs.defaultFS", "file:///");
     long baselineTimeMS = 0;
     for (String inputTrace : inputTraces) {
       File fin = new File(inputTrace);
-      JobTraceReader reader = new JobTraceReader(
-              new Path(fin.getAbsolutePath()), conf);
+      JobTraceReader reader =
+          new JobTraceReader(new Path(fin.getAbsolutePath()), conf);
       try {
         LoggedJob job = null;
         while ((job = reader.getNext()) != null) {
           // only support MapReduce currently
           String jobType = "mapreduce";
-          String user = job.getUser() == null ?
-                  "default" : job.getUser().getValue();
+          String user =
+              job.getUser() == null ? "default" : job.getUser().getValue();
           String jobQueue = job.getQueue().getValue();
           String oldJobId = job.getJobID().toString();
           long jobStartTimeMS = job.getSubmitTime();
@@ -407,48 +460,48 @@ public class SLSRunner {
           }
 
           boolean isTracked = trackedApps.contains(oldJobId);
-          int queueSize = queueAppNumMap.containsKey(jobQueue) ?
-                  queueAppNumMap.get(jobQueue) : 0;
-          queueSize ++;
+          int queueSize = queueAppNumMap.containsKey(jobQueue)
+              ? queueAppNumMap.get(jobQueue) : 0;
+          queueSize++;
           queueAppNumMap.put(jobQueue, queueSize);
 
           List<ContainerSimulator> containerList =
-                  new ArrayList<ContainerSimulator>();
+              new ArrayList<ContainerSimulator>();
           // map tasks
-          for(LoggedTask mapTask : job.getMapTasks()) {
+          for (LoggedTask mapTask : job.getMapTasks()) {
             if (mapTask.getAttempts().size() == 0) {
               continue;
             }
-            LoggedTaskAttempt taskAttempt = mapTask.getAttempts()
-                    .get(mapTask.getAttempts().size() - 1);
+            LoggedTaskAttempt taskAttempt =
+                mapTask.getAttempts().get(mapTask.getAttempts().size() - 1);
             String hostname = taskAttempt.getHostName().getValue();
-            long containerLifeTime = taskAttempt.getFinishTime()
-                    - taskAttempt.getStartTime();
+            long containerLifeTime =
+                taskAttempt.getFinishTime() - taskAttempt.getStartTime();
             containerList.add(new ContainerSimulator(containerResource,
-                    containerLifeTime, hostname, 10, "map"));
+                containerLifeTime, hostname, 10, "map"));
           }
 
           // reduce tasks
-          for(LoggedTask reduceTask : job.getReduceTasks()) {
+          for (LoggedTask reduceTask : job.getReduceTasks()) {
             if (reduceTask.getAttempts().size() == 0) {
               continue;
             }
             LoggedTaskAttempt taskAttempt = reduceTask.getAttempts()
-                    .get(reduceTask.getAttempts().size() - 1);
+                .get(reduceTask.getAttempts().size() - 1);
             String hostname = taskAttempt.getHostName().getValue();
-            long containerLifeTime = taskAttempt.getFinishTime()
-                    - taskAttempt.getStartTime();
+            long containerLifeTime =
+                taskAttempt.getFinishTime() - taskAttempt.getStartTime();
             containerList.add(new ContainerSimulator(containerResource,
-                    containerLifeTime, hostname, 20, "reduce"));
+                containerLifeTime, hostname, 20, "reduce"));
           }
 
           // create a new AM
-          AMSimulator amSim = (AMSimulator) ReflectionUtils.newInstance(
-                  amClassMap.get(jobType), conf);
+          AMSimulator amSim = (AMSimulator) ReflectionUtils
+              .newInstance(amClassMap.get(jobType), conf);
           if (amSim != null) {
-            amSim.init(AM_ID ++, heartbeatInterval, containerList,
-                    rm, this, jobStartTimeMS, jobFinishTimeMS, user, jobQueue,
-                    isTracked, oldJobId);
+            amSim.init(AM_ID++, heartbeatInterval, containerList, rm, this,
+                jobStartTimeMS, jobFinishTimeMS, user, jobQueue, isTracked,
+                oldJobId, null, runner.getStartTimeMS());
             runner.schedule(amSim);
             maxRuntime = Math.max(maxRuntime, jobFinishTimeMS);
             numTasks += containerList.size();
@@ -460,34 +513,168 @@ public class SLSRunner {
       }
     }
   }
-  
+
+  /**
+   * parse workload information from synth-generator trace files.
+   */
+  @SuppressWarnings("unchecked")
+  private void startAMFromSynthGenerator(int heartbeatInterval)
+      throws IOException {
+    Configuration localConf = new Configuration();
+    localConf.set("fs.defaultFS", "file:///");
+    long baselineTimeMS = 0;
+
+    // reservations use wall clock time, so need to have a reference for that
+    UTCClock clock = new UTCClock();
+    long now = clock.getTime();
+
+    try {
+
+      // if we use the nodeFile this could have been not initialized yet.
+      if (stjp == null) {
+        stjp = new SynthTraceJobProducer(getConf(), new Path(inputTraces[0]));
+      }
+
+      SynthJob job = null;
+      // we use stjp, a reference to the job producer instantiated during node
+      // creation
+      while ((job = (SynthJob) stjp.getNextJob()) != null) {
+        // only support MapReduce currently
+        String jobType = "mapreduce";
+        String user = job.getUser();
+        String jobQueue = job.getQueueName();
+        String oldJobId = job.getJobID().toString();
+        long jobStartTimeMS = job.getSubmissionTime();
+
+        // CARLO: Finish time is only used for logging, omit for now
+        long jobFinishTimeMS = -1L;
+
+        if (baselineTimeMS == 0) {
+          baselineTimeMS = jobStartTimeMS;
+        }
+        jobStartTimeMS -= baselineTimeMS;
+        jobFinishTimeMS -= baselineTimeMS;
+        if (jobStartTimeMS < 0) {
+          LOG.warn("Warning: reset job " + oldJobId + " start time to 0.");
+          jobFinishTimeMS = jobFinishTimeMS - jobStartTimeMS;
+          jobStartTimeMS = 0;
+        }
+
+        boolean isTracked = trackedApps.contains(oldJobId);
+        int queueSize = queueAppNumMap.containsKey(jobQueue)
+            ? queueAppNumMap.get(jobQueue) : 0;
+        queueSize++;
+        queueAppNumMap.put(jobQueue, queueSize);
+
+        List<ContainerSimulator> containerList =
+            new ArrayList<ContainerSimulator>();
+        ArrayList<NodeId> keyAsArray = new ArrayList<NodeId>(nmMap.keySet());
+        Random rand = new Random(stjp.getSeed());
+
+        Resource maxMapRes = Resource.newInstance(0, 0);
+        long maxMapDur = 0;
+        // map tasks
+        for (int i = 0; i < job.getNumberMaps(); i++) {
+          TaskAttemptInfo tai = job.getTaskAttemptInfo(TaskType.MAP, i, 0);
+          RMNode node = nmMap
+              .get(keyAsArray.get(rand.nextInt(keyAsArray.size()))).getNode();
+          String hostname = "/" + node.getRackName() + "/" + node.getHostName();
+          long containerLifeTime = tai.getRuntime();
+          Resource containerResource =
+              Resource.newInstance((int) tai.getTaskInfo().getTaskMemory(),
+                  (int) tai.getTaskInfo().getTaskVCores());
+          containerList.add(new ContainerSimulator(containerResource,
+              containerLifeTime, hostname, 10, "map"));
+          maxMapRes = Resources.componentwiseMax(maxMapRes, containerResource);
+          maxMapDur =
+              containerLifeTime > maxMapDur ? containerLifeTime : maxMapDur;
+
+        }
+
+        Resource maxRedRes = Resource.newInstance(0, 0);
+        long maxRedDur = 0;
+        // reduce tasks
+        for (int i = 0; i < job.getNumberReduces(); i++) {
+          TaskAttemptInfo tai = job.getTaskAttemptInfo(TaskType.REDUCE, i, 0);
+          RMNode node = nmMap
+              .get(keyAsArray.get(rand.nextInt(keyAsArray.size()))).getNode();
+          String hostname = "/" + node.getRackName() + "/" + node.getHostName();
+          long containerLifeTime = tai.getRuntime();
+          Resource containerResource =
+              Resource.newInstance((int) tai.getTaskInfo().getTaskMemory(),
+                  (int) tai.getTaskInfo().getTaskVCores());
+          containerList.add(new ContainerSimulator(containerResource,
+              containerLifeTime, hostname, 20, "reduce"));
+          maxRedRes = Resources.componentwiseMax(maxRedRes, containerResource);
+          maxRedDur =
+              containerLifeTime > maxRedDur ? containerLifeTime : maxRedDur;
+
+        }
+
+        // generating reservations for the jobs that require them
+
+        ReservationSubmissionRequest rr = null;
+        if (job.hasDeadline()) {
+          ReservationId reservationId =
+              ReservationId.newInstance(this.rm.getStartTime(), AM_ID);
+
+          rr = ReservationClientUtil.createMRReservation(reservationId,
+              "reservation_" + AM_ID, maxMapRes, job.getNumberMaps(), maxMapDur,
+              maxRedRes, job.getNumberReduces(), maxRedDur,
+              now + jobStartTimeMS, now + job.getDeadline(),
+              job.getQueueName());
+
+        }
+        // create a new AM
+        AMSimulator amSim = (AMSimulator) ReflectionUtils
+            .newInstance(amClassMap.get(jobType), localConf);
+        if (amSim != null) {
+          amSim.init(AM_ID++, heartbeatInterval, containerList, rm, this,
+              jobStartTimeMS, jobFinishTimeMS, user, jobQueue, isTracked,
+              oldJobId, rr, runner.getStartTimeMS());
+          runner.schedule(amSim);
+          maxRuntime = Math.max(maxRuntime, jobFinishTimeMS);
+          numTasks += containerList.size();
+          amMap.put(oldJobId, amSim);
+        }
+      }
+    } finally {
+      stjp.close();
+    }
+
+  }
+
   private void printSimulationInfo() {
     if (printSimulation) {
       // node
       LOG.info("------------------------------------");
-      LOG.info(MessageFormat.format("# nodes = {0}, # racks = {1}, capacity " +
-              "of each node {2} MB memory and {3} vcores.",
-              numNMs, numRacks, nmMemoryMB, nmVCores));
+      LOG.info(MessageFormat.format(
+          "# nodes = {0}, # racks = {1}, capacity "
+              + "of each node {2} MB memory and {3} vcores.",
+          numNMs, numRacks, nmMemoryMB, nmVCores));
       LOG.info("------------------------------------");
       // job
-      LOG.info(MessageFormat.format("# applications = {0}, # total " +
-              "tasks = {1}, average # tasks per application = {2}",
-              numAMs, numTasks, (int)(Math.ceil((numTasks + 0.0) / numAMs))));
+      LOG.info(MessageFormat.format(
+          "# applications = {0}, # total "
+              + "tasks = {1}, average # tasks per application = {2}",
+          numAMs, numTasks, (int) (Math.ceil((numTasks + 0.0) / numAMs))));
       LOG.info("JobId\tQueue\tAMType\tDuration\t#Tasks");
       for (Map.Entry<String, AMSimulator> entry : amMap.entrySet()) {
         AMSimulator am = entry.getValue();
-        LOG.info(entry.getKey() + "\t" + am.getQueue() + "\t" + am.getAMType() 
+        LOG.info(entry.getKey() + "\t" + am.getQueue() + "\t" + am.getAMType()
             + "\t" + am.getDuration() + "\t" + am.getNumTasks());
       }
       LOG.info("------------------------------------");
       // queue
-      LOG.info(MessageFormat.format("number of queues = {0}  average " +
-              "number of apps = {1}", queueAppNumMap.size(),
-              (int)(Math.ceil((numAMs + 0.0) / queueAppNumMap.size()))));
+      LOG.info(MessageFormat.format(
+          "number of queues = {0}  average " + "number of apps = {1}",
+          queueAppNumMap.size(),
+          (int) (Math.ceil((numAMs + 0.0) / queueAppNumMap.size()))));
       LOG.info("------------------------------------");
       // runtime
-      LOG.info(MessageFormat.format("estimated simulation time is {0}" +
-              " seconds", (long)(Math.ceil(maxRuntime / 1000.0))));
+      LOG.info(
+          MessageFormat.format("estimated simulation time is {0}" + " seconds",
+              (long) (Math.ceil(maxRuntime / 1000.0))));
       LOG.info("------------------------------------");
     }
     // package these information in the simulateInfoMap used by other places
@@ -510,69 +697,121 @@ public class SLSRunner {
     return nmMap;
   }
 
-  public static TaskRunner getRunner() {
-    return runner;
-  }
-
   public static void decreaseRemainingApps() {
-    remainingApps --;
+    remainingApps--;
 
     if (remainingApps == 0) {
       LOG.info("SLSRunner tears down.");
-      System.exit(0);
     }
   }
 
-  public static void main(String args[]) throws Exception {
+  public void stop() throws InterruptedException {
+    rm.stop();
+    runner.stop();
+  }
+
+  public int run(final String[] argv) throws IOException, InterruptedException,
+      ParseException, ClassNotFoundException, YarnException {
+
     Options options = new Options();
+
+    // Left for compatibility
     options.addOption("inputrumen", true, "input rumen files");
     options.addOption("inputsls", true, "input sls files");
+
+    // New more general format
+    options.addOption("tracetype", true, "the type of trace");
+    options.addOption("tracelocation", true, "input trace files");
+
     options.addOption("nodes", true, "input topology");
     options.addOption("output", true, "output directory");
     options.addOption("trackjobs", true,
-            "jobs to be tracked during simulating");
+        "jobs to be tracked during simulating");
     options.addOption("printsimulation", false,
-            "print out simulation information");
-    
+        "print out simulation information");
+
     CommandLineParser parser = new GnuParser();
-    CommandLine cmd = parser.parse(options, args);
+    CommandLine cmd = parser.parse(options, argv);
 
-    String inputRumen = cmd.getOptionValue("inputrumen");
-    String inputSLS = cmd.getOptionValue("inputsls");
-    String output = cmd.getOptionValue("output");
-    
-    if ((inputRumen == null && inputSLS == null) || output == null) {
-      System.err.println();
-      System.err.println("ERROR: Missing input or output file");
-      System.err.println();
-      System.err.println("Options: -inputrumen|-inputsls FILE,FILE... " +
-              "-output FILE [-nodes FILE] [-trackjobs JobId,JobId...] " +
-              "[-printsimulation]");
-      System.err.println();
-      System.exit(1);
+    String traceType = null;
+    String traceLocation = null;
+
+    // compatibility with old commandline
+    if (cmd.hasOption("inputrumen")) {
+      traceType = "RUMEN";
+      traceLocation = cmd.getOptionValue("inputrumen");
+    }
+    if (cmd.hasOption("inputsls")) {
+      traceType = "SLS";
+      traceLocation = cmd.getOptionValue("inputsls");
+    }
+
+    if (cmd.hasOption("tracetype")) {
+      traceType = cmd.getOptionValue("tracetype");
+      traceLocation = cmd.getOptionValue("tracelocation");
     }
-    
+
+    String output = cmd.getOptionValue("output");
+
     File outputFile = new File(output);
-    if (! outputFile.exists()
-            && ! outputFile.mkdirs()) {
+    if (!outputFile.exists() && !outputFile.mkdirs()) {
       System.err.println("ERROR: Cannot create output directory "
-              + outputFile.getAbsolutePath());
-      System.exit(1);
+          + outputFile.getAbsolutePath());
+      throw new YarnException("Cannot create output directory");
     }
-    
+
     Set<String> trackedJobSet = new HashSet<String>();
     if (cmd.hasOption("trackjobs")) {
       String trackjobs = cmd.getOptionValue("trackjobs");
       String jobIds[] = trackjobs.split(",");
       trackedJobSet.addAll(Arrays.asList(jobIds));
     }
-    
-    String nodeFile = cmd.hasOption("nodes") ? cmd.getOptionValue("nodes") : "";
 
-    boolean isSLS = inputSLS != null;
-    String inputFiles[] = isSLS ? inputSLS.split(",") : inputRumen.split(",");
-    SLSRunner sls = new SLSRunner(isSLS, inputFiles, nodeFile, output,
+    String tempNodeFile =
+        cmd.hasOption("nodes") ? cmd.getOptionValue("nodes") : "";
+
+    TraceType tempTraceType = TraceType.SLS;
+    switch (traceType) {
+    case "SLS":
+      tempTraceType = TraceType.SLS;
+      break;
+    case "RUMEN":
+      tempTraceType = TraceType.RUMEN;
+      break;
+
+    case "SYNTH":
+      tempTraceType = TraceType.SYNTH;
+      break;
+    default:
+      printUsage();
+      throw new YarnException("Misconfigured input");
+    }
+
+    String[] inputFiles = traceLocation.split(",");
+
+    setSimulationParams(tempTraceType, inputFiles, tempNodeFile, output,
         trackedJobSet, cmd.hasOption("printsimulation"));
-    sls.start();
+
+    start();
+
+    return 0;
   }
+
+  public static void main(String[] argv) throws Exception {
+    ToolRunner.run(new Configuration(), new SLSRunner(), argv);
+  }
+
+  static void printUsage() {
+    System.err.println();
+    System.err.println("ERROR: Wrong tracetype");
+    System.err.println();
+    System.err.println(
+        "Options: -tracetype " + "SLS|RUMEN|SYNTH -tracelocation FILE,FILE... "
+            + "(deprecated alternative options --inputsls FILE, FILE,... "
+            + " | --inputrumen FILE,FILE,...)"
+            + "-output FILE [-nodes FILE] [-trackjobs JobId,JobId...] "
+            + "[-printsimulation]");
+    System.err.println();
+  }
+
 }

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/appmaster/AMSimulator.java

@@ -19,6 +19,7 @@
 package org.apache.hadoop.yarn.sls.appmaster;
 
 import java.io.IOException;
+import java.lang.reflect.UndeclaredThrowableException;
 import java.nio.ByteBuffer;
 import java.security.PrivilegedExceptionAction;
 import java.text.MessageFormat;
@@ -37,6 +38,7 @@ import org.apache.hadoop.yarn.api.protocolrecords.AllocateRequest;
 import org.apache.hadoop.yarn.api.protocolrecords.AllocateResponse;
 import org.apache.hadoop.yarn.api.protocolrecords
         .FinishApplicationMasterRequest;
+import org.apache.hadoop.yarn.api.protocolrecords.ReservationSubmissionRequest;
 import org.apache.hadoop.yarn.api.protocolrecords.SubmitApplicationRequest;
 import org.apache.hadoop.yarn.api.protocolrecords.GetNewApplicationRequest;
 import org.apache.hadoop.yarn.api.protocolrecords.GetNewApplicationResponse;
@@ -55,6 +57,7 @@ import org.apache.hadoop.yarn.api.records.ContainerLaunchContext;
 import org.apache.hadoop.yarn.api.records.FinalApplicationStatus;
 import org.apache.hadoop.yarn.api.records.LocalResource;
 import org.apache.hadoop.yarn.api.records.Priority;
+import org.apache.hadoop.yarn.api.records.ReservationId;
 import org.apache.hadoop.yarn.api.records.Resource;
 import org.apache.hadoop.yarn.api.records.ResourceRequest;
 import org.apache.hadoop.yarn.exceptions.YarnException;
@@ -97,6 +100,7 @@ public abstract class AMSimulator extends TaskRunner.Task {
   // am type
   protected String amtype;
   // job start/end time
+  private long baselineTimeMS;
   protected long traceStartTimeMS;
   protected long traceFinishTimeMS;
   protected long simulateStartTimeMS;
@@ -117,25 +121,30 @@ public abstract class AMSimulator extends TaskRunner.Task {
   private final static int MR_AM_CONTAINER_RESOURCE_MEMORY_MB = 1024;
   private final static int MR_AM_CONTAINER_RESOURCE_VCORES = 1;
 
+  private ReservationSubmissionRequest reservationRequest;
+
   public AMSimulator() {
     this.responseQueue = new LinkedBlockingQueue<>();
   }
 
-  public void init(int id, int heartbeatInterval, 
-      List<ContainerSimulator> containerList, ResourceManager rm, SLSRunner se,
-      long traceStartTime, long traceFinishTime, String user, String queue, 
-      boolean isTracked, String oldAppId) {
-    super.init(traceStartTime, traceStartTime + 1000000L * heartbeatInterval,
-            heartbeatInterval);
-    this.user = user;
-    this.rm = rm;
-    this.se = se;
-    this.user = user;
-    this.queue = queue;
-    this.oldAppId = oldAppId;
-    this.isTracked = isTracked;
-    this.traceStartTimeMS = traceStartTime;
-    this.traceFinishTimeMS = traceFinishTime;
+  @SuppressWarnings("checkstyle:parameternumber")
+  public void init(int id, int heartbeatInterval,
+      List<ContainerSimulator> containerList, ResourceManager resourceManager,
+      SLSRunner slsRunnner, long startTime, long finishTime, String simUser,
+      String simQueue, boolean tracked, String oldApp,
+      ReservationSubmissionRequest rr, long baseTimeMS) {
+    super.init(startTime, startTime + 1000000L * heartbeatInterval,
+        heartbeatInterval);
+    this.user = simUser;
+    this.rm = resourceManager;
+    this.se = slsRunnner;
+    this.queue = simQueue;
+    this.oldAppId = oldApp;
+    this.isTracked = tracked;
+    this.baselineTimeMS = baseTimeMS;
+    this.traceStartTimeMS = startTime;
+    this.traceFinishTimeMS = finishTime;
+    this.reservationRequest = rr;
   }
 
   /**
@@ -143,11 +152,21 @@ public abstract class AMSimulator extends TaskRunner.Task {
    */
   @Override
   public void firstStep() throws Exception {
-    simulateStartTimeMS = System.currentTimeMillis() - 
-                          SLSRunner.getRunner().getStartTimeMS();
+    simulateStartTimeMS = System.currentTimeMillis() - baselineTimeMS;
+
+    ReservationId reservationId = null;
+
+    // submit a reservation if one is required, exceptions naturally happen
+    // when the reservation does not fit, catch, log, and move on running job
+    // without reservation.
+    try {
+      reservationId = submitReservationWhenSpecified();
+    } catch (UndeclaredThrowableException y) {
+      LOG.warn("Unable to place reservation: " + y.getMessage());
+    }
 
     // submit application, waiting until ACCEPTED
-    submitApp();
+    submitApp(reservationId);
 
     // track app metrics
     trackApp();
@@ -161,6 +180,26 @@ public abstract class AMSimulator extends TaskRunner.Task {
     isAMContainerRunning = true;
   }
 
+  private ReservationId submitReservationWhenSpecified()
+      throws IOException, InterruptedException {
+    if (reservationRequest != null) {
+      UserGroupInformation ugi = UserGroupInformation.createRemoteUser(user);
+      ugi.doAs(new PrivilegedExceptionAction<Object>() {
+        @Override
+        public Object run() throws YarnException, IOException {
+          rm.getClientRMService().submitReservation(reservationRequest);
+          LOG.info("RESERVATION SUCCESSFULLY SUBMITTED "
+              + reservationRequest.getReservationId());
+          return null;
+
+        }
+      });
+      return reservationRequest.getReservationId();
+    } else {
+      return null;
+    }
+  }
+
   @Override
   public void middleStep() throws Exception {
     if (isAMContainerRunning) {
@@ -217,14 +256,13 @@ public abstract class AMSimulator extends TaskRunner.Task {
       }
     });
 
-    simulateFinishTimeMS = System.currentTimeMillis() -
-        SLSRunner.getRunner().getStartTimeMS();
+    simulateFinishTimeMS = System.currentTimeMillis() - baselineTimeMS;
     // record job running information
     SchedulerMetrics schedulerMetrics =
-        ((SchedulerWrapper)rm.getResourceScheduler()).getSchedulerMetrics();
+            ((SchedulerWrapper)rm.getResourceScheduler()).getSchedulerMetrics();
     if (schedulerMetrics != null) {
       schedulerMetrics.addAMRuntime(appId, traceStartTimeMS, traceFinishTimeMS,
-          simulateStartTimeMS, simulateFinishTimeMS);
+              simulateStartTimeMS, simulateFinishTimeMS);
     }
   }
   
@@ -261,7 +299,7 @@ public abstract class AMSimulator extends TaskRunner.Task {
   
   protected abstract void checkStop();
   
-  private void submitApp()
+  private void submitApp(ReservationId reservationId)
           throws YarnException, InterruptedException, IOException {
     // ask for new application
     GetNewApplicationRequest newAppRequest =
@@ -291,6 +329,11 @@ public abstract class AMSimulator extends TaskRunner.Task {
     appSubContext.setResource(Resources
         .createResource(MR_AM_CONTAINER_RESOURCE_MEMORY_MB,
             MR_AM_CONTAINER_RESOURCE_VCORES));
+
+    if(reservationId != null) {
+      appSubContext.setReservationID(reservationId);
+    }
+
     subAppRequest.setApplicationSubmissionContext(appSubContext);
     UserGroupInformation ugi = UserGroupInformation.createRemoteUser(user);
     ugi.doAs(new PrivilegedExceptionAction<Object>() {

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/appmaster/MRAMSimulator.java

@@ -27,13 +27,13 @@ import java.util.LinkedList;
 import java.util.List;
 import java.util.Map;
 
-import org.apache.avro.Protocol;
 import org.apache.hadoop.classification.InterfaceAudience.Private;
 import org.apache.hadoop.classification.InterfaceStability.Unstable;
 import org.apache.hadoop.security.UserGroupInformation;
 import org.apache.hadoop.security.token.Token;
 import org.apache.hadoop.yarn.api.protocolrecords.AllocateRequest;
 import org.apache.hadoop.yarn.api.protocolrecords.AllocateResponse;
+import org.apache.hadoop.yarn.api.protocolrecords.ReservationSubmissionRequest;
 import org.apache.hadoop.yarn.api.records.Container;
 import org.apache.hadoop.yarn.api.records.ContainerExitStatus;
 import org.apache.hadoop.yarn.api.records.ContainerId;
@@ -42,7 +42,6 @@ import org.apache.hadoop.yarn.api.records.ResourceRequest;
 import org.apache.hadoop.yarn.exceptions.YarnException;
 import org.apache.hadoop.yarn.security.AMRMTokenIdentifier;
 import org.apache.hadoop.yarn.server.resourcemanager.ResourceManager;
-import org.apache.hadoop.yarn.server.utils.BuilderUtils;
 
 import org.apache.hadoop.yarn.sls.scheduler.ContainerSimulator;
 import org.apache.hadoop.yarn.sls.SLSRunner;
@@ -114,13 +113,15 @@ public class MRAMSimulator extends AMSimulator {
 
   public final Logger LOG = Logger.getLogger(MRAMSimulator.class);
 
+  @SuppressWarnings("checkstyle:parameternumber")
   public void init(int id, int heartbeatInterval,
       List<ContainerSimulator> containerList, ResourceManager rm, SLSRunner se,
       long traceStartTime, long traceFinishTime, String user, String queue, 
-      boolean isTracked, String oldAppId) {
+      boolean isTracked, String oldAppId, ReservationSubmissionRequest rr,
+      long baselineStartTimeMS) {
     super.init(id, heartbeatInterval, containerList, rm, se, 
               traceStartTime, traceFinishTime, user, queue,
-              isTracked, oldAppId);
+              isTracked, oldAppId, rr, baselineStartTimeMS);
     amtype = "mapreduce";
     
     // get map/reduce tasks

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/resourcemanager/MockAMLauncher.java

@@ -65,6 +65,11 @@ public class MockAMLauncher extends ApplicationMasterLauncher
     // Do nothing
   }
 
+  @Override
+  protected void serviceStop() throws Exception {
+    // Do nothing
+  }
+
   private void setupAMRMToken(RMAppAttempt appAttempt) {
     // Setup AMRMToken
     Token<AMRMTokenIdentifier> amrmToken =

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/scheduler/SLSCapacityScheduler.java

@@ -28,7 +28,6 @@ import org.apache.hadoop.classification.InterfaceAudience.Private;
 import org.apache.hadoop.classification.InterfaceStability.Unstable;
 import org.apache.hadoop.conf.Configurable;
 import org.apache.hadoop.conf.Configuration;
-import org.apache.hadoop.util.ShutdownHookManager;
 import org.apache.hadoop.yarn.api.records.ApplicationAttemptId;
 import org.apache.hadoop.yarn.api.records.Container;
 import org.apache.hadoop.yarn.api.records.ContainerExitStatus;
@@ -52,7 +51,6 @@ import org.apache.hadoop.yarn.server.resourcemanager.scheduler.event.SchedulerEv
 import org.apache.hadoop.yarn.server.resourcemanager.scheduler.event.SchedulerEventType;
 import org.apache.hadoop.yarn.sls.SLSRunner;
 import org.apache.hadoop.yarn.sls.conf.SLSConfiguration;
-import org.apache.hadoop.yarn.sls.utils.SLSUtils;
 import org.apache.hadoop.yarn.util.resource.Resources;
 
 import com.codahale.metrics.Timer;
@@ -96,16 +94,6 @@ public class SLSCapacityScheduler extends CapacityScheduler implements
       } catch (Exception e) {
         e.printStackTrace();
       }
-
-      ShutdownHookManager.get().addShutdownHook(new Runnable() {
-        @Override public void run() {
-          try {
-            schedulerMetrics.tearDown();
-          } catch (Exception e) {
-            e.printStackTrace();
-          }
-        }
-      }, SLSUtils.SHUTDOWN_HOOK_PRIORITY);
     }
   }
 
@@ -344,7 +332,6 @@ public class SLSCapacityScheduler extends CapacityScheduler implements
       initQueueMetrics(child);
     }
   }
-
   @Override
   public void serviceInit(Configuration configuration) throws Exception {
     super.serviceInit(configuration);
@@ -354,6 +341,17 @@ public class SLSCapacityScheduler extends CapacityScheduler implements
     }
   }
 
+  @Override
+  public void serviceStop() throws Exception {
+    try {
+      schedulerMetrics.tearDown();
+    } catch (Exception e) {
+      e.printStackTrace();
+    }
+    super.serviceStop();
+  }
+
+
   public SchedulerMetrics getSchedulerMetrics() {
     return schedulerMetrics;
   }

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/scheduler/SLSFairScheduler.java

@@ -22,7 +22,6 @@ import org.apache.hadoop.classification.InterfaceAudience.Private;
 import org.apache.hadoop.classification.InterfaceStability.Unstable;
 import org.apache.hadoop.conf.Configurable;
 import org.apache.hadoop.conf.Configuration;
-import org.apache.hadoop.util.ShutdownHookManager;
 import org.apache.hadoop.yarn.api.records.ApplicationAttemptId;
 import org.apache.hadoop.yarn.api.records.Container;
 import org.apache.hadoop.yarn.api.records.ContainerExitStatus;
@@ -44,7 +43,6 @@ import org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FSQueue;
 import org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler;
 import org.apache.hadoop.yarn.sls.SLSRunner;
 import org.apache.hadoop.yarn.sls.conf.SLSConfiguration;
-import org.apache.hadoop.yarn.sls.utils.SLSUtils;
 import org.apache.hadoop.yarn.util.resource.Resources;
 
 import java.io.IOException;
@@ -90,16 +88,6 @@ public class SLSFairScheduler extends FairScheduler
       } catch (Exception e) {
         e.printStackTrace();
       }
-
-      ShutdownHookManager.get().addShutdownHook(new Runnable() {
-        @Override public void run() {
-          try {
-            schedulerMetrics.tearDown();
-          } catch (Exception e) {
-            e.printStackTrace();
-          }
-        }
-      }, SLSUtils.SHUTDOWN_HOOK_PRIORITY);
     }
   }
 
@@ -335,5 +323,15 @@ public class SLSFairScheduler extends FairScheduler
       initQueueMetrics(getQueueManager().getRootQueue());
     }
   }
+
+  @Override
+  public void serviceStop() throws Exception {
+    try {
+      schedulerMetrics.tearDown();
+    } catch (Exception e) {
+      e.printStackTrace();
+    }
+    super.serviceStop();
+  }
 }
 

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/scheduler/TaskRunner.java

@@ -17,7 +17,6 @@
  */
 package org.apache.hadoop.yarn.sls.scheduler;
 
-import java.io.IOException;
 import java.text.MessageFormat;
 import java.util.Queue;
 import java.util.concurrent.DelayQueue;
@@ -27,7 +26,6 @@ import java.util.concurrent.TimeUnit;
 
 import org.apache.hadoop.classification.InterfaceAudience.Private;
 import org.apache.hadoop.classification.InterfaceStability.Unstable;
-import org.apache.hadoop.yarn.exceptions.YarnException;
 
 @Private
 @Unstable
@@ -148,8 +146,8 @@ public class TaskRunner {
 
   @SuppressWarnings("unchecked")
   public void start() {
-    if (executor != null) {
-      throw new IllegalStateException("Already started");
+    if (executor != null && !executor.isTerminated()) {
+      throw new IllegalStateException("Executor already running");
     }
     DelayQueue preStartQueue = queue;
 
@@ -164,8 +162,9 @@ public class TaskRunner {
     }
   }
   
-  public void stop() {
+  public void stop() throws InterruptedException {
     executor.shutdownNow();
+    executor.awaitTermination(20, TimeUnit.SECONDS);
   }
 
   @SuppressWarnings("unchecked")

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/synthetic/SynthJob.java

@@ -0,0 +1,306 @@
+/**
+ * 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.hadoop.yarn.sls.synthetic;
+
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.commons.math3.distribution.LogNormalDistribution;
+import org.apache.commons.math3.random.JDKRandomGenerator;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.mapred.JobConf;
+import org.apache.hadoop.mapred.TaskStatus.State;
+import org.apache.hadoop.mapreduce.InputSplit;
+import org.apache.hadoop.mapreduce.JobID;
+import org.apache.hadoop.mapreduce.MRJobConfig;
+import org.apache.hadoop.mapreduce.TaskType;
+import org.apache.hadoop.tools.rumen.*;
+import org.apache.hadoop.tools.rumen.Pre21JobHistoryConstants.Values;
+
+import java.util.Arrays;
+import java.util.concurrent.atomic.AtomicInteger;
+
+import static java.util.concurrent.TimeUnit.MILLISECONDS;
+import static java.util.concurrent.TimeUnit.SECONDS;
+import static org.apache.hadoop.mapreduce.MRJobConfig.QUEUE_NAME;
+
+/**
+ * Generates random task data for a synthetic job.
+ */
+public class SynthJob implements JobStory {
+
+  @SuppressWarnings("StaticVariableName")
+  private static Log LOG = LogFactory.getLog(SynthJob.class);
+
+  private final Configuration conf;
+  private final int id;
+
+  @SuppressWarnings("ConstantName")
+  private static final AtomicInteger sequence = new AtomicInteger(0);
+  private final String name;
+  private final String queueName;
+  private final SynthJobClass jobClass;
+
+  // job timing
+  private final long submitTime;
+  private final long duration;
+  private final long deadline;
+
+  private final int numMapTasks;
+  private final int numRedTasks;
+  private final long mapMaxMemory;
+  private final long reduceMaxMemory;
+  private final long mapMaxVcores;
+  private final long reduceMaxVcores;
+  private final long[] mapRuntime;
+  private final float[] reduceRuntime;
+  private long totMapRuntime;
+  private long totRedRuntime;
+
+  public SynthJob(JDKRandomGenerator rand, Configuration conf,
+      SynthJobClass jobClass, long actualSubmissionTime) {
+
+    this.conf = conf;
+    this.jobClass = jobClass;
+
+    this.duration = MILLISECONDS.convert(jobClass.getDur(), SECONDS);
+    this.numMapTasks = jobClass.getMtasks();
+    this.numRedTasks = jobClass.getRtasks();
+
+    // sample memory distributions, correct for sub-minAlloc sizes
+    long tempMapMaxMemory = jobClass.getMapMaxMemory();
+    this.mapMaxMemory = tempMapMaxMemory < MRJobConfig.DEFAULT_MAP_MEMORY_MB
+        ? MRJobConfig.DEFAULT_MAP_MEMORY_MB : tempMapMaxMemory;
+    long tempReduceMaxMemory = jobClass.getReduceMaxMemory();
+    this.reduceMaxMemory =
+            tempReduceMaxMemory < MRJobConfig.DEFAULT_REDUCE_MEMORY_MB
+            ? MRJobConfig.DEFAULT_REDUCE_MEMORY_MB : tempReduceMaxMemory;
+
+    // sample vcores distributions, correct for sub-minAlloc sizes
+    long tempMapMaxVCores = jobClass.getMapMaxVcores();
+    this.mapMaxVcores = tempMapMaxVCores < MRJobConfig.DEFAULT_MAP_CPU_VCORES
+        ? MRJobConfig.DEFAULT_MAP_CPU_VCORES : tempMapMaxVCores;
+    long tempReduceMaxVcores = jobClass.getReduceMaxVcores();
+    this.reduceMaxVcores =
+        tempReduceMaxVcores < MRJobConfig.DEFAULT_REDUCE_CPU_VCORES
+            ? MRJobConfig.DEFAULT_REDUCE_CPU_VCORES : tempReduceMaxVcores;
+
+    if (numMapTasks > 0) {
+      conf.setLong(MRJobConfig.MAP_MEMORY_MB, this.mapMaxMemory);
+      conf.set(MRJobConfig.MAP_JAVA_OPTS,
+          "-Xmx" + (this.mapMaxMemory - 100) + "m");
+    }
+
+    if (numRedTasks > 0) {
+      conf.setLong(MRJobConfig.REDUCE_MEMORY_MB, this.reduceMaxMemory);
+      conf.set(MRJobConfig.REDUCE_JAVA_OPTS,
+          "-Xmx" + (this.reduceMaxMemory - 100) + "m");
+    }
+
+    boolean hasDeadline =
+        (rand.nextDouble() <= jobClass.jobClass.chance_of_reservation);
+
+    LogNormalDistribution deadlineFactor =
+        SynthUtils.getLogNormalDist(rand, jobClass.jobClass.deadline_factor_avg,
+            jobClass.jobClass.deadline_factor_stddev);
+
+    double deadlineFactorSample =
+        (deadlineFactor != null) ? deadlineFactor.sample() : -1;
+
+    this.queueName = jobClass.workload.getQueueName();
+
+    this.submitTime = MILLISECONDS.convert(actualSubmissionTime, SECONDS);
+
+    this.deadline =
+        hasDeadline ? MILLISECONDS.convert(actualSubmissionTime, SECONDS)
+            + (long) Math.ceil(deadlineFactorSample * duration) : -1;
+
+    conf.set(QUEUE_NAME, queueName);
+
+    // name and initialize job randomness
+    final long seed = rand.nextLong();
+    rand.setSeed(seed);
+    id = sequence.getAndIncrement();
+
+    name = String.format(jobClass.getClassName() + "_%06d", id);
+    LOG.debug(name + " (" + seed + ")");
+
+    LOG.info("JOB TIMING`: job: " + name + " submission:" + submitTime
+        + " deadline:" + deadline + " duration:" + duration
+        + " deadline-submission: " + (deadline - submitTime));
+
+    // generate map and reduce runtimes
+    mapRuntime = new long[numMapTasks];
+    for (int i = 0; i < numMapTasks; i++) {
+      mapRuntime[i] = jobClass.getMapTimeSample();
+      totMapRuntime += mapRuntime[i];
+    }
+    reduceRuntime = new float[numRedTasks];
+    for (int i = 0; i < numRedTasks; i++) {
+      reduceRuntime[i] = jobClass.getReduceTimeSample();
+      totRedRuntime += (long) Math.ceil(reduceRuntime[i]);
+    }
+  }
+
+  public boolean hasDeadline() {
+    return deadline > 0;
+  }
+
+  @Override
+  public String getName() {
+    return name;
+  }
+
+  @Override
+  public String getUser() {
+    return jobClass.getUserName();
+  }
+
+  @Override
+  public JobID getJobID() {
+    return new JobID("job_mock_" + name, id);
+  }
+
+  @Override
+  public Values getOutcome() {
+    return Values.SUCCESS;
+  }
+
+  @Override
+  public long getSubmissionTime() {
+    return submitTime;
+  }
+
+  @Override
+  public int getNumberMaps() {
+    return numMapTasks;
+  }
+
+  @Override
+  public int getNumberReduces() {
+    return numRedTasks;
+  }
+
+  @Override
+  public TaskInfo getTaskInfo(TaskType taskType, int taskNumber) {
+    switch (taskType) {
+    case MAP:
+      return new TaskInfo(-1, -1, -1, -1, mapMaxMemory, mapMaxVcores);
+    case REDUCE:
+      return new TaskInfo(-1, -1, -1, -1, reduceMaxMemory, reduceMaxVcores);
+    default:
+      throw new IllegalArgumentException("Not interested");
+    }
+  }
+
+  @Override
+  public InputSplit[] getInputSplits() {
+    throw new UnsupportedOperationException();
+  }
+
+  @Override
+  public TaskAttemptInfo getTaskAttemptInfo(TaskType taskType, int taskNumber,
+      int taskAttemptNumber) {
+    switch (taskType) {
+    case MAP:
+      return new MapTaskAttemptInfo(State.SUCCEEDED,
+          getTaskInfo(taskType, taskNumber), mapRuntime[taskNumber], null);
+
+    case REDUCE:
+      // We assume uniform split between pull/sort/reduce
+      // aligned with naive progress reporting assumptions
+      return new ReduceTaskAttemptInfo(State.SUCCEEDED,
+          getTaskInfo(taskType, taskNumber),
+          (long) Math.round((reduceRuntime[taskNumber] / 3)),
+          (long) Math.round((reduceRuntime[taskNumber] / 3)),
+          (long) Math.round((reduceRuntime[taskNumber] / 3)), null);
+
+    default:
+      break;
+    }
+    throw new UnsupportedOperationException();
+  }
+
+  @Override
+  public TaskAttemptInfo getMapTaskAttemptInfoAdjusted(int taskNumber,
+      int taskAttemptNumber, int locality) {
+    throw new UnsupportedOperationException();
+  }
+
+  @Override
+  public org.apache.hadoop.mapred.JobConf getJobConf() {
+    return new JobConf(conf);
+  }
+
+  @Override
+  public String getQueueName() {
+    return queueName;
+  }
+
+  @Override
+  public String toString() {
+    return "SynthJob [\n" + "  workload=" + jobClass.getWorkload().getId()
+        + "\n" + "  jobClass="
+        + jobClass.getWorkload().getClassList().indexOf(jobClass) + "\n"
+        + "  conf=" + conf + ",\n" + "  id=" + id + ",\n" + "  name=" + name
+        + ",\n" + "  mapRuntime=" + Arrays.toString(mapRuntime) + ",\n"
+        + "  reduceRuntime=" + Arrays.toString(reduceRuntime) + ",\n"
+        + "  submitTime=" + submitTime + ",\n" + "  numMapTasks=" + numMapTasks
+        + ",\n" + "  numRedTasks=" + numRedTasks + ",\n" + "  mapMaxMemory="
+        + mapMaxMemory + ",\n" + "  reduceMaxMemory=" + reduceMaxMemory + ",\n"
+        + "  queueName=" + queueName + "\n" + "]";
+  }
+
+  public SynthJobClass getJobClass() {
+    return jobClass;
+  }
+
+  public long getTotalSlotTime() {
+    return totMapRuntime + totRedRuntime;
+  }
+
+  public long getDuration() {
+    return duration;
+  }
+
+  public long getDeadline() {
+    return deadline;
+  }
+
+  @Override
+  public boolean equals(Object other) {
+    if (!(other instanceof SynthJob)) {
+      return false;
+    }
+    SynthJob o = (SynthJob) other;
+    return Arrays.equals(mapRuntime, o.mapRuntime)
+        && Arrays.equals(reduceRuntime, o.reduceRuntime)
+        && submitTime == o.submitTime && numMapTasks == o.numMapTasks
+        && numRedTasks == o.numRedTasks && mapMaxMemory == o.mapMaxMemory
+        && reduceMaxMemory == o.reduceMaxMemory
+        && mapMaxVcores == o.mapMaxVcores
+        && reduceMaxVcores == o.reduceMaxVcores && queueName.equals(o.queueName)
+        && jobClass.equals(o.jobClass) && totMapRuntime == o.totMapRuntime
+        && totRedRuntime == o.totRedRuntime;
+  }
+
+  @Override
+  public int hashCode() {
+    // could have a bad distr; investigate if a relevant use case exists
+    return jobClass.hashCode() * (int) submitTime;
+  }
+}

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/synthetic/SynthJobClass.java

@@ -0,0 +1,180 @@
+/**
+ * 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.hadoop.yarn.sls.synthetic;
+
+import org.apache.commons.math3.distribution.AbstractRealDistribution;
+import org.apache.commons.math3.distribution.LogNormalDistribution;
+import org.apache.commons.math3.random.JDKRandomGenerator;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.tools.rumen.JobStory;
+import org.apache.hadoop.yarn.sls.synthetic.SynthTraceJobProducer.JobClass;
+import org.apache.hadoop.yarn.sls.synthetic.SynthTraceJobProducer.Trace;
+
+/**
+ * This is a class that represent a class of Jobs. It is used to generate an
+ * individual job, by picking random durations, task counts, container size,
+ * etc.
+ */
+public class SynthJobClass {
+
+  private final JDKRandomGenerator rand;
+  private final LogNormalDistribution dur;
+  private final LogNormalDistribution mapRuntime;
+  private final LogNormalDistribution redRuntime;
+  private final LogNormalDistribution mtasks;
+  private final LogNormalDistribution rtasks;
+  private final LogNormalDistribution mapMem;
+  private final LogNormalDistribution redMem;
+  private final LogNormalDistribution mapVcores;
+  private final LogNormalDistribution redVcores;
+
+  private final Trace trace;
+  @SuppressWarnings("VisibilityModifier")
+  protected final SynthWorkload workload;
+  @SuppressWarnings("VisibilityModifier")
+  protected final JobClass jobClass;
+
+  public SynthJobClass(JDKRandomGenerator rand, Trace trace,
+      SynthWorkload workload, int classId) {
+
+    this.trace = trace;
+    this.workload = workload;
+    this.rand = new JDKRandomGenerator();
+    this.rand.setSeed(rand.nextLong());
+    jobClass = trace.workloads.get(workload.getId()).job_classes.get(classId);
+
+    this.dur = SynthUtils.getLogNormalDist(rand, jobClass.dur_avg,
+        jobClass.dur_stddev);
+    this.mapRuntime = SynthUtils.getLogNormalDist(rand, jobClass.mtime_avg,
+        jobClass.mtime_stddev);
+    this.redRuntime = SynthUtils.getLogNormalDist(rand, jobClass.rtime_avg,
+        jobClass.rtime_stddev);
+    this.mtasks = SynthUtils.getLogNormalDist(rand, jobClass.mtasks_avg,
+        jobClass.mtasks_stddev);
+    this.rtasks = SynthUtils.getLogNormalDist(rand, jobClass.rtasks_avg,
+        jobClass.rtasks_stddev);
+
+    this.mapMem = SynthUtils.getLogNormalDist(rand, jobClass.map_max_memory_avg,
+        jobClass.map_max_memory_stddev);
+    this.redMem = SynthUtils.getLogNormalDist(rand,
+        jobClass.reduce_max_memory_avg, jobClass.reduce_max_memory_stddev);
+    this.mapVcores = SynthUtils.getLogNormalDist(rand,
+        jobClass.map_max_vcores_avg, jobClass.map_max_vcores_stddev);
+    this.redVcores = SynthUtils.getLogNormalDist(rand,
+        jobClass.reduce_max_vcores_avg, jobClass.reduce_max_vcores_stddev);
+  }
+
+  public JobStory getJobStory(Configuration conf, long actualSubmissionTime) {
+    return new SynthJob(rand, conf, this, actualSubmissionTime);
+  }
+
+  @Override
+  public String toString() {
+    return "SynthJobClass [workload=" + workload.getName() + ", class="
+        + jobClass.class_name + " job_count=" + jobClass.class_weight + ", dur="
+        + ((dur != null) ? dur.getNumericalMean() : 0) + ", mapRuntime="
+        + ((mapRuntime != null) ? mapRuntime.getNumericalMean() : 0)
+        + ", redRuntime="
+        + ((redRuntime != null) ? redRuntime.getNumericalMean() : 0)
+        + ", mtasks=" + ((mtasks != null) ? mtasks.getNumericalMean() : 0)
+        + ", rtasks=" + ((rtasks != null) ? rtasks.getNumericalMean() : 0)
+        + ", chance_of_reservation=" + jobClass.chance_of_reservation + "]\n";
+
+  }
+
+  public double getClassWeight() {
+    return jobClass.class_weight;
+  }
+
+  public long getDur() {
+    return genLongSample(dur);
+  }
+
+  public int getMtasks() {
+    return genIntSample(mtasks);
+  }
+
+  public int getRtasks() {
+    return genIntSample(rtasks);
+  }
+
+  public long getMapMaxMemory() {
+    return genLongSample(mapMem);
+  }
+
+  public long getReduceMaxMemory() {
+    return genLongSample(redMem);
+  }
+
+  public long getMapMaxVcores() {
+    return genLongSample(mapVcores);
+  }
+
+  public long getReduceMaxVcores() {
+    return genLongSample(redVcores);
+  }
+
+  public SynthWorkload getWorkload() {
+    return workload;
+  }
+
+  public int genIntSample(AbstractRealDistribution dist) {
+    if (dist == null) {
+      return 0;
+    }
+    double baseSample = dist.sample();
+    if (baseSample < 0) {
+      baseSample = 0;
+    }
+    return (int) (Integer.MAX_VALUE & (long) Math.ceil(baseSample));
+  }
+
+  public long genLongSample(AbstractRealDistribution dist) {
+    return dist != null ? (long) Math.ceil(dist.sample()) : 0;
+  }
+
+  @Override
+  public boolean equals(Object other) {
+    if (!(other instanceof SynthJobClass)) {
+      return false;
+    }
+    SynthJobClass o = (SynthJobClass) other;
+    return workload.equals(o.workload);
+  }
+
+  @Override
+  public int hashCode() {
+    return workload.hashCode() * workload.getId();
+  }
+
+  public String getClassName() {
+    return jobClass.class_name;
+  }
+
+  public long getMapTimeSample() {
+    return genLongSample(mapRuntime);
+  }
+
+  public long getReduceTimeSample() {
+    return genLongSample(redRuntime);
+  }
+
+  public String getUserName() {
+    return jobClass.user_name;
+  }
+}

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/synthetic/SynthTraceJobProducer.java

@@ -0,0 +1,316 @@
+/**
+ * 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.hadoop.yarn.sls.synthetic;
+
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+import org.apache.commons.math3.random.JDKRandomGenerator;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FSDataInputStream;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.tools.rumen.JobStory;
+import org.apache.hadoop.tools.rumen.JobStoryProducer;
+import org.codehaus.jackson.annotate.JsonProperty;
+import org.codehaus.jackson.map.ObjectMapper;
+
+import javax.xml.bind.annotation.XmlRootElement;
+import java.io.IOException;
+import java.util.*;
+import java.util.concurrent.atomic.AtomicInteger;
+
+import static org.codehaus.jackson.JsonParser.Feature.INTERN_FIELD_NAMES;
+import static org.codehaus.jackson.map.DeserializationConfig.Feature.FAIL_ON_UNKNOWN_PROPERTIES;
+
+/**
+ * This is a JobStoryProducer that operates from distribution of different
+ * workloads. The .json input file is used to determine how many jobs, which
+ * size, number of maps/reducers and their duration, as well as the temporal
+ * distributed of submissions. For each parameter we control avg and stdev, and
+ * generate values via normal or log-normal distributions.
+ */
+public class SynthTraceJobProducer implements JobStoryProducer {
+
+  @SuppressWarnings("StaticVariableName")
+  private static final Log LOG = LogFactory.getLog(SynthTraceJobProducer.class);
+
+  private final Configuration conf;
+  private final AtomicInteger numJobs;
+  private final Trace trace;
+  private final long seed;
+
+  private int totalWeight;
+  private final List<Double> weightList;
+  private final Map<Integer, SynthWorkload> workloads;
+
+  private final Queue<StoryParams> listStoryParams;
+
+  private final JDKRandomGenerator rand;
+
+  public static final String SLS_SYNTHETIC_TRACE_FILE =
+      "sls.synthetic" + ".trace_file";
+
+  public SynthTraceJobProducer(Configuration conf) throws IOException {
+    this(conf, new Path(conf.get(SLS_SYNTHETIC_TRACE_FILE)));
+  }
+
+  public SynthTraceJobProducer(Configuration conf, Path path)
+      throws IOException {
+
+    LOG.info("SynthTraceJobProducer");
+
+    this.conf = conf;
+    this.rand = new JDKRandomGenerator();
+    workloads = new HashMap<Integer, SynthWorkload>();
+    weightList = new ArrayList<Double>();
+
+    ObjectMapper mapper = new ObjectMapper();
+    mapper.configure(INTERN_FIELD_NAMES, true);
+    mapper.configure(FAIL_ON_UNKNOWN_PROPERTIES, false);
+
+    FileSystem ifs = path.getFileSystem(conf);
+    FSDataInputStream fileIn = ifs.open(path);
+
+    this.trace = mapper.readValue(fileIn, Trace.class);
+    seed = trace.rand_seed;
+    rand.setSeed(seed);
+
+    this.numJobs = new AtomicInteger(trace.num_jobs);
+
+    for (int workloadId = 0; workloadId < trace.workloads
+        .size(); workloadId++) {
+      SynthWorkload workload = new SynthWorkload(workloadId, trace);
+      for (int classId =
+          0; classId < trace.workloads.get(workloadId).job_classes
+              .size(); classId++) {
+        SynthJobClass cls = new SynthJobClass(rand, trace, workload, classId);
+        workload.add(cls);
+      }
+      workloads.put(workloadId, workload);
+    }
+
+    for (int i = 0; i < workloads.size(); i++) {
+      double w = workloads.get(i).getWorkloadWeight();
+      totalWeight += w;
+      weightList.add(w);
+    }
+
+    // create priority queue to keep start-time sorted
+    listStoryParams =
+        new PriorityQueue<StoryParams>(10, new Comparator<StoryParams>() {
+          @Override
+          public int compare(StoryParams o1, StoryParams o2) {
+            return Math
+                .toIntExact(o2.actualSubmissionTime - o1.actualSubmissionTime);
+          }
+        });
+
+    // initialize it
+    createStoryParams();
+    LOG.info("Generated " + listStoryParams.size() + " deadlines for "
+        + this.numJobs.get() + " jobs ");
+  }
+
+  public long getSeed() {
+    return seed;
+  }
+
+  public int getNodesPerRack() {
+    return trace.nodes_per_rack;
+  }
+
+  public int getNumNodes() {
+    return trace.num_nodes;
+  }
+
+  /**
+   * Class used to parse a trace configuration file.
+   */
+  @SuppressWarnings({ "membername", "checkstyle:visibilitymodifier" })
+  @XmlRootElement
+  public static class Trace {
+    @JsonProperty("description")
+    String description;
+    @JsonProperty("num_nodes")
+    int num_nodes;
+    @JsonProperty("nodes_per_rack")
+    int nodes_per_rack;
+    @JsonProperty("num_jobs")
+    int num_jobs;
+
+    // in sec (selects a portion of time_distribution
+    @JsonProperty("rand_seed")
+    long rand_seed;
+    @JsonProperty("workloads")
+    List<Workload> workloads;
+
+  }
+
+  /**
+   * Class used to parse a workload from file.
+   */
+  @SuppressWarnings({ "membername", "checkstyle:visibilitymodifier" })
+  public static class Workload {
+    @JsonProperty("workload_name")
+    String workload_name;
+    // used to change probability this workload is picked for each job
+    @JsonProperty("workload_weight")
+    double workload_weight;
+    @JsonProperty("queue_name")
+    String queue_name;
+    @JsonProperty("job_classes")
+    List<JobClass> job_classes;
+    @JsonProperty("time_distribution")
+    List<TimeSample> time_distribution;
+  }
+
+  /**
+   * Class used to parse a job class from file.
+   */
+  @SuppressWarnings({ "membername", "checkstyle:visibilitymodifier" })
+  public static class JobClass {
+
+    @JsonProperty("class_name")
+    String class_name;
+    @JsonProperty("user_name")
+    String user_name;
+
+    // used to change probability this class is chosen
+    @JsonProperty("class_weight")
+    double class_weight;
+
+    // reservation related params
+    @JsonProperty("chance_of_reservation")
+    double chance_of_reservation;
+    @JsonProperty("deadline_factor_avg")
+    double deadline_factor_avg;
+    @JsonProperty("deadline_factor_stddev")
+    double deadline_factor_stddev;
+
+    // durations in sec
+    @JsonProperty("dur_avg")
+    double dur_avg;
+    @JsonProperty("dur_stddev")
+    double dur_stddev;
+    @JsonProperty("mtime_avg")
+    double mtime_avg;
+    @JsonProperty("mtime_stddev")
+    double mtime_stddev;
+    @JsonProperty("rtime_avg")
+    double rtime_avg;
+    @JsonProperty("rtime_stddev")
+    double rtime_stddev;
+
+    // number of tasks
+    @JsonProperty("mtasks_avg")
+    double mtasks_avg;
+    @JsonProperty("mtasks_stddev")
+    double mtasks_stddev;
+    @JsonProperty("rtasks_avg")
+    double rtasks_avg;
+    @JsonProperty("rtasks_stddev")
+    double rtasks_stddev;
+
+    // memory in MB
+    @JsonProperty("map_max_memory_avg")
+    long map_max_memory_avg;
+    @JsonProperty("map_max_memory_stddev")
+    double map_max_memory_stddev;
+    @JsonProperty("reduce_max_memory_avg")
+    long reduce_max_memory_avg;
+    @JsonProperty("reduce_max_memory_stddev")
+    double reduce_max_memory_stddev;
+
+    // vcores
+    @JsonProperty("map_max_vcores_avg")
+    long map_max_vcores_avg;
+    @JsonProperty("map_max_vcores_stddev")
+    double map_max_vcores_stddev;
+    @JsonProperty("reduce_max_vcores_avg")
+    long reduce_max_vcores_avg;
+    @JsonProperty("reduce_max_vcores_stddev")
+    double reduce_max_vcores_stddev;
+
+  }
+
+  /**
+   * This is used to define time-varying probability of a job start-time (e.g.,
+   * to simulate daily patterns).
+   */
+  @SuppressWarnings({ "membername", "checkstyle:visibilitymodifier" })
+  public static class TimeSample {
+    // in sec
+    @JsonProperty("time")
+    int time;
+    @JsonProperty("weight")
+    double jobs;
+  }
+
+  static class StoryParams {
+    private SynthJobClass pickedJobClass;
+    private long actualSubmissionTime;
+
+    StoryParams(SynthJobClass pickedJobClass, long actualSubmissionTime) {
+      this.pickedJobClass = pickedJobClass;
+      this.actualSubmissionTime = actualSubmissionTime;
+    }
+  }
+
+
+  void createStoryParams() {
+
+    for (int i = 0; i < numJobs.get(); i++) {
+      int workload = SynthUtils.getWeighted(weightList, rand);
+      SynthWorkload pickedWorkload = workloads.get(workload);
+      long jobClass =
+          SynthUtils.getWeighted(pickedWorkload.getWeightList(), rand);
+      SynthJobClass pickedJobClass =
+          pickedWorkload.getClassList().get((int) jobClass);
+      long actualSubmissionTime = pickedWorkload.getBaseSubmissionTime(rand);
+      // long actualSubmissionTime = (i + 1) * 10;
+      listStoryParams
+          .add(new StoryParams(pickedJobClass, actualSubmissionTime));
+    }
+  }
+
+  @Override
+  public JobStory getNextJob() throws IOException {
+    if (numJobs.decrementAndGet() < 0) {
+      return null;
+    }
+    StoryParams storyParams = listStoryParams.poll();
+    return storyParams.pickedJobClass.getJobStory(conf,
+        storyParams.actualSubmissionTime);
+  }
+
+  @Override
+  public void close() {
+  }
+
+  @Override
+  public String toString() {
+    return "SynthTraceJobProducer [ conf=" + conf + ", numJobs=" + numJobs
+        + ", weightList=" + weightList + ", r=" + rand + ", totalWeight="
+        + totalWeight + ", workloads=" + workloads + "]";
+  }
+
+  public int getNumJobs() {
+    return trace.num_jobs;
+  }
+
+}

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/synthetic/SynthUtils.java

@@ -0,0 +1,101 @@
+/**
+ * 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.hadoop.yarn.sls.synthetic;
+
+import org.apache.commons.math3.distribution.LogNormalDistribution;
+import org.apache.commons.math3.distribution.NormalDistribution;
+import org.apache.commons.math3.random.JDKRandomGenerator;
+
+import java.util.Collection;
+import java.util.Random;
+
+/**
+ * Utils for the Synthetic generator.
+ */
+public final class SynthUtils {
+
+  private SynthUtils(){
+    //class is not meant to be instantiated
+  }
+
+  public static int getWeighted(Collection<Double> weights, Random rr) {
+
+    double totalWeight = 0;
+    for (Double i : weights) {
+      totalWeight += i;
+    }
+
+    double rand = rr.nextDouble() * totalWeight;
+
+    double cur = 0;
+    int ind = 0;
+    for (Double i : weights) {
+      cur += i;
+      if (cur > rand) {
+        break;
+      }
+      ind++;
+    }
+
+    return ind;
+  }
+
+  public static NormalDistribution getNormalDist(JDKRandomGenerator rand,
+      double average, double stdDev) {
+
+    if (average <= 0) {
+      return null;
+    }
+
+    // set default for missing param
+    if (stdDev == 0) {
+      stdDev = average / 6;
+    }
+
+    NormalDistribution ret = new NormalDistribution(average, stdDev,
+        NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
+    ret.reseedRandomGenerator(rand.nextLong());
+    return ret;
+  }
+
+  public static LogNormalDistribution getLogNormalDist(JDKRandomGenerator rand,
+      double mean, double stdDev) {
+
+    if (mean <= 0) {
+      return null;
+    }
+
+    // set default for missing param
+    if (stdDev == 0) {
+      stdDev = mean / 6;
+    }
+
+    // derive lognormal parameters for X = LogNormal(mu, sigma)
+    // sigma^2 = ln (1+Var[X]/(E[X])^2)
+    // mu = ln(E[X]) - 1/2 * sigma^2
+    double var = stdDev * stdDev;
+    double sigmasq = Math.log1p(var / (mean * mean));
+    double sigma = Math.sqrt(sigmasq);
+    double mu = Math.log(mean) - 0.5 * sigmasq;
+
+    LogNormalDistribution ret = new LogNormalDistribution(mu, sigma,
+        LogNormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
+    ret.reseedRandomGenerator(rand.nextLong());
+    return ret;
+  }
+}

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/synthetic/SynthWorkload.java

@@ -0,0 +1,121 @@
+/**
+ * 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.hadoop.yarn.sls.synthetic;
+
+import org.apache.hadoop.yarn.sls.synthetic.SynthTraceJobProducer.Trace;
+
+import java.util.*;
+
+/**
+ * This class represent a workload (made up of multiple SynthJobClass(es)). It
+ * also stores the temporal distributions of jobs in this workload.
+ */
+public class SynthWorkload {
+
+  private final int id;
+  private final List<SynthJobClass> classList;
+  private final Trace trace;
+  private final SortedMap<Integer, Double> timeWeights;
+
+  public SynthWorkload(int identifier, Trace inTrace) {
+    classList = new ArrayList<SynthJobClass>();
+    this.id = identifier;
+    this.trace = inTrace;
+    timeWeights = new TreeMap<Integer, Double>();
+    for (SynthTraceJobProducer.TimeSample ts : trace.workloads
+        .get(id).time_distribution) {
+      timeWeights.put(ts.time, ts.jobs);
+    }
+  }
+
+  public boolean add(SynthJobClass s) {
+    return classList.add(s);
+  }
+
+  public List<Double> getWeightList() {
+    ArrayList<Double> ret = new ArrayList<Double>();
+    for (SynthJobClass s : classList) {
+      ret.add(s.getClassWeight());
+    }
+    return ret;
+  }
+
+  public int getId() {
+    return id;
+  }
+
+  @Override
+  public boolean equals(Object other) {
+    if (!(other instanceof SynthWorkload)) {
+      return false;
+    }
+    // assume ID determines job classes by construction
+    return getId() == ((SynthWorkload) other).getId();
+  }
+
+  @Override
+  public int hashCode() {
+    return getId();
+  }
+
+  @Override
+  public String toString() {
+    return "SynthWorkload " + trace.workloads.get(id).workload_name + "[\n"
+        + classList + "]\n";
+  }
+
+  public String getName() {
+    return trace.workloads.get(id).workload_name;
+  }
+
+  public double getWorkloadWeight() {
+    return trace.workloads.get(id).workload_weight;
+  }
+
+  public String getQueueName() {
+    return trace.workloads.get(id).queue_name;
+  }
+
+  public long getBaseSubmissionTime(Random rand) {
+
+    // pick based on weights the "bucket" for this start time
+    int position = SynthUtils.getWeighted(timeWeights.values(), rand);
+
+    int[] time = new int[timeWeights.keySet().size()];
+    int index = 0;
+    for (Integer i : timeWeights.keySet()) {
+      time[index++] = i;
+    }
+
+    // uniformly pick a time between start and end time of this bucket
+    int startRange = time[position];
+    int endRange = startRange;
+    // if there is no subsequent bucket pick startRange
+    if (position < timeWeights.keySet().size() - 1) {
+      endRange = time[position + 1];
+      return startRange + rand.nextInt((endRange - startRange));
+    } else {
+      return startRange;
+    }
+  }
+
+  public List<SynthJobClass> getClassList() {
+    return classList;
+  }
+
+}

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/synthetic/package-info.java

@@ -0,0 +1,22 @@
+/*
+ * 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.
+ */
+
+/**
+ * Classes comprising the synthetic load generator for SLS.
+ */
+package org.apache.hadoop.yarn.sls.synthetic;

hadoop-tools/hadoop-sls/src/main/java/org/apache/hadoop/yarn/sls/utils/SLSUtils.java

@@ -149,4 +149,13 @@ public class SLSUtils {
     }
     return nodeSet;
   }
+
+  public static Set<? extends String> generateNodesFromSynth(
+      int numNodes, int nodesPerRack) {
+    Set<String> nodeSet = new HashSet<String>();
+    for (int i = 0; i < numNodes; i++) {
+      nodeSet.add("/rack" + i % nodesPerRack + "/node" + i);
+    }
+    return nodeSet;
+  }
 }

hadoop-tools/hadoop-sls/src/site/markdown/SchedulerLoadSimulator.md

@@ -27,9 +27,11 @@ Yarn Scheduler Load Simulator (SLS)
     * [Metrics](#Metrics)
         * [Real-time Tracking](#Real-time_Tracking)
         * [Offline Analysis](#Offline_Analysis)
+    * [Synthetic Load Generator](#SynthGen)
     * [Appendix](#Appendix)
         * [Resources](#Resources)
         * [SLS JSON input file format](#SLS_JSON_input_file_format)
+        * [SYNTH JSON input file format](#SYNTH_JSON_input_file_format)
         * [Simulator input topology file format](#Simulator_input_topology_file_format)
 
 Overview
@@ -72,7 +74,7 @@ The following figure illustrates the implementation architecture of the simulato
 
 ![The architecture of the simulator](images/sls_arch.png)
 
-The simulator takes input of workload traces, and fetches the cluster and applications information. For each NM and AM, the simulator builds a simulator to simulate their running. All NM/AM simulators run in a thread pool. The simulator reuses Yarn Resource Manager, and builds a wrapper out of the scheduler. The Scheduler Wrapper can track the scheduler behaviors and generates several logs, which are the outputs of the simulator and can be further analyzed.
+The simulator takes input of workload traces, or synthetic load distributions and generaters the cluster and applications information. For each NM and AM, the simulator builds a simulator to simulate their running. All NM/AM simulators run in a thread pool. The simulator reuses Yarn Resource Manager, and builds a wrapper out of the scheduler. The Scheduler Wrapper can track the scheduler behaviors and generates several logs, which are the outputs of the simulator and can be further analyzed.
 
 ### Usecases
 
@@ -179,17 +181,30 @@ The simulator supports two types of input files: the rumen traces and its own in
 
     $ cd $HADOOP_ROOT/share/hadoop/tools/sls
     $ bin/slsrun.sh
-      --input-rumen |--input-sls=<TRACE_FILE1,TRACE_FILE2,...>
-      --output-dir=<SLS_SIMULATION_OUTPUT_DIRECTORY> [--nodes=<SLS_NODES_FILE>]
-        [--track-jobs=<JOBID1,JOBID2,...>] [--print-simulation]
+      Usage: slsrun.sh <OPTIONS>
+                 --tracetype=<SYNTH | SLS | RUMEN>
+                 --tracelocation=<FILE1,FILE2,...>
+                 (deprecated --input-rumen=<FILE1,FILE2,...>  | --input-sls=<FILE1,FILE2,...>)
+                 --output-dir=<SLS_SIMULATION_OUTPUT_DIRECTORY>
+                 [--nodes=<SLS_NODES_FILE>]
+                 [--track-jobs=<JOBID1,JOBID2,...>]
+                 [--print-simulation]
+
 
 *   `--input-rumen`: The input rumen trace files. Users can input multiple
     files, separated by comma. One example trace is provided in
     `$HADOOP_ROOT/share/hadoop/tools/sls/sample-data/2jobs2min-rumen-jh.json`.
+    This is equivalent to `--tracetype=RUMEN --tracelocation=<path_to_trace>`.
 
 *   `--input-sls`: Simulator its own file format. The simulator also
     provides a tool to convert rumen traces to sls traces (`rumen2sls.sh`).
     Refer to appendix for an example of sls input json file.
+    This is equivalent to `--tracetype=SLS --tracelocation=<path_to_trace>`.
+
+*   `--tracetype`: This is the new way to configure the trace generation and
+    takes values RUMEN, SLS, or SYNTH, to trigger the three type of load generation
+
+*   `--tracelocation`: Path to the input file, matching the tracetype above.
 
 *   `--output-dir`: The output directory for generated running logs and
     metrics.
@@ -279,12 +294,34 @@ After the simulator finishes, all logs are saved in the output directory specifi
 
 *   Folder `metrics`: logs generated by the Metrics.
 
+Users can also reproduce those real-time tracking charts in offline mode. Just upload the `realtimetrack.json` to `$HADOOP_ROOT/share/hadoop/tools/sls/html/showSimulationTrace.html`. For browser security problem, need to put files `realtimetrack.json` and `showSimulationTrace.html` in the same directory.
+
+
+Synthetic Load Generator
+------------------------
+The Synthetic Load Generator complements the extensive nature of SLS-native and RUMEN traces, by providing a
+distribution-driven generation of load. The load generator is organized as a JobStoryProducer
+(compatible with rumen, and thus gridmix for later integration). We seed the Random number generator so
+that results randomized but deterministic---hence reproducible.
+We organize the jobs being generated around */workloads/job_class* hierarchy, which allow to easily
+group jobs with similar behaviors and categorize them (e.g., jobs with long running containers, or maponly
+computations, etc..). The user can control average and standard deviations for many of the
+important parameters, such as number of mappers/reducers, duration of mapper/reducers, size
+(mem/cpu) of containers, chance of reservation, etc. We use weighted-random sampling (whenever we
+pick among a small number of options) or LogNormal distributions (to avoid negative values) when we
+pick from wide ranges of values---see appendix on LogNormal distributions.
+
+The SYNTH mode of SLS is very convenient to generate very large loads without the need for extensive input
+files. This allows to easily explore wide range of use cases (e.g., imagine simulating 100k jobs, and in different
+runs simply tune the average number of mappers, or average task duration), in an efficient and compact way.
+
 Appendix
 --------
 
 ### Resources
 
 [YARN-1021](https://issues.apache.org/jira/browse/YARN-1021) is the main JIRA that introduces Yarn Scheduler Load Simulator to Hadoop Yarn project.
+[YARN-6363](https://issues.apache.org/jira/browse/YARN-6363) is the main JIRA that introduces the Synthetic Load Generator to SLS.
 
 ### SLS JSON input file format
 
@@ -339,6 +376,77 @@ Here we provide an example format of the sls json file, which contains 2 jobs. T
       } ]
     }
 
+
+### SYNTH JSON input file format
+Here we provide an example format of the synthetic generator json file. We use *(json-non-conforming)* inline comments to explain the use of each parameter.
+
+    {
+      "description" : "tiny jobs workload",    //description of the meaning of this collection of workloads
+      "num_nodes" : 10,  //total nodes in the simulated cluster
+      "nodes_per_rack" : 4, //number of nodes in each simulated rack
+      "num_jobs" : 10, // total number of jobs being simulated
+      "rand_seed" : 2, //the random seed used for deterministic randomized runs
+
+      // a list of “workloads”, each of which has job classes, and temporal properties
+      "workloads" : [
+        {
+          "workload_name" : "tiny-test", // name of the workload
+          "workload_weight": 0.5,  // used for weighted random selection of which workload to sample from
+          "queue_name" : "sls_queue_1", //queue the job will be submitted to
+
+        //different classes of jobs for this workload
+           "job_classes" : [
+            {
+              "class_name" : "class_1", //name of the class
+              "class_weight" : 1.0, //used for weighted random selection of class within workload
+
+              //nextr group controls average and standard deviation of a LogNormal distribution that
+              //determines the number of mappers and reducers for thejob.
+              "mtasks_avg" : 5,
+              "mtasks_stddev" : 1,
+              "rtasks_avg" : 5,
+              "rtasks_stddev" : 1,
+
+              //averge and stdev input param of LogNormal distribution controlling job duration
+              "dur_avg" : 60,
+              "dur_stddev" : 5,
+
+              //averge and stdev input param of LogNormal distribution controlling mappers and reducers durations
+              "mtime_avg" : 10,
+              "mtime_stddev" : 2,
+              "rtime_avg" : 20,
+              "rtime_stddev" : 4,
+
+              //averge and stdev input param of LogNormal distribution controlling memory and cores for map and reduce
+              "map_max_memory_avg" : 1024,
+              "map_max_memory_stddev" : 0.001,
+              "reduce_max_memory_avg" : 2048,
+              "reduce_max_memory_stddev" : 0.001,
+              "map_max_vcores_avg" : 1,
+              "map_max_vcores_stddev" : 0.001,
+              "reduce_max_vcores_avg" : 2,
+              "reduce_max_vcores_stddev" : 0.001,
+
+              //probability of running this job with a reservation
+              "chance_of_reservation" : 0.5,
+              //input parameters of LogNormal distribution that determines the deadline slack (as a multiplier of job duration)
+              "deadline_factor_avg" : 10.0,
+              "deadline_factor_stddev" : 0.001,
+            }
+           ],
+        // for each workload determines with what probability each time bucket is picked to choose the job starttime.
+        // In the example below the jobs have twice as much chance to start in the first minute than in the second minute
+        // of simulation, and then zero chance thereafter.
+          "time_distribution" : [
+            { "time" : 1, "weight" : 66 },
+            { "time" : 60, "weight" : 33 },
+            { "time" : 120, "jobs" : 0 }
+         ]
+        }
+     ]
+    }
+
+
 ### Simulator input topology file format
 
 Here is an example input topology file which has 3 nodes organized in 1 rack.
@@ -353,3 +461,9 @@ Here is an example input topology file which has 3 nodes organized in 1 rack.
         "node" : "node3"
       }]
     }
+
+### Notes on LogNormal distribution:
+LogNormal distributions represent well many of the parameters we see in practice (e.g., most jobs have
+a small number of mappers, but few might be very large, and few very small, but greater than zero. It is
+however worth noticing that it might be tricky to use, as the average is typically on the right side of the
+peak (most common value) of the distribution, because the distribution has a one-side tail.

hadoop-tools/hadoop-sls/src/test/java/org/apache/hadoop/yarn/sls/BaseSLSRunnerTest.java

@@ -0,0 +1,120 @@
+/**
+ * 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.hadoop.yarn.sls;
+
+import net.jcip.annotations.NotThreadSafe;
+import org.apache.commons.lang3.ArrayUtils;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.yarn.conf.YarnConfiguration;
+import org.junit.After;
+import org.junit.Assert;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+import org.junit.runners.Parameterized.Parameter;
+
+import java.io.File;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.UUID;
+
+/**
+ * This is a base class to ease the implementation of SLS-based tests.
+ */
+@RunWith(value = Parameterized.class)
+@NotThreadSafe
+@SuppressWarnings("VisibilityModifier")
+public class BaseSLSRunnerTest {
+
+  @Parameter(value = 0)
+  public String schedulerType;
+
+  @Parameter(value = 1)
+  public String traceType;
+
+  @Parameter(value = 2)
+  public String traceLocation;
+
+  @Parameter(value = 3)
+  public String nodeFile;
+
+  protected SLSRunner sls;
+
+  @After
+  public void tearDown() throws InterruptedException {
+    sls.stop();
+  }
+
+  public void runSLS(Configuration conf, long timeout) throws Exception {
+    File tempDir = new File("target", UUID.randomUUID().toString());
+    final List<Throwable> exceptionList =
+        Collections.synchronizedList(new ArrayList<Throwable>());
+
+    Thread.setDefaultUncaughtExceptionHandler(
+        new Thread.UncaughtExceptionHandler() {
+          @Override
+          public void uncaughtException(Thread t, Throwable e) {
+            e.printStackTrace();
+            exceptionList.add(e);
+          }
+        });
+
+    // start the simulator
+    File slsOutputDir = new File(tempDir.getAbsolutePath() + "/slsoutput/");
+
+    String[] args;
+
+    switch (traceType) {
+    case "OLD_SLS":
+      args = new String[] {"-inputsls", traceLocation, "-output",
+          slsOutputDir.getAbsolutePath()};
+      break;
+    case "OLD_RUMEN":
+      args = new String[] {"-inputrumen", traceLocation, "-output",
+          slsOutputDir.getAbsolutePath()};
+      break;
+    default:
+      args = new String[] {"-tracetype", traceType, "-tracelocation",
+          traceLocation, "-output", slsOutputDir.getAbsolutePath()};
+    }
+
+    if (nodeFile != null) {
+      args = ArrayUtils.addAll(args, new String[] {"-nodes", nodeFile});
+    }
+
+    conf.set(YarnConfiguration.RM_SCHEDULER, schedulerType);
+    sls = new SLSRunner(conf);
+    sls.run(args);
+
+    // wait for timeout seconds before stop, unless there is an uncaught
+    // exception in which
+    // case fail fast.
+    while (timeout >= 0) {
+      Thread.sleep(1000);
+
+      if (!exceptionList.isEmpty()) {
+        sls.stop();
+        Assert.fail("TestSLSRunner catched exception from child thread "
+            + "(TaskRunner.Task): " + exceptionList);
+        break;
+      }
+      timeout--;
+    }
+  }
+
+}

hadoop-tools/hadoop-sls/src/test/java/org/apache/hadoop/yarn/sls/TestSLSRunner.java

@@ -18,53 +18,67 @@
 
 package org.apache.hadoop.yarn.sls;
 
-import org.junit.Assert;
+import net.jcip.annotations.NotThreadSafe;
+import org.apache.hadoop.conf.Configuration;
 import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+import org.junit.runners.Parameterized.*;
 
-import java.io.File;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.List;
-import java.util.UUID;
+import java.util.*;
 
-public class TestSLSRunner {
+/**
+ * This test performs simple runs of the SLS with different trace types and
+ * schedulers.
+ */
+@RunWith(value = Parameterized.class)
+@NotThreadSafe
+public class TestSLSRunner extends BaseSLSRunnerTest {
 
-  @Test
-  @SuppressWarnings("all")
-  public void testSimulatorRunning() throws Exception {
-    File tempDir = new File("target", UUID.randomUUID().toString());
-    final List<Throwable> exceptionList =
-        Collections.synchronizedList(new ArrayList<Throwable>());
+  @Parameters(name = "Testing with: {1}, {0}, (nodeFile {3})")
+  public static Collection<Object[]> data() {
 
-    Thread.setDefaultUncaughtExceptionHandler(new Thread.UncaughtExceptionHandler() {
-      @Override
-      public void uncaughtException(Thread t, Throwable e) {
-        exceptionList.add(e);
-      }
-    });
+    String capScheduler =
+        "org.apache.hadoop.yarn.server.resourcemanager.scheduler."
+            + "capacity.CapacityScheduler";
+    String fairScheduler =
+        "org.apache.hadoop.yarn.server.resourcemanager.scheduler."
+            + "fair.FairScheduler";
+    String slsTraceFile = "src/test/resources/inputsls.json";
+    String rumenTraceFile = "src/main/data/2jobs2min-rumen-jh.json";
+    String synthTraceFile = "src/test/resources/syn.json";
+    String nodeFile = "src/test/resources/nodes.json";
+
+    // Test with both schedulers, and all three load producers.
+    return Arrays.asList(new Object[][] {
 
-    // start the simulator
-    File slsOutputDir = new File(tempDir.getAbsolutePath() + "/slsoutput/");
-    String args[] = new String[]{
-            "-inputrumen", "src/main/data/2jobs2min-rumen-jh.json",
-            "-output", slsOutputDir.getAbsolutePath()};
-    SLSRunner.main(args);
+        // covering old commandline in tests
+        {capScheduler, "OLD_RUMEN", rumenTraceFile, nodeFile },
+        {capScheduler, "OLD_SLS", slsTraceFile, nodeFile },
 
-    // wait for 20 seconds before stop
-    int count = 20;
-    while (count >= 0) {
-      Thread.sleep(1000);
+        // covering the no nodeFile case
+        {capScheduler, "SYNTH", synthTraceFile, null },
+        {capScheduler, "RUMEN", rumenTraceFile, null },
+        {capScheduler, "SLS", slsTraceFile, null },
 
-      if (! exceptionList.isEmpty()) {
-        SLSRunner.getRunner().stop();
-        Assert.fail("TestSLSRunner catched exception from child thread " +
-            "(TaskRunner.Task): " + exceptionList.get(0).getMessage());
-        break;
-      }
-      count--;
-    }
+        // covering new commandline and CapacityScheduler
+        {capScheduler, "SYNTH", synthTraceFile, nodeFile },
+        {capScheduler, "RUMEN", rumenTraceFile, nodeFile },
+        {capScheduler, "SLS", slsTraceFile, nodeFile },
 
-    SLSRunner.getRunner().stop();
+        // covering FairScheduler
+        {fairScheduler, "SYNTH", synthTraceFile, nodeFile },
+        {fairScheduler, "RUMEN", rumenTraceFile, nodeFile },
+        {fairScheduler, "SLS", slsTraceFile, nodeFile }
+    });
+  }
+
+  @Test(timeout = 60000)
+  @SuppressWarnings("all")
+  public void testSimulatorRunning() throws Exception {
+    Configuration conf = new Configuration(false);
+    long timeTillShutdownInsec = 20L;
+    runSLS(conf, timeTillShutdownInsec);
   }
 
 }

hadoop-tools/hadoop-sls/src/test/java/org/apache/hadoop/yarn/sls/TestSynthJobGeneration.java

@@ -0,0 +1,96 @@
+/**
+ * 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.hadoop.yarn.sls;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.mapreduce.TaskType;
+import org.apache.hadoop.tools.rumen.TaskAttemptInfo;
+import org.apache.hadoop.yarn.sls.synthetic.SynthJob;
+import org.apache.hadoop.yarn.sls.synthetic.SynthTraceJobProducer;
+import org.apache.hadoop.mapreduce.MRJobConfig;
+import org.apache.log4j.Logger;
+import org.junit.Assert;
+import org.junit.Test;
+
+import java.io.IOException;
+
+import static org.junit.Assert.assertTrue;
+
+/**
+ * Simple test class driving the {@code SynthTraceJobProducer}, and validating
+ * jobs produce are within expected range.
+ */
+public class TestSynthJobGeneration {
+
+  public final static Logger LOG =
+      Logger.getLogger(TestSynthJobGeneration.class);
+
+  @Test
+  public void test() throws IllegalArgumentException, IOException {
+
+    Configuration conf = new Configuration();
+
+    conf.set(SynthTraceJobProducer.SLS_SYNTHETIC_TRACE_FILE,
+        "src/test/resources/syn.json");
+
+    SynthTraceJobProducer stjp = new SynthTraceJobProducer(conf);
+
+    SynthJob js = (SynthJob) stjp.getNextJob();
+
+    int jobCount = 0;
+
+    while (js != null) {
+      LOG.info((jobCount++) + " " + js.getQueueName() + " -- "
+          + js.getJobClass().getClassName() + " (conf: "
+          + js.getJobConf().get(MRJobConfig.QUEUE_NAME) + ") " + " submission: "
+          + js.getSubmissionTime() + ", " + " duration: " + js.getDuration()
+          + " numMaps: " + js.getNumberMaps() + " numReduces: "
+          + js.getNumberReduces());
+
+      validateJob(js);
+      js = (SynthJob) stjp.getNextJob();
+    }
+
+    Assert.assertEquals(stjp.getNumJobs(), jobCount);
+  }
+
+  private void validateJob(SynthJob js) {
+
+    assertTrue(js.getSubmissionTime() > 0);
+    assertTrue(js.getDuration() > 0);
+    assertTrue(js.getNumberMaps() >= 0);
+    assertTrue(js.getNumberReduces() >= 0);
+    assertTrue(js.getNumberMaps() + js.getNumberReduces() > 0);
+    assertTrue(js.getTotalSlotTime() >= 0);
+
+    for (int i = 0; i < js.getNumberMaps(); i++) {
+      TaskAttemptInfo tai = js.getTaskAttemptInfo(TaskType.MAP, i, 0);
+      assertTrue(tai.getRuntime() > 0);
+    }
+
+    for (int i = 0; i < js.getNumberReduces(); i++) {
+      TaskAttemptInfo tai = js.getTaskAttemptInfo(TaskType.REDUCE, i, 0);
+      assertTrue(tai.getRuntime() > 0);
+    }
+
+    if (js.hasDeadline()) {
+      assertTrue(js.getDeadline() > js.getSubmissionTime() + js.getDuration());
+    }
+
+  }
+}

hadoop-tools/hadoop-sls/src/test/java/org/apache/hadoop/yarn/sls/appmaster/TestAMSimulator.java

@@ -134,7 +134,7 @@ public class TestAMSimulator {
     String queue = "default";
     List<ContainerSimulator> containers = new ArrayList<>();
     app.init(1, 1000, containers, rm, null, 0, 1000000L, "user1", queue,
-        true, appId);
+        true, appId, null, 0);
     app.firstStep();
 
     verifySchedulerMetrics(appId);

hadoop-tools/hadoop-sls/src/test/java/org/apache/hadoop/yarn/sls/scheduler/TestTaskRunner.java

@@ -35,7 +35,7 @@ public class TestTaskRunner {
   }
 
   @After
-  public void cleanUp() {
+  public void cleanUp() throws InterruptedException {
     runner.stop();
   }
 

hadoop-tools/hadoop-sls/src/test/resources/capacity-scheduler.xml

@@ -38,6 +38,16 @@
     <value>100</value>
   </property>
 
+  <property>
+    <name>yarn.scheduler.capacity.root.sls_queue_1.reservable</name>
+    <value>true</value>
+  </property>
+
+  <property>
+    <name>yarn.scheduler.capacity.root.sls_queue_1.show-reservations-as-queues</name>
+    <value>true</value>
+  </property>
+
   <property>
     <name>yarn.scheduler.capacity.root.sls_queue_2.capacity</name>
     <value>25</value>

hadoop-tools/hadoop-sls/src/test/resources/fair-scheduler.xml

@@ -21,6 +21,7 @@
 -->
 
 <allocations>
+  <defaultQueueSchedulingPolicy>drf</defaultQueueSchedulingPolicy>
   <user name="jenkins">
     <!-- Limit on running jobs for the user across all pools. If more
       jobs than this are submitted, only the first <maxRunningJobs> will
@@ -31,20 +32,21 @@
   <userMaxAppsDefault>1000</userMaxAppsDefault>
   <queue name="sls_queue_1">
     <minResources>1024 mb, 1 vcores</minResources>
-    <schedulingMode>fair</schedulingMode>
+    <schedulingPolicy>drf</schedulingPolicy>
     <weight>0.25</weight>
     <minSharePreemptionTimeout>2</minSharePreemptionTimeout>
+    <reservation>true</reservation>
   </queue>
   <queue name="sls_queue_2">
     <minResources>1024 mb, 1 vcores</minResources>
-    <schedulingMode>fair</schedulingMode>
+    <schedulingMode>drf</schedulingMode>
     <weight>0.25</weight>
     <minSharePreemptionTimeout>2</minSharePreemptionTimeout>
   </queue>
   <queue name="sls_queue_3">
     <minResources>1024 mb, 1 vcores</minResources>
     <weight>0.5</weight>
-    <schedulingMode>fair</schedulingMode>
+    <schedulingMode>drf</schedulingMode>
     <minSharePreemptionTimeout>2</minSharePreemptionTimeout>
   </queue>
 </allocations>

hadoop-tools/hadoop-sls/src/test/resources/inputsls.json

@@ -0,0 +1,55 @@
+{
+  "am.type": "mapreduce",
+  "job.start.ms": 0,
+  "job.end.ms": 95375,
+  "job.queue.name": "sls_queue_1",
+  "job.id": "job_1",
+  "job.user": "default",
+  "job.tasks": [
+    {
+      "container.host": "/default-rack/node1",
+      "container.start.ms": 6664,
+      "container.end.ms": 23707,
+      "container.priority": 20,
+      "container.type": "map"
+    },
+    {
+      "container.host": "/default-rack/node3",
+      "container.start.ms": 6665,
+      "container.end.ms": 21593,
+      "container.priority": 20,
+      "container.type": "map"
+    },
+    {
+      "container.host": "/default-rack/node2",
+      "container.start.ms": 68770,
+      "container.end.ms": 86613,
+      "container.priority": 20,
+      "container.type": "map"
+    }
+  ]
+}
+{
+  "am.type": "mapreduce",
+  "job.start.ms": 105204,
+  "job.end.ms": 197256,
+  "job.queue.name": "sls_queue_2",
+  "job.id": "job_2",
+  "job.user": "default",
+  "job.tasks": [
+    {
+      "container.host": "/default-rack/node1",
+      "container.start.ms": 111822,
+      "container.end.ms": 133985,
+      "container.priority": 20,
+      "container.type": "map"
+    },
+    {
+      "container.host": "/default-rack/node2",
+      "container.start.ms": 111788,
+      "container.end.ms": 131377,
+      "container.priority": 20,
+      "container.type": "map"
+    }
+  ]
+}

hadoop-tools/hadoop-sls/src/test/resources/nodes.json

@@ -0,0 +1,84 @@
+{
+  "rack": "rack1",
+  "nodes": [
+    {
+      "node": "node1"
+    },
+    {
+      "node": "node2"
+    },
+    {
+      "node": "node3"
+    },
+    {
+      "node": "node4"
+    }
+  ]
+}
+{
+  "rack": "rack2",
+  "nodes": [
+    {
+      "node": "node5"
+    },
+    {
+      "node": "node6"
+    },
+    {
+      "node": "node7"
+    },
+    {
+      "node": "node8"
+    }
+  ]
+}
+{
+  "rack": "rack3",
+  "nodes": [
+    {
+      "node": "node9"
+    },
+    {
+      "node": "node10"
+    },
+    {
+      "node": "node11"
+    },
+    {
+      "node": "node12"
+    }
+  ]
+}
+{
+  "rack": "rack4",
+  "nodes": [
+    {
+      "node": "node13"
+    },
+    {
+      "node": "node14"
+    },
+    {
+      "node": "node15"
+    },
+    {
+      "node": "node16"
+    }
+  ]
+}
+{
+  "rack": "rack5",
+  "nodes": [
+    {
+      "node": "node17"
+    },
+    {
+      "node": "node18"
+    },
+    {
+      "node": "node19"
+    },
+    {
+    }
+  ]
+}

hadoop-tools/hadoop-sls/src/test/resources/sls-runner.xml

@@ -25,11 +25,11 @@
   <!-- Nodes configuration -->
   <property>
     <name>yarn.sls.nm.memory.mb</name>
-    <value>10240</value>
+    <value>100240</value>
   </property>
   <property>
     <name>yarn.sls.nm.vcores</name>
-    <value>10</value>
+    <value>100</value>
   </property>
   <property>
     <name>yarn.sls.nm.heartbeat.interval.ms</name>
@@ -77,5 +77,5 @@
     <name>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</name>
     <value>org.apache.hadoop.yarn.sls.scheduler.CapacitySchedulerMetrics</value>
   </property>
-  
+
 </configuration>

hadoop-tools/hadoop-sls/src/test/resources/syn.json

@@ -0,0 +1,53 @@
+{
+  "description": "tiny jobs workload",
+  "num_nodes": 20,
+  "nodes_per_rack": 4,
+  "num_jobs": 10,
+  "rand_seed": 2,
+  "workloads": [
+    {
+      "workload_name": "tiny-test",
+      "workload_weight": 0.5,
+      "description": "Sort jobs",
+      "queue_name": "sls_queue_1",
+      "job_classes": [
+        {
+          "class_name": "class_1",
+          "user_name": "foobar",
+          "class_weight": 1.0,
+          "mtasks_avg": 5,
+          "mtasks_stddev": 1,
+          "rtasks_avg": 5,
+          "rtasks_stddev": 1,
+          "dur_avg": 60,
+          "dur_stddev": 5,
+          "mtime_avg": 10,
+          "mtime_stddev": 2,
+          "rtime_avg": 20,
+          "rtime_stddev": 4,
+          "map_max_memory_avg": 1024,
+          "map_max_memory_stddev": 0.001,
+          "reduce_max_memory_avg": 2048,
+          "reduce_max_memory_stddev": 0.001,
+          "map_max_vcores_avg": 1,
+          "map_max_vcores_stddev": 0.001,
+          "reduce_max_vcores_avg": 2,
+          "reduce_max_vcores_stddev": 0.001,
+          "chance_of_reservation": 0.5,
+          "deadline_factor_avg": 10.0,
+          "deadline_factor_stddev": 0.001
+        }
+      ],
+      "time_distribution": [
+        {
+          "time": 1,
+          "weight": 100
+        },
+        {
+          "time": 60,
+          "jobs": 0
+        }
+      ]
+    }
+  ]
+}

hadoop-tools/hadoop-sls/src/test/resources/yarn-site.xml

@@ -17,7 +17,7 @@
 <configuration>
   <property>
     <name>yarn.resourcemanager.scheduler.class</name>
-	  <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
+    <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
     <!-- <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value> -->
   </property>
 
@@ -79,4 +79,12 @@
     <name>yarn.scheduler.fair.assignmultiple</name>
     <value>true</value>
   </property>
+
+
+  <property>
+    <description>Enable reservation system.</description>
+    <name>yarn.resourcemanager.reservation-system.enable</name>
+    <value>true</value>
+  </property>
+
 </configuration>