Examples with HeuristicResult com.linkedin.drelephant.analysis.HeuristicResult used on opensource projects

Example 46 with HeuristicResult

use of com.linkedin.drelephant.analysis.HeuristicResult in project dr-elephant by linkedin.

the class MapperTimeHeuristic method apply.

@Override
public HeuristicResult apply(MapReduceApplicationData data) {
    if (!data.getSucceeded()) {
        return null;
    }
    MapReduceTaskData[] tasks = data.getMapperData();
    List<Long> inputBytes = new ArrayList<Long>();
    List<Long> runtimesMs = new ArrayList<Long>();
    long taskMinMs = Long.MAX_VALUE;
    long taskMaxMs = 0;
    for (MapReduceTaskData task : tasks) {
        if (task.isTimeAndCounterDataPresent()) {
            long inputByte = 0;
            for (MapReduceCounterData.CounterName counterName : _counterNames) {
                inputByte += task.getCounters().get(counterName);
            }
            inputBytes.add(inputByte);
            long taskTime = task.getTotalRunTimeMs();
            runtimesMs.add(taskTime);
            taskMinMs = Math.min(taskMinMs, taskTime);
            taskMaxMs = Math.max(taskMaxMs, taskTime);
        }
    }
    if (taskMinMs == Long.MAX_VALUE) {
        taskMinMs = 0;
    }
    long averageSize = Statistics.average(inputBytes);
    long averageTimeMs = Statistics.average(runtimesMs);
    Severity shortTaskSeverity = shortTaskSeverity(tasks.length, averageTimeMs);
    Severity longTaskSeverity = longTaskSeverity(tasks.length, averageTimeMs);
    Severity severity = Severity.max(shortTaskSeverity, longTaskSeverity);
    HeuristicResult result = new HeuristicResult(_heuristicConfData.getClassName(), _heuristicConfData.getHeuristicName(), severity, Utils.getHeuristicScore(severity, tasks.length));
    result.addResultDetail("Number of tasks", Integer.toString(tasks.length));
    result.addResultDetail("Average task input size", FileUtils.byteCountToDisplaySize(averageSize));
    result.addResultDetail("Average task runtime", Statistics.readableTimespan(averageTimeMs));
    result.addResultDetail("Max task runtime", Statistics.readableTimespan(taskMaxMs));
    result.addResultDetail("Min task runtime", Statistics.readableTimespan(taskMinMs));
    return result;
}

Example 47 with HeuristicResult

use of com.linkedin.drelephant.analysis.HeuristicResult in project dr-elephant by linkedin.

the class GenericGCHeuristic method apply.

public HeuristicResult apply(TezApplicationData data) {
    if (!data.getSucceeded()) {
        return null;
    }
    TezTaskData[] tasks = getTasks(data);
    List<Long> gcMs = new ArrayList<Long>();
    List<Long> cpuMs = new ArrayList<Long>();
    List<Long> runtimesMs = new ArrayList<Long>();
    for (TezTaskData task : tasks) {
        if (task.isSampled()) {
            runtimesMs.add(task.getTotalRunTimeMs());
            gcMs.add(task.getCounters().get(TezCounterData.CounterName.GC_TIME_MILLIS));
            cpuMs.add(task.getCounters().get(TezCounterData.CounterName.CPU_MILLISECONDS));
        }
    }
    long avgRuntimeMs = Statistics.average(runtimesMs);
    long avgCpuMs = Statistics.average(cpuMs);
    long avgGcMs = Statistics.average(gcMs);
    double ratio = avgCpuMs != 0 ? avgGcMs * (1.0) / avgCpuMs : 0;
    Severity severity;
    if (tasks.length == 0) {
        severity = Severity.NONE;
    } else {
        severity = getGcRatioSeverity(avgRuntimeMs, avgCpuMs, avgGcMs);
    }
    HeuristicResult result = new HeuristicResult(_heuristicConfData.getClassName(), _heuristicConfData.getHeuristicName(), severity, Utils.getHeuristicScore(severity, tasks.length));
    result.addResultDetail("Number of tasks", Integer.toString(tasks.length));
    result.addResultDetail("Avg task runtime (ms)", Long.toString(avgRuntimeMs));
    result.addResultDetail("Avg task CPU time (ms)", Long.toString(avgCpuMs));
    result.addResultDetail("Avg task GC time (ms)", Long.toString(avgGcMs));
    result.addResultDetail("Task GC/CPU ratio", Double.toString(ratio));
    return result;
}

Example 48 with HeuristicResult

use of com.linkedin.drelephant.analysis.HeuristicResult in project dr-elephant by linkedin.

the class GenericMemoryHeuristic method apply.

public HeuristicResult apply(TezApplicationData data) {
    if (!data.getSucceeded()) {
        return null;
    }
    TezTaskData[] tasks = getTasks(data);
    List<Long> totalPhysicalMemory = new LinkedList<Long>();
    List<Long> totalVirtualMemory = new LinkedList<Long>();
    List<Long> runTime = new LinkedList<Long>();
    for (TezTaskData task : tasks) {
        if (task.isSampled()) {
            totalPhysicalMemory.add(task.getCounters().get(TezCounterData.CounterName.PHYSICAL_MEMORY_BYTES));
            totalVirtualMemory.add(task.getCounters().get(TezCounterData.CounterName.VIRTUAL_MEMORY_BYTES));
            runTime.add(task.getTotalRunTimeMs());
        }
    }
    long averagePMem = Statistics.average(totalPhysicalMemory);
    long averageVMem = Statistics.average(totalVirtualMemory);
    long maxPMem;
    long minPMem;
    try {
        maxPMem = Collections.max(totalPhysicalMemory);
        minPMem = Collections.min(totalPhysicalMemory);
    } catch (Exception exception) {
        maxPMem = 0;
        minPMem = 0;
    }
    long averageRunTime = Statistics.average(runTime);
    String containerSizeStr;
    if (!Strings.isNullOrEmpty(data.getConf().getProperty(_containerMemConf))) {
        containerSizeStr = data.getConf().getProperty(_containerMemConf);
    } else {
        containerSizeStr = getContainerMemDefaultMBytes();
    }
    long containerSize = Long.valueOf(containerSizeStr) * FileUtils.ONE_MB;
    double averageMemMb = (double) ((averagePMem) / FileUtils.ONE_MB);
    double ratio = averageMemMb / ((double) (containerSize / FileUtils.ONE_MB));
    Severity severity;
    if (tasks.length == 0) {
        severity = Severity.NONE;
    } else {
        severity = getMemoryRatioSeverity(ratio);
    }
    HeuristicResult result = new HeuristicResult(_heuristicConfData.getClassName(), _heuristicConfData.getHeuristicName(), severity, Utils.getHeuristicScore(severity, tasks.length));
    result.addResultDetail("Number of tasks", Integer.toString(tasks.length));
    result.addResultDetail("Maximum Physical Memory (MB)", tasks.length == 0 ? "0" : Long.toString(maxPMem / FileUtils.ONE_MB));
    result.addResultDetail("Minimum Physical memory (MB)", tasks.length == 0 ? "0" : Long.toString(minPMem / FileUtils.ONE_MB));
    result.addResultDetail("Average Physical Memory (MB)", tasks.length == 0 ? "0" : Long.toString(averagePMem / FileUtils.ONE_MB));
    result.addResultDetail("Average Virtual Memory (MB)", tasks.length == 0 ? "0" : Long.toString(averageVMem / FileUtils.ONE_MB));
    result.addResultDetail("Average Task RunTime", tasks.length == 0 ? "0" : Statistics.readableTimespan(averageRunTime));
    result.addResultDetail("Requested Container Memory (MB)", (tasks.length == 0 || containerSize == 0 || containerSize == -1) ? "0" : String.valueOf(containerSize / FileUtils.ONE_MB));
    return result;
}