Examples of com.codahale.metrics.MergeableExponentiallyDecayingReservoir

com.codahale.metrics.MergeableExponentiallyDecayingReservoir
rutgers.edu/~graham/pubs/papers/fwddecay.pdf"> Cormode et al., "Forward Decay: A Practical Time Decay Model for Streaming Systems." ICDE '09: Proceedings of the 2009 IEEE International Conference on Data Engineering (2009)

    _event.ownerId = ownerId;
    _name = name;
    _dimension = dimension;
    _deadnessThresholdMs = deadnessThresholdMs;
    _mbeanServer = server;
    _reservoirTimeLagSourceToReceiptMs = new MergeableExponentiallyDecayingReservoir();
    _reservoirTimeLagConsumerCallbacksMs = new MergeableExponentiallyDecayingReservoir();
    resetData();
    registerAsMbean();
  }

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        _reservoirTimeLagSourceToReceiptMs = null;
      }
      else if (_isBootstrapping && !isBootstrapping)
      {
        // bootstrap -> online-consumption transition:  resurrect _reservoirTimeLagSourceToReceiptMs
        _reservoirTimeLagSourceToReceiptMs = new MergeableExponentiallyDecayingReservoir();
      }
      _isBootstrapping = isBootstrapping;
      _event.curBootstrappingPartitions = isBootstrapping ? 1 : 0;
    }
    finally

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  private static final long NUM_NSECS_IN_MSEC = 1000000L;


  @Test
  public void testEmptyReservoir()
  {
    MergeableExponentiallyDecayingReservoir res = new MergeableExponentiallyDecayingReservoir(10, 0.015);


    // add NO data


    double[] dataValues = res.getUnsortedValues();
    assertEquals("expected empty dataValues array", 0, dataValues.length);
    double result = StatUtils.percentile(dataValues, 50.0);
    assertEquals("expected NaN for 50th percentile of empty array", Double.NaN, result);
    result = StatUtils.max(dataValues);
    assertEquals("expected NaN for max of empty array", Double.NaN, result);

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   */
  @Test
  public void testReservoirMergeAndLandmarkSynch() throws InterruptedException
  {
    // two low-level reservoirs and one aggregator
    MergeableExponentiallyDecayingReservoir res1;
    MergeableExponentiallyDecayingReservoir res2;
    MergeableExponentiallyDecayingReservoir aggr;


    aggr = new MergeableExponentiallyDecayingReservoir(10, 0.015);
    Thread.sleep(1000L);
    res1 = new MergeableExponentiallyDecayingReservoir(10, 0.015);
    Thread.sleep(1000L);
    res2 = new MergeableExponentiallyDecayingReservoir(10, 0.015);


    //long origLandmarkAggr = aggr.getLandmark();
    long origLandmarkRes1 = res1.getLandmark();
    long origLandmarkRes2 = res2.getLandmark();
    assertTrue("expected aggregator to have older landmark value than res1", aggr.getLandmark() < origLandmarkRes1);
    assertTrue("expected res1 to have older landmark value than res2", origLandmarkRes1 < origLandmarkRes2);


    // generate some data for both low-level reservoirs, then make sure their landmarks don't change
    for (int i = 0; i < 10; ++i)
    {
      long nowSecs = System.currentTimeMillis() / NUM_MSECS_IN_SEC;
      long timestamp1 = nowSecs - i - 3L;
      long timestamp2 = nowSecs - i - 5L;


      res1.update((double)i, timestamp1);
      res2.update((double)(i+100), timestamp2);
    }
    assertEquals("expected res1 landmark value to be unchanged", origLandmarkRes1, res1.getLandmark());
    assertEquals("expected res2 landmark value to be unchanged", origLandmarkRes2, res2.getLandmark());


    aggr.merge(res1);
    assertEquals("expected res1 landmark value to be unchanged", origLandmarkRes1, res1.getLandmark());
    assertEquals("expected aggregator landmark value to match res1", origLandmarkRes1, aggr.getLandmark());


    aggr.merge(res2);
    assertEquals("expected res2 landmark value to be unchanged", origLandmarkRes2, res2.getLandmark());
    assertEquals("expected aggregator landmark value to match res2", origLandmarkRes2, aggr.getLandmark());


    // generate some more data for both low-level reservoirs; their landmarks still should not have changed
    for (int i = 0; i < 10; ++i)
    {
      long nowSecs = System.currentTimeMillis() / NUM_MSECS_IN_SEC;
      long timestamp1 = nowSecs - i - 1L;
      long timestamp2 = nowSecs - i - 2L;


      res1.update((double)(i+200), timestamp1);
      res2.update((double)(i+300), timestamp2);
    }
    assertEquals("expected res1 landmark value to be unchanged", origLandmarkRes1, res1.getLandmark());
    assertEquals("expected res2 landmark value to be unchanged", origLandmarkRes2, res2.getLandmark());


    aggr.merge(res1);
    assertEquals("expected aggregator landmark value to be unchanged", origLandmarkRes2, aggr.getLandmark());
    assertEquals("expected res1 landmark value to match res2", origLandmarkRes2, res1.getLandmark());
  }

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  // Q[99th]  =  x[10-1] + (10.89 - 10)*(x[10-1+1] - x[10-1])  =  10.0 + 0.89*(10.0 - 10.0)  =  10.0
  @Test
  public void testReservoirReplacement()
  {
    ManuallyControllableClock clock = new ManuallyControllableClock();
    MergeableExponentiallyDecayingReservoir res = new MergeableExponentiallyDecayingReservoir(10, 0.015, clock);


    clock.advanceTime(1L * NUM_MSECS_IN_SEC * NUM_NSECS_IN_MSEC);  // initial data show up 1 sec after reservoir created
    res.update(3.0);
    res.update(8.0);
    res.update(9.0);
    res.update(4.0);
    res.update(7.0);
    res.update(5.0);
    res.update(2.0);
    res.update(10.0);
    res.update(6.0);
    res.update(1.0);


    double[] dataValues = res.getUnsortedValues();
    assertEquals("expected non-empty dataValues array", 10, dataValues.length);
    double result = StatUtils.percentile(dataValues, 50.0);
    assertEquals("unexpected 50th percentile", 5.5, result);
    result = StatUtils.percentile(dataValues, 90.0);
    assertEquals("unexpected 90th percentile", 9.9, result);
    result = StatUtils.percentile(dataValues, 95.0);
    assertEquals("unexpected 95th percentile", 10.0, result);
    result = StatUtils.percentile(dataValues, 99.0);
    assertEquals("unexpected 99th percentile", 10.0, result);
    result = StatUtils.max(dataValues);
    assertEquals("unexpected max", 10.0, result);
    result = StatUtils.min(dataValues);
    assertEquals("unexpected min", 1.0, result);


    // Now advance the time and add a couple more values.  We don't control the random-number generation,
    // so we don't know the priorities of either the original 10 data points or the two new ones, but we
    // do expect the new ones to have higher priorities than most or all of the original set, thanks to
    // their "newness" (by half an hour) and the alpha value that exponentially weights data from the most
    // recent 5 minutes.  Since they're bigger/smaller than all the rest of the data values, the new max/min
    // values should reflect them regardless of which older data points they preempted.


    clock.advanceTime(1800L * NUM_MSECS_IN_SEC * NUM_NSECS_IN_MSEC);  // new data show up 30 min after initial set
    res.update(20.0);
    res.update(0.0);


    dataValues = res.getUnsortedValues();
    assertEquals("expected size for dataValues array", 10, dataValues.length);
    result = StatUtils.max(dataValues);
    assertEquals("unexpected max", 20.0, result);
    result = StatUtils.min(dataValues);
    assertEquals("unexpected min", 0.0, result);

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  }


  @Test
  public void testReservoirWithIdenticalValues()
  {
    MergeableExponentiallyDecayingReservoir res = new MergeableExponentiallyDecayingReservoir(10, 0.015);


    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);
    res.update(7.0);


    double[] dataValues = res.getUnsortedValues();
    assertEquals("expected non-empty dataValues array", 10, dataValues.length);
    double result = StatUtils.percentile(dataValues, 50.0);
    assertEquals("expected 50th percentile to equal (constant) value of data points", 7.0, result);
    result = StatUtils.percentile(dataValues, 90.0);
    assertEquals("expected 90th percentile to equal (constant) value of data points", 7.0, result);

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  }


  @Test
  public void testReservoirWithSingleDatum()
  {
    MergeableExponentiallyDecayingReservoir res = new MergeableExponentiallyDecayingReservoir(10, 0.015);


    res.update(3.0);


    double[] dataValues = res.getUnsortedValues();
    assertEquals("expected non-empty dataValues array", 1, dataValues.length);
    double result = StatUtils.percentile(dataValues, 50.0);
    assertEquals("expected 50th percentile to equal value of single data point", 3.0, result);
    result = StatUtils.percentile(dataValues, 90.0);
    assertEquals("expected 90th percentile to equal value of single data point", 3.0, result);

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