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diff --git a/src/main/java/org/openecomp/sparky/analytics/HistogramSampler.java b/src/main/java/org/openecomp/sparky/analytics/HistogramSampler.java
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+/**
+ * ============LICENSE_START===================================================
+ * SPARKY (AAI UI service)
+ * ============================================================================
+ * Copyright © 2017 AT&T Intellectual Property.
+ * Copyright © 2017 Amdocs
+ * All rights reserved.
+ * ============================================================================
+ * Licensed 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.
+ * ============LICENSE_END=====================================================
+ *
+ * ECOMP and OpenECOMP are trademarks
+ * and service marks of AT&T Intellectual Property.
+ */
+
+package org.openecomp.sparky.analytics;
+
+/**
+ * A class that models a histogram for reporting and tracking long values with variable steps, bins,
+ * and floating point accuracy.
+ * 
+ * @author davea.
+ */
+public final class HistogramSampler {
+
+  private String label;
+
+  private long binMaxValue;
+
+  private int numBins;
+
+  private double stepSize;
+
+  private long sampleValueTotal;
+
+  private long minValue = -1;
+
+  private long maxValue = 0;
+
+  private long numSamples = 0;
+
+  private long decimalPointAccuracy = 0;
+
+  private static String FORMAT_FLOAT_TEMPLATE = "%%.%df";
+
+  private String floatFormatStr;
+
+  private long[] histogramBins;
+
+  /**
+   * Instantiates a new histogram sampler.
+   *
+   * @param label the label
+   * @param maxValue the max value
+   * @param numBins the num bins
+   * @param decimalPointAccuracy the decimal point accuracy
+   */
+  public HistogramSampler(String label, long maxValue, int numBins, int decimalPointAccuracy) {
+    this.label = label;
+    this.binMaxValue = maxValue;
+    this.numBins = numBins;
+    this.stepSize = ((double) binMaxValue / (double) numBins);
+    this.decimalPointAccuracy = decimalPointAccuracy;
+    this.floatFormatStr = String.format(FORMAT_FLOAT_TEMPLATE, this.decimalPointAccuracy);
+
+    /*
+     * [numBins + 1] => last bin is catch-all for outliers
+     */
+
+    initializeHistogramBins(numBins + 1);
+
+  }
+
+  /**
+   * Initialize histogram bins.
+   *
+   * @param numBins the num bins
+   */
+  private void initializeHistogramBins(int numBins) {
+
+    histogramBins = new long[numBins];
+    int counter = 0;
+    while (counter < numBins) {
+      histogramBins[counter] = 0;
+      counter++;
+    }
+
+  }
+
+  /*
+   * Is it really necessary to synchronize the collection, or should we simply switch the underlying
+   * data type to an AtomicLong
+   */
+
+  /**
+   * Track.
+   *
+   * @param value the value
+   */
+  public synchronized void track(long value) {
+
+    if (value < 0) {
+      return;
+    }
+
+    sampleValueTotal += value;
+    numSamples++;
+
+    if (minValue == -1) {
+      minValue = value;
+    }
+
+    if (value < minValue) {
+      minValue = value;
+    }
+
+    if (value > maxValue) {
+      maxValue = value;
+    }
+
+    /*
+     * One step bin determination
+     */
+
+    if (value < (numBins * stepSize)) {
+
+      int index = (int) (value / stepSize);
+      histogramBins[index]++;
+
+    } else {
+      // peg the metric in the outlier bin
+      histogramBins[numBins - 1]++;
+    }
+
+  }
+
+  /**
+   * Clear.
+   */
+  public void clear() {
+
+    int counter = 0;
+    while (counter < numBins) {
+      histogramBins[counter] = 0;
+      counter++;
+    }
+
+    minValue = -1;
+    maxValue = 0;
+    numSamples = 0;
+    sampleValueTotal = 0;
+
+  }
+
+  /**
+   * Re initialize bins.
+   *
+   * @param label the label
+   * @param numBins the num bins
+   * @param maxValue the max value
+   * @param decimalPointAccuracy the decimal point accuracy
+   */
+  public void reInitializeBins(String label, int numBins, long maxValue, int decimalPointAccuracy) {
+    this.label = label;
+    this.decimalPointAccuracy = decimalPointAccuracy;
+    this.floatFormatStr = String.format(FORMAT_FLOAT_TEMPLATE, this.decimalPointAccuracy);
+    this.numBins = numBins;
+    this.minValue = -1;
+    this.maxValue = 0;
+    initializeHistogramBins(numBins);
+    this.stepSize = (maxValue / numBins);
+    clear();
+  }
+
+  public long getNumberOfSamples() {
+    return numSamples;
+  }
+
+  public long getTotalValueSum() {
+    return sampleValueTotal;
+  }
+
+  /**
+   * Gets the stats.
+   *
+   * @param formatted the formatted
+   * @param indentPadding the indent padding
+   * @return the stats
+   */
+  public String getStats(boolean formatted, String indentPadding) {
+
+    StringBuilder sb = new StringBuilder(128);
+
+
+    if (!formatted) {
+      // generate CSV in the following format
+
+      /*
+       * label,minValue,maxValue,avgValue,numSamples,stepSize,numSteps,stepCounters
+       */
+      sb.append(indentPadding);
+      sb.append(label).append(",");
+      sb.append(minValue).append(",");
+      sb.append(maxValue).append(",");
+      if (numSamples == 0) {
+        sb.append(0).append(",");
+      } else {
+        sb.append((sampleValueTotal / numSamples)).append(",");
+      }
+      sb.append(numSamples).append(",");
+      sb.append(numBins).append(",");
+      sb.append(String.format(floatFormatStr, stepSize));
+
+      int counter = 0;
+      while (counter < numBins) {
+
+        if (counter != (numBins)) {
+          sb.append(",");
+        }
+
+        sb.append(histogramBins[counter]);
+
+        counter++;
+
+      }
+
+      return sb.toString();
+
+    }
+
+    sb.append("\n");
+    sb.append(indentPadding).append("Label = ").append(label).append("\n");
+    sb.append(indentPadding).append("Min = ").append(minValue).append("\n");
+    sb.append(indentPadding).append("Max = ").append(maxValue).append("\n");
+    sb.append(indentPadding).append("numSamples = ").append(numSamples).append("\n");
+
+    if (numSamples == 0) {
+      sb.append(indentPadding).append("Avg = ").append(0).append("\n");
+    } else {
+      sb.append(indentPadding).append("Avg = ").append((sampleValueTotal / numSamples))
+          .append("\n");
+    }
+
+    sb.append(indentPadding).append("StepSize = ").append(String.format(floatFormatStr, stepSize))
+        .append("\n");
+
+    sb.append(indentPadding).append("Sample Histogram:").append("\n");
+
+    int counter = 0;
+    while (counter < numBins) {
+
+      if (counter == (numBins - 1)) {
+        // outlier bin
+        double leftBound = (stepSize * counter);
+        sb.append(indentPadding).append("\t")
+            .append(" x >= " + String.format(floatFormatStr, leftBound) + " : " 
+                + histogramBins[counter])
+            .append("\n");
+
+      } else {
+        double leftBound = (stepSize * counter);
+        double rightBound = ((stepSize) * (counter + 1));
+        sb.append(indentPadding).append("\t")
+            .append((String.format(floatFormatStr, leftBound) + " < x < "
+                + String.format(floatFormatStr, rightBound) + " : " + histogramBins[counter]))
+            .append("\n");
+      }
+
+      counter++;
+
+    }
+
+    return sb.toString();
+
+  }
+
+}