HBASE-6131 Add attribution for code added by HBASE-5533 metrics

git-svn-id: https://svn.apache.org/repos/asf/hbase/trunk@1344299 13f79535-47bb-0310-9956-ffa450edef68

hbase-server/pom.xml

@@ -297,6 +297,10 @@
 
   <dependencies>
     <!-- General dependencies -->
+    <dependency>
+      <groupId>com.yammer.metrics</groupId>
+      <artifactId>metrics-core</artifactId>
+    </dependency>
     <dependency>
       <groupId>com.google.guava</groupId>
       <artifactId>guava</artifactId>

hbase-server/src/main/java/org/apache/hadoop/hbase/metrics/histogram/ExponentiallyDecayingSample.java

@@ -1,226 +0,0 @@
-/**
- * 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.hbase.metrics.histogram;
-
-import java.util.ArrayList;
-import java.util.Random;
-import java.util.concurrent.ConcurrentSkipListMap;
-import java.util.concurrent.Executors;
-import java.util.concurrent.ScheduledExecutorService;
-import java.util.concurrent.ThreadFactory;
-import java.util.concurrent.TimeUnit;
-import java.util.concurrent.atomic.AtomicInteger;
-import java.util.concurrent.atomic.AtomicLong;
-import java.util.concurrent.locks.ReentrantReadWriteLock;
-
-/**
- * An exponentially-decaying random sample of {@code long}s. 
- * Uses Cormode et al's forward-decaying priority reservoir sampling method 
- * to produce a statistically representative sample, exponentially biased 
- * towards newer entries.
- *
- * see Cormode et al. 
- * Forward Decay: A Practical Time Decay Model for Streaming Systems. ICDE '09
- */
-public class ExponentiallyDecayingSample implements Sample {
-
-  private static final Random RANDOM = new Random();  
-  private static final long RESCALE_THRESHOLD = TimeUnit.HOURS.toNanos(1);
-
-  private static final ScheduledExecutorService TICK_SERVICE = 
-    Executors.newScheduledThreadPool(1, 
-      getNamedDaemonThreadFactory(Thread.currentThread().getName() + ".decayingSampleTick."));
-
-  private static volatile long CURRENT_TICK = 
-      TimeUnit.MILLISECONDS.toSeconds(System.currentTimeMillis());
-
-  static {
-    // sample at twice our signal's frequency (1Hz) per the Nyquist theorem
-    TICK_SERVICE.scheduleAtFixedRate(new Runnable() {
-      @Override
-      public void run() {
-        CURRENT_TICK = 
-            TimeUnit.MILLISECONDS.toSeconds(System.currentTimeMillis());
-      }
-    }, 0, 500, TimeUnit.MILLISECONDS);
-  }
-  
-  private final ConcurrentSkipListMap<Double, Long> values = 
-      new ConcurrentSkipListMap<Double, Long>();
-  private final ReentrantReadWriteLock lock = new ReentrantReadWriteLock();
-  private final AtomicLong count = new AtomicLong(0);
-  private final AtomicLong nextScaleTime = new AtomicLong(0);
-
-  private final double alpha;
-  private final int reservoirSize;
-  private volatile long startTime;
-
-  /**
-   * Constructor for an ExponentiallyDecayingSample.
-   *
-   * @param reservoirSize the number of samples to keep in the reservoir
-   * @param alpha         the exponential decay factor; the higher this is, 
-   *                      the more biased the sample will be towards newer 
-   *                      values
-   */
-  public ExponentiallyDecayingSample(int reservoirSize, double alpha) {
-    this.alpha = alpha;
-    this.reservoirSize = reservoirSize;
-    clear();
-  }
-
-  @Override
-  public void clear() {
-    lockForRescale();
-    try {
-      values.clear();
-      count.set(0);
-      this.startTime = CURRENT_TICK;
-      nextScaleTime.set(System.nanoTime() + RESCALE_THRESHOLD);
-    } finally {
-      unlockForRescale();
-    }
-  }
-
-  @Override
-  public int size() {
-    return (int) Math.min(reservoirSize, count.get());
-  }
-
-  @Override
-  public void update(long value) {
-    update(value, CURRENT_TICK);
-  }
-
-  /**
-   * Adds an old value with a fixed timestamp to the sample.
-   *
-   * @param value     the value to be added
-   * @param timestamp the epoch timestamp of {@code value} in seconds
-   */
-  public void update(long value, long timestamp) {
-    lockForRegularUsage();
-    try {
-      final double priority = weight(timestamp - startTime) 
-          / RANDOM.nextDouble();
-      final long newCount = count.incrementAndGet();
-      if (newCount <= reservoirSize) {
-        values.put(priority, value);
-      } else {
-        Double first = values.firstKey();
-        if (first < priority) {
-          if (values.putIfAbsent(priority, value) == null) {
-            // ensure we always remove an item
-            while (values.remove(first) == null) {
-              first = values.firstKey();
-            }
-          }
-        }
-      }
-    } finally {
-      unlockForRegularUsage();
-    }
-
-    final long now = System.nanoTime();
-    final long next = nextScaleTime.get();
-    if (now >= next) {
-      rescale(now, next);
-    }
-  }
-
-  @Override
-  public Snapshot getSnapshot() {
-    lockForRegularUsage();
-    try {
-      return new Snapshot(values.values());
-    } finally {
-      unlockForRegularUsage();
-    }
-  }
-
-  private double weight(long t) {
-    return Math.exp(alpha * t);
-  }
-
-  /* "A common feature of the above techniques—indeed, the key technique that
-   * allows us to track the decayed weights efficiently—is that they maintain
-   * counts and other quantities based on g(ti − L), and only scale by g(t − L)
-   * at query time. But while g(ti −L)/g(t−L) is guaranteed to lie between zero
-   * and one, the intermediate values of g(ti − L) could become very large. For
-   * polynomial functions, these values should not grow too large, and should 
-   * be effectively represented in practice by floating point values without 
-   * loss of precision. For exponential functions, these values could grow 
-   * quite large as new values of (ti − L) become large, and potentially 
-   * exceed the capacity of common floating point types. However, since the 
-   * values stored by the algorithms are linear combinations of g values 
-   * (scaled sums), they can be rescaled relative to a new landmark. That is, 
-   * by the analysis of exponential decay in Section III-A, the choice of L 
-   * does not affect the final result. We can therefore multiply each value 
-   * based on L by a factor of exp(−α(L′ − L)), and obtain the correct value 
-   * as if we had instead computed relative to a new landmark L′ (and then use 
-   * this new L′ at query time). This can be done with a linear pass over 
-   * whatever data structure is being used."
-   */
-  private void rescale(long now, long next) {
-    if (nextScaleTime.compareAndSet(next, now + RESCALE_THRESHOLD)) {
-      lockForRescale();
-      try {
-        final long oldStartTime = startTime;
-        this.startTime = CURRENT_TICK;
-        final ArrayList<Double> keys = new ArrayList<Double>(values.keySet());
-        for (Double key : keys) {
-          final Long value = values.remove(key);
-          values.put(key * Math.exp(-alpha * (startTime - oldStartTime)), 
-              value);
-        }
-      } finally {
-        unlockForRescale();
-      }
-    }
-  }
-
-  private void unlockForRescale() {
-    lock.writeLock().unlock();
-  }
-
-  private void lockForRescale() {
-    lock.writeLock().lock();
-  }
-
-  private void lockForRegularUsage() {
-    lock.readLock().lock();
-  }
-
-  private void unlockForRegularUsage() {
-    lock.readLock().unlock();
-  }
-
-  private static ThreadFactory getNamedDaemonThreadFactory(final String prefix) {
-    return new ThreadFactory() {
-
-      private final AtomicInteger threadNumber = new AtomicInteger(1);
-      
-      @Override
-      public Thread newThread(Runnable r) {
-        Thread t= new Thread(r, prefix + threadNumber.getAndIncrement());
-        t.setDaemon(true);
-        return t;
-      }
-    };
-  }
-}

hbase-server/src/main/java/org/apache/hadoop/hbase/metrics/histogram/MetricsHistogram.java

@@ -25,6 +25,11 @@ import org.apache.hadoop.metrics.MetricsRecord;
 import org.apache.hadoop.metrics.util.MetricsBase;
 import org.apache.hadoop.metrics.util.MetricsRegistry;
 
+import com.yammer.metrics.stats.Sample;
+import com.yammer.metrics.stats.Snapshot;
+import com.yammer.metrics.stats.UniformSample;
+import com.yammer.metrics.stats.ExponentiallyDecayingSample;
+
 public class MetricsHistogram extends MetricsBase {
   
   // 1028 items implies 99.9% CI w/ 5% margin of error 

hbase-server/src/main/java/org/apache/hadoop/hbase/metrics/histogram/Sample.java

@@ -1,49 +0,0 @@
-/**
- * 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.hbase.metrics.histogram;
-
-/**
- * A statistically representative sample of items from a stream.
- */
-public interface Sample {
-  /**
-   * Clears all recorded values.
-   */
-  void clear();
-
-  /**
-   * Returns the number of values recorded.
-   *
-   * @return the number of values recorded
-   */
-  int size();
-
-  /**
-   * Adds a new recorded value to the sample.
-   *
-   * @param value a new recorded value
-   */
-  void update(long value);
-
-  /**
-   * Returns a snapshot of the sample's values.
-   *
-   * @return a snapshot of the sample's values
-   */
-  Snapshot getSnapshot();
-}

hbase-server/src/main/java/org/apache/hadoop/hbase/metrics/histogram/Snapshot.java

@@ -1,166 +0,0 @@
-/**
- * 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.hbase.metrics.histogram;
-
-import java.io.File;
-import java.io.IOException;
-import java.io.PrintWriter;
-import java.util.Arrays;
-import java.util.Collection;
-
-/**
- * A snapshot of all the information seen in a Sample.
- */
-public class Snapshot {
-
-  private static final double MEDIAN_Q = 0.5;
-  private static final double P75_Q = 0.75;
-  private static final double P95_Q = 0.95;
-  private static final double P98_Q = 0.98;
-  private static final double P99_Q = 0.99;
-  private static final double P999_Q = 0.999;
-
-  private final double[] values;
-
-  /**
-   * Create a new {@link Snapshot} with the given values.
-   *
-   * @param values    an unordered set of values in the sample
-   */
-  public Snapshot(Collection<Long> values) {
-    final Object[] copy = values.toArray();
-    this.values = new double[copy.length];
-    for (int i = 0; i < copy.length; i++) {
-      this.values[i] = (Long) copy[i];
-    }
-    Arrays.sort(this.values);
-  }
-
-  /**
-   * Create a new {@link Snapshot} with the given values.
-   *
-   * @param values    an unordered set of values in the sample
-   */
-  public Snapshot(double[] values) {
-    this.values = new double[values.length];
-    System.arraycopy(values, 0, this.values, 0, values.length);
-    Arrays.sort(this.values);
-  }
-
-  /**
-   * Returns the value at the given quantile.
-   *
-   * @param quantile    a given quantile, in [0..1]
-   * @return the value in the distribution at quantile
-   */
-  public double getValue(double quantile) {
-    if (quantile < 0.0 || quantile > 1.0) {
-      throw new IllegalArgumentException(quantile + " is not in [0..1]");
-    }
-
-    if (values.length == 0) {
-      return 0.0;
-    }
-
-    final double pos = quantile * (values.length + 1);
-
-    if (pos < 1) {
-      return values[0];
-    }
-
-    if (pos >= values.length) {
-      return values[values.length - 1];
-    }
-
-    final double lower = values[(int) pos - 1];
-    final double upper = values[(int) pos];
-    return lower + (pos - Math.floor(pos)) * (upper - lower);
-  }
-
-  /**
-   * Returns the number of values in the snapshot.
-   *
-   * @return the number of values in the snapshot
-   */
-  public int size() {
-    return values.length;
-  }
-
-  /**
-   * Returns the median value in the distribution.
-   *
-   * @return the median value in the distribution
-   */
-  public double getMedian() {
-    return getValue(MEDIAN_Q);
-  }
-
-  /**
-   * Returns the value at the 75th percentile in the distribution.
-   *
-   * @return the value at the 75th percentile in the distribution
-   */
-  public double get75thPercentile() {
-    return getValue(P75_Q);
-  }
-
-  /**
-   * Returns the value at the 95th percentile in the distribution.
-   *
-   * @return the value at the 95th percentile in the distribution
-   */
-  public double get95thPercentile() {
-    return getValue(P95_Q);
-  }
-
-  /**
-   * Returns the value at the 98th percentile in the distribution.
-   *
-   * @return the value at the 98th percentile in the distribution
-   */
-  public double get98thPercentile() {
-    return getValue(P98_Q);
-  }
-
-  /**
-   * Returns the value at the 99th percentile in the distribution.
-   *
-   * @return the value at the 99th percentile in the distribution
-   */
-  public double get99thPercentile() {
-    return getValue(P99_Q);
-  }
-
-  /**
-   * Returns the value at the 99.9th percentile in the distribution.
-   *
-   * @return the value at the 99.9th percentile in the distribution
-   */
-  public double get999thPercentile() {
-    return getValue(P999_Q);
-  }
-
-  /**
-   * Returns the entire set of values in the snapshot.
-   *
-   * @return the entire set of values in the snapshot
-   */
-  public double[] getValues() {
-    return Arrays.copyOf(values, values.length);
-  }
-}

hbase-server/src/main/java/org/apache/hadoop/hbase/metrics/histogram/UniformSample.java

@@ -1,105 +0,0 @@
-/**
- * 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.hbase.metrics.histogram;
-
-import java.util.ArrayList;
-import java.util.List;
-import java.util.Random;
-import java.util.concurrent.atomic.AtomicLong;
-import java.util.concurrent.atomic.AtomicLongArray;
-
-/**
- * A random sample of a stream of longs. Uses Vitter's Algorithm R to produce a
- * statistically representative sample.
- *
- * see: http://www.cs.umd.edu/~samir/498/vitter.pdf
- */
-public class UniformSample implements Sample {
-  
-  private static final Random RANDOM = new Random();
-  private static final int BITS_PER_LONG = 63;
-  
-  private final AtomicLong count = new AtomicLong();
-  private final AtomicLongArray values;
-
-  /**
-   * Creates a new UniformSample
-   *
-   * @param reservoirSize the number of samples to keep
-   */
-  public UniformSample(int reservoirSize) {
-    this.values = new AtomicLongArray(reservoirSize);
-    clear();
-  }
-
-  @Override
-  public void clear() {
-    for (int i = 0; i < values.length(); i++) {
-      values.set(i, 0);
-    }
-    count.set(0);
-  }
-
-  @Override
-  public int size() {
-    final long c = count.get();
-    if (c > values.length()) {
-      return values.length();
-    }
-    return (int) c;
-  }
-
-  @Override
-  public void update(long value) {
-    final long c = count.incrementAndGet();
-    if (c <= values.length()) {
-      values.set((int) c - 1, value);
-    } else {
-      final long r = nextLong(c);
-      if (r < values.length()) {
-        values.set((int) r, value);
-      }
-    }
-  }
-
-  /**
-   * Get a pseudo-random long uniformly between 0 and n-1. Stolen from
-   * {@link java.util.Random#nextInt()}.
-   *
-   * @param n the bound
-   * @return a value select randomly from the range {@code [0..n)}.
-   */
-  private static long nextLong(long n) {
-    long bits, val;
-    do {
-      bits = RANDOM.nextLong() & (~(1L << BITS_PER_LONG));
-      val = bits % n;
-    } while (bits - val + (n - 1) < 0L);
-    return val;
-  }
-
-  @Override
-  public Snapshot getSnapshot() {
-    final int s = size();
-    final List<Long> copy = new ArrayList<Long>(s);
-    for (int i = 0; i < s; i++) {
-      copy.add(values.get(i));
-    }
-    return new Snapshot(copy);
-  }
-}

hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/metrics/RegionServerMetrics.java

@@ -33,7 +33,7 @@ import org.apache.hadoop.hbase.metrics.HBaseInfo;
 import org.apache.hadoop.hbase.metrics.MetricsRate;
 import org.apache.hadoop.hbase.metrics.PersistentMetricsTimeVaryingRate;
 import org.apache.hadoop.hbase.metrics.histogram.MetricsHistogram;
-import org.apache.hadoop.hbase.metrics.histogram.Snapshot;
+import com.yammer.metrics.stats.Snapshot;
 import org.apache.hadoop.hbase.regionserver.wal.HLog;
 import org.apache.hadoop.hbase.util.Pair;
 import org.apache.hadoop.hbase.util.Strings;

hbase-server/src/test/java/org/apache/hadoop/hbase/metrics/TestExponentiallyDecayingSample.java

@@ -20,8 +20,8 @@ package org.apache.hadoop.hbase.metrics;
 
 import junit.framework.Assert;
 
-import org.apache.hadoop.hbase.metrics.histogram.ExponentiallyDecayingSample;
+import com.yammer.metrics.stats.ExponentiallyDecayingSample;
-import org.apache.hadoop.hbase.metrics.histogram.Snapshot;
+import com.yammer.metrics.stats.Snapshot;
 import org.apache.hadoop.hbase.SmallTests;
 import org.junit.Test;
 import org.junit.experimental.categories.Category;

hbase-server/src/test/java/org/apache/hadoop/hbase/metrics/TestMetricsHistogram.java

@@ -22,7 +22,7 @@ import java.util.Arrays;
 import java.util.Random;
 
 import org.apache.hadoop.hbase.metrics.histogram.MetricsHistogram;
-import org.apache.hadoop.hbase.metrics.histogram.Snapshot;
+import com.yammer.metrics.stats.Snapshot;
 import org.apache.hadoop.hbase.SmallTests;
 import org.junit.Assert;
 import org.junit.Test;

pom.xml

@@ -658,6 +658,7 @@
     <commons-logging.version>1.1.1</commons-logging.version>
     <commons-math.version>2.1</commons-math.version>
     <commons-configuration.version>1.6</commons-configuration.version>
+    <metrics-core.version>2.1.2</metrics-core.version>
     <guava.version>11.0.2</guava.version>
     <jackson.version>1.8.8</jackson.version>
     <jasper.version>5.5.23</jasper.version>
@@ -743,6 +744,11 @@
       </dependency>
 
       <!-- General dependencies -->
+      <dependency>
+	<groupId>com.yammer.metrics</groupId>
+	<artifactId>metrics-core</artifactId>
+	<version>${metrics-core.version}</version>
+      </dependency>
       <dependency>
         <groupId>com.google.guava</groupId>
         <artifactId>guava</artifactId>