Concurrent LRUCache

最近要为cat增为加一个top key统计,为了避免内存爆掉，希望能实现LRU，但又必须是线程安全的：

 

google的ConcurrentLinkedHashmap源代码解析

google的ConcurrentLinkedHashmap 源代码解析- Ken-专注后端技术

 

http://code.google.com/p/concurrentlinkedhashmap/

 

solr的实现：

package org.apache.solr.common.util;
/**
 * 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.
 */

import org.apache.lucene.util.PriorityQueue;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.LinkedHashMap;
import java.util.Map;
import java.util.TreeSet;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.locks.ReentrantLock;
import java.lang.ref.WeakReference;

/**
 * A LRU cache implementation based upon ConcurrentHashMap and other techniques to reduce
 * contention and synchronization overhead to utilize multiple CPU cores more effectively.
 * 

 * Note that the implementation does not follow a true LRU (least-recently-used) eviction
 * strategy. Instead it strives to remove least recently used items but when the initial
 * cleanup does not remove enough items to reach the 'acceptableWaterMark' limit, it can
 * remove more items forcefully regardless of access order.
 *
 * @version $Id: ConcurrentLRUCache.java 807872 2009-08-26 04:18:22Z hossman $
 * @since solr 1.4
 */
public class ConcurrentLRUCache {
  private static Logger log = LoggerFactory.getLogger(ConcurrentLRUCache.class);

  private final ConcurrentHashMap map;
  private final int upperWaterMark, lowerWaterMark;
  private final ReentrantLock markAndSweepLock = new ReentrantLock(true);
  private boolean isCleaning = false;  // not volatile... piggybacked on other volatile vars
  private final boolean newThreadForCleanup;
  private volatile boolean islive = true;
  private final Stats stats = new Stats();
  private final int acceptableWaterMark;
  private long oldestEntry = 0;  // not volatile, only accessed in the cleaning method
  private final EvictionListener evictionListener;
  private CleanupThread cleanupThread ;

  public ConcurrentLRUCache(int upperWaterMark, final int lowerWaterMark, int acceptableWatermark,
                            int initialSize, boolean runCleanupThread, boolean runNewThreadForCleanup,
                            EvictionListener evictionListener) {
    if (upperWaterMark < 1) throw new IllegalArgumentException("upperWaterMark must be > 0");
    if (lowerWaterMark >= upperWaterMark)
      throw new IllegalArgumentException("lowerWaterMark must be  < upperWaterMark");
    map = new ConcurrentHashMap(initialSize);
    newThreadForCleanup = runNewThreadForCleanup;
    this.upperWaterMark = upperWaterMark;
    this.lowerWaterMark = lowerWaterMark;
    this.acceptableWaterMark = acceptableWatermark;
    this.evictionListener = evictionListener;
    if (runCleanupThread) {
      cleanupThread = new CleanupThread(this);
      cleanupThread.start();
    }
  }

  public ConcurrentLRUCache(int size, int lowerWatermark) {
    this(size, lowerWatermark, (int) Math.floor((lowerWatermark + size) / 2),
            (int) Math.ceil(0.75 * size), false, false, null);
  }

  public void setAlive(boolean live) {
    islive = live;
  }

  public V get(K key) {
    CacheEntry e = map.get(key);
    if (e == null) {
      if (islive) stats.missCounter.incrementAndGet();
      return null;
    }
    if (islive) e.lastAccessed = stats.accessCounter.incrementAndGet();
    return e.value;
  }

  public V remove(K key) {
    CacheEntry cacheEntry = map.remove(key);
    if (cacheEntry != null) {
      stats.size.decrementAndGet();
      return cacheEntry.value;
    }
    return null;
  }

  public Object put(K key, V val) {
    if (val == null) return null;
    CacheEntry e = new CacheEntry(key, val, stats.accessCounter.incrementAndGet());
    CacheEntry oldCacheEntry = map.put(key, e);
    if (oldCacheEntry == null) {
      stats.size.incrementAndGet();
    }
    if (islive) {
      stats.putCounter.incrementAndGet();
    } else {
      stats.nonLivePutCounter.incrementAndGet();
    }

    // Check if we need to clear out old entries from the cache.
    // isCleaning variable is checked instead of markAndSweepLock.isLocked()
    // for performance because every put invokation will check until
    // the size is back to an acceptable level.
    //
    // There is a race between the check and the call to markAndSweep, but
    // it's unimportant because markAndSweep actually aquires the lock or returns if it can't.
    //
    // Thread safety note: isCleaning read is piggybacked (comes after) other volatile reads
    // in this method.
    if (stats.size.get() > upperWaterMark && !isCleaning) {
      if (newThreadForCleanup) {
        new Thread() {
          public void run() {
            markAndSweep();
          }
        }.start();
      } else if (cleanupThread != null){
        cleanupThread.wakeThread();
      } else {
        markAndSweep();
      }
    }
    return oldCacheEntry == null ? null : oldCacheEntry.value;
  }

  /**
   * Removes items from the cache to bring the size down
   * to an acceptable value ('acceptableWaterMark').
   * 

   * It is done in two stages. In the first stage, least recently used items are evicted.
   * If, after the first stage, the cache size is still greater than 'acceptableSize'
   * config parameter, the second stage takes over.
   * 

   * The second stage is more intensive and tries to bring down the cache size
   * to the 'lowerWaterMark' config parameter.
   */
  private void markAndSweep() {
    // if we want to keep at least 1000 entries, then timestamps of
    // current through current-1000 are guaranteed not to be the oldest (but that does
    // not mean there are 1000 entries in that group... it's acutally anywhere between
    // 1 and 1000).
    // Also, if we want to remove 500 entries, then
    // oldestEntry through oldestEntry+500 are guaranteed to be
    // removed (however many there are there).

    if (!markAndSweepLock.tryLock()) return;
    try {
      long oldestEntry = this.oldestEntry;
      isCleaning = true;
      this.oldestEntry = oldestEntry;     // volatile write to make isCleaning visible

      long timeCurrent = stats.accessCounter.get();
      int sz = stats.size.get();

      int numRemoved = 0;
      int numKept = 0;
      long newestEntry = timeCurrent;
      long newNewestEntry = -1;
      long newOldestEntry = Integer.MAX_VALUE;

      int wantToKeep = lowerWaterMark;
      int wantToRemove = sz - lowerWaterMark;

      CacheEntry[] eset = new CacheEntry[sz];
      int eSize = 0;

      // System.out.println("newestEntry="+newestEntry + " oldestEntry="+oldestEntry);
      // System.out.println("items removed:" + numRemoved + " numKept=" + numKept + " esetSz="+ eSize + " sz-numRemoved=" + (sz-numRemoved));

      for (CacheEntry ce : map.values()) {
        // set lastAccessedCopy to avoid more volatile reads
        ce.lastAccessedCopy = ce.lastAccessed;
        long thisEntry = ce.lastAccessedCopy;

        // since the wantToKeep group is likely to be bigger than wantToRemove, check it first
        if (thisEntry > newestEntry - wantToKeep) {
          // this entry is guaranteed not to be in the bottom
          // group, so do nothing.
          numKept++;
          newOldestEntry = Math.min(thisEntry, newOldestEntry);
        } else if (thisEntry < oldestEntry + wantToRemove) { // entry in bottom group?
          // this entry is guaranteed to be in the bottom group
          // so immediately remove it from the map.
          evictEntry(ce.key);
          numRemoved++;
        } else {
          // This entry *could* be in the bottom group.
          // Collect these entries to avoid another full pass... this is wasted
          // effort if enough entries are normally removed in this first pass.
          // An alternate impl could make a full second pass.
          if (eSize < eset.length-1) {
            eset[eSize++] = ce;
            newNewestEntry = Math.max(thisEntry, newNewestEntry);
            newOldestEntry = Math.min(thisEntry, newOldestEntry);
          }
        }
      }

      // System.out.println("items removed:" + numRemoved + " numKept=" + numKept + " esetSz="+ eSize + " sz-numRemoved=" + (sz-numRemoved));
      // TODO: allow this to be customized in the constructor?
      int numPasses=1; // maximum number of linear passes over the data

      // if we didn't remove enough entries, then make more passes
      // over the values we collected, with updated min and max values.
      while (sz - numRemoved > acceptableWaterMark && --numPasses>=0) {

        oldestEntry = newOldestEntry == Integer.MAX_VALUE ? oldestEntry : newOldestEntry;
        newOldestEntry = Integer.MAX_VALUE;
        newestEntry = newNewestEntry;
        newNewestEntry = -1;
        wantToKeep = lowerWaterMark - numKept;
        wantToRemove = sz - lowerWaterMark - numRemoved;

        // iterate backward to make it easy to remove items.
        for (int i=eSize-1; i>=0; i--) {
          CacheEntry ce = eset[i];
          long thisEntry = ce.lastAccessedCopy;

          if (thisEntry > newestEntry - wantToKeep) {
            // this entry is guaranteed not to be in the bottom
            // group, so do nothing but remove it from the eset.
            numKept++;
            // remove the entry by moving the last element to it's position
            eset[i] = eset[eSize-1];
            eSize--;

            newOldestEntry = Math.min(thisEntry, newOldestEntry);
            
          } else if (thisEntry < oldestEntry + wantToRemove) { // entry in bottom group?

            // this entry is guaranteed to be in the bottom group
            // so immediately remove it from the map.
            evictEntry(ce.key);
            numRemoved++;

            // remove the entry by moving the last element to it's position
            eset[i] = eset[eSize-1];
            eSize--;
          } else {
            // This entry *could* be in the bottom group, so keep it in the eset,
            // and update the stats.
            newNewestEntry = Math.max(thisEntry, newNewestEntry);
            newOldestEntry = Math.min(thisEntry, newOldestEntry);
          }
        }
        // System.out.println("items removed:" + numRemoved + " numKept=" + numKept + " esetSz="+ eSize + " sz-numRemoved=" + (sz-numRemoved));
      }



      // if we still didn't remove enough entries, then make another pass while
      // inserting into a priority queue
      if (sz - numRemoved > acceptableWaterMark) {

        oldestEntry = newOldestEntry == Integer.MAX_VALUE ? oldestEntry : newOldestEntry;
        newOldestEntry = Integer.MAX_VALUE;
        newestEntry = newNewestEntry;
        newNewestEntry = -1;
        wantToKeep = lowerWaterMark - numKept;
        wantToRemove = sz - lowerWaterMark - numRemoved;

        PQueue queue = new PQueue(wantToRemove);

        for (int i=eSize-1; i>=0; i--) {
          CacheEntry ce = eset[i];
          long thisEntry = ce.lastAccessedCopy;

          if (thisEntry > newestEntry - wantToKeep) {
            // this entry is guaranteed not to be in the bottom
            // group, so do nothing but remove it from the eset.
            numKept++;
            // removal not necessary on last pass.
            // eset[i] = eset[eSize-1];
            // eSize--;

            newOldestEntry = Math.min(thisEntry, newOldestEntry);
            
          } else if (thisEntry < oldestEntry + wantToRemove) {  // entry in bottom group?
            // this entry is guaranteed to be in the bottom group
            // so immediately remove it.
            evictEntry(ce.key);
            numRemoved++;

            // removal not necessary on last pass.
            // eset[i] = eset[eSize-1];
            // eSize--;
          } else {
            // This entry *could* be in the bottom group.
            // add it to the priority queue

            // everything in the priority queue will be removed, so keep track of
            // the lowest value that ever comes back out of the queue.

            // first reduce the size of the priority queue to account for
            // the number of items we have already removed while executing
            // this loop so far.
            queue.myMaxSize = sz - lowerWaterMark - numRemoved;
            while (queue.size() > queue.myMaxSize && queue.size() > 0) {
              CacheEntry otherEntry = (CacheEntry) queue.pop();
              newOldestEntry = Math.min(otherEntry.lastAccessedCopy, newOldestEntry);
            }
            if (queue.myMaxSize <= 0) break;

            Object o = queue.myInsertWithOverflow(ce);
            if (o != null) {
              newOldestEntry = Math.min(((CacheEntry)o).lastAccessedCopy, newOldestEntry);
            }
          }
        }

        // Now delete everything in the priority queue.
        // avoid using pop() since order doesn't matter anymore
        for (Object o : queue.getValues()) {
          if (o==null) continue;
          CacheEntry ce = (CacheEntry)o;
          evictEntry(ce.key);
          numRemoved++;
        }

        // System.out.println("items removed:" + numRemoved + " numKept=" + numKept + " initialQueueSize="+ wantToRemove + " finalQueueSize=" + queue.size() + " sz-numRemoved=" + (sz-numRemoved));
      }

      oldestEntry = newOldestEntry == Integer.MAX_VALUE ? oldestEntry : newOldestEntry;
      this.oldestEntry = oldestEntry;
    } finally {
      isCleaning = false;  // set before markAndSweep.unlock() for visibility
      markAndSweepLock.unlock();
    }
  }

  private static class PQueue extends PriorityQueue {
    int myMaxSize;
    PQueue(int maxSz) {
      super.initialize(maxSz);
      myMaxSize = maxSz;
    }

    Object[] getValues() { return heap; }

    protected boolean lessThan(Object a, Object b) {
      // reverse the parameter order so that the queue keeps the oldest items
      return ((CacheEntry)b).lastAccessedCopy < ((CacheEntry)a).lastAccessedCopy;
    }

    // necessary because maxSize is private in base class
    public Object myInsertWithOverflow(Object element) {
      if (size() < myMaxSize) {
        put(element);
        return null;
      } else if (size() > 0 && !lessThan(element, heap[1])) {
        Object ret = heap[1];
        heap[1] = element;
        adjustTop();
        return ret;
      } else {
        return element;
      }
    }
  }


  private void evictEntry(K key) {
    CacheEntry o = map.remove(key);
    if (o == null) return;
    stats.size.decrementAndGet();
    stats.evictionCounter++;
    if(evictionListener != null) evictionListener.evictedEntry(o.key,o.value);
  }

  /**
   * Returns 'n' number of oldest accessed entries present in this cache.
   *
   * This uses a TreeSet to collect the 'n' oldest items ordered by ascending last access time
   *  and returns a LinkedHashMap containing 'n' or less than 'n' entries.
   * @param n the number of oldest items needed
   * @return a LinkedHashMap containing 'n' or less than 'n' entries
   */
  public Map getOldestAccessedItems(int n) {
    markAndSweepLock.lock();
    Map result = new LinkedHashMap();
    TreeSet tree = new TreeSet();
    try {
      for (Map.Entry entry : map.entrySet()) {
        CacheEntry ce = entry.getValue();
        ce.lastAccessedCopy = ce.lastAccessed;
        if (tree.size() < n) {
          tree.add(ce);
        } else {
          if (ce.lastAccessedCopy < tree.first().lastAccessedCopy) {
            tree.remove(tree.first());
            tree.add(ce);
          }
        }
      }
    } finally {
      markAndSweepLock.unlock();
    }
    for (CacheEntry e : tree) {
      result.put(e.key, e.value);
    }
    return result;
  }

  public Map getLatestAccessedItems(int n) {
    // we need to grab the lock since we are changing lastAccessedCopy
    markAndSweepLock.lock();
    Map result = new LinkedHashMap();
    TreeSet tree = new TreeSet();
    try {
      for (Map.Entry entry : map.entrySet()) {
        CacheEntry ce = entry.getValue();
        ce.lastAccessedCopy = ce.lastAccessed;
        if (tree.size() < n) {
          tree.add(ce);
        } else {
          if (ce.lastAccessedCopy > tree.last().lastAccessedCopy) {
            tree.remove(tree.last());
            tree.add(ce);
          }
        }
      }
    } finally {
      markAndSweepLock.unlock();
    }
    for (CacheEntry e : tree) {
      result.put(e.key, e.value);
    }
    return result;
  }

  public int size() {
    return stats.size.get();
  }

  public void clear() {
    map.clear();
  }

  public Map getMap() {
    return map;
  }

  private static class CacheEntry implements Comparable {
    K key;
    V value;
    volatile long lastAccessed = 0;
    long lastAccessedCopy = 0;


    public CacheEntry(K key, V value, long lastAccessed) {
      this.key = key;
      this.value = value;
      this.lastAccessed = lastAccessed;
    }

    public void setLastAccessed(long lastAccessed) {
      this.lastAccessed = lastAccessed;
    }

    public int compareTo(CacheEntry that) {
      if (this.lastAccessedCopy == that.lastAccessedCopy) return 0;
      return this.lastAccessedCopy < that.lastAccessedCopy ? 1 : -1;
    }

    public int hashCode() {
      return value.hashCode();
    }

    public boolean equals(Object obj) {
      return value.equals(obj);
    }

    public String toString() {
      return "key: " + key + " value: " + value + " lastAccessed:" + lastAccessed;
    }
  }

 private boolean isDestroyed =  false;
  public void destroy() {
    try {
      if(cleanupThread != null){
        cleanupThread.stopThread();
      }
    } finally {
      isDestroyed = true;
    }
  }

  public Stats getStats() {
    return stats;
  }


  public static class Stats {
    private final AtomicLong accessCounter = new AtomicLong(0),
            putCounter = new AtomicLong(0),
            nonLivePutCounter = new AtomicLong(0),
            missCounter = new AtomicLong();
    private final AtomicInteger size = new AtomicInteger();
    private long evictionCounter = 0;

    public long getCumulativeLookups() {
      return (accessCounter.get() - putCounter.get() - nonLivePutCounter.get()) + missCounter.get();
    }

    public long getCumulativeHits() {
      return accessCounter.get() - putCounter.get() - nonLivePutCounter.get();
    }

    public long getCumulativePuts() {
      return putCounter.get();
    }

    public long getCumulativeEvictions() {
      return evictionCounter;
    }

    public int getCurrentSize() {
      return size.get();
    }

    public long getCumulativeNonLivePuts() {
      return nonLivePutCounter.get();
    }

    public long getCumulativeMisses() {
      return missCounter.get();
    }
  }

  public static interface EvictionListener{
    public void evictedEntry(K key, V value);
  }

  private static class CleanupThread extends Thread {
    private WeakReference cache;

    private boolean stop = false;

    public CleanupThread(ConcurrentLRUCache c) {
      cache = new WeakReference(c);
    }

    public void run() {
      while (true) {
        synchronized (this) {
          if (stop) break;
          try {
            this.wait();
          } catch (InterruptedException e) {}
        }
        if (stop) break;
        ConcurrentLRUCache c = cache.get();
        if(c == null) break;
        c.markAndSweep();
      }
    }

    void wakeThread() {
      synchronized(this){
        this.notify();
      }
    }

    void stopThread() {
      synchronized(this){
        stop=true;
        this.notify();
      }
    }
  }

  protected void finalize() throws Throwable {
    try {
      if(!isDestroyed){
        log.error("ConcurrentLRUCache was not destroyed prior to finalize(), indicates a bug -- POSSIBLE RESOURCE LEAK!!!");
        destroy();
      }
    } finally {
      super.finalize();
    }
  }
}