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package org.mapdb;
/*
* 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 java.util.Arrays;
import java.util.Collections;
import java.util.Iterator;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.locks.ReentrantLock;
/**
* 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.
*
* MapDB note: reworked to implement LongMap. Original comes from:
* https://svn.apache.org/repos/asf/lucene/dev/trunk/solr/core/src/java/org/apache/solr/util/LongConcurrentLRUMap.java
*
*/
public class LongConcurrentLRUMap extends LongMap {
protected final LongConcurrentHashMap> map;
protected final int upperWaterMark, lowerWaterMark;
protected final ReentrantLock markAndSweepLock = new ReentrantLock(true);
protected boolean isCleaning = false; // not volatile... piggybacked on other volatile vars
protected final int acceptableWaterMark;
protected long oldestEntry = 0; // not volatile, only accessed in the cleaning method
protected final AtomicLong accessCounter = new AtomicLong(0),
putCounter = new AtomicLong(0),
missCounter = new AtomicLong(),
evictionCounter = new AtomicLong();
protected final AtomicInteger size = new AtomicInteger();
public LongConcurrentLRUMap(int upperWaterMark, final int lowerWaterMark, int acceptableWatermark,
int initialSize) {
if (upperWaterMark < 1) throw new IllegalArgumentException("upperWaterMark must be > 0");
if (lowerWaterMark >= upperWaterMark)
throw new IllegalArgumentException("lowerWaterMark must be < upperWaterMark");
map = new LongConcurrentHashMap>(initialSize);
this.upperWaterMark = upperWaterMark;
this.lowerWaterMark = lowerWaterMark;
this.acceptableWaterMark = acceptableWatermark;
}
public LongConcurrentLRUMap(int size, int lowerWatermark) {
this(size, lowerWatermark, (int) Math.floor((lowerWatermark + size) / 2),
(int) Math.ceil(0.75 * size));
}
public V get(long key) {
CacheEntry e = map.get(key);
if (e == null) {
missCounter.incrementAndGet();
return null;
}
e.lastAccessed = accessCounter.incrementAndGet();
return e.value;
}
@Override
public boolean isEmpty() {
return map.isEmpty();
}
public V remove(long key) {
CacheEntry cacheEntry = map.remove(key);
if (cacheEntry != null) {
size.decrementAndGet();
return cacheEntry.value;
}
return null;
}
public V put(long key, V val) {
if (val == null) return null;
CacheEntry e = new CacheEntry(key, val, accessCounter.incrementAndGet());
CacheEntry oldCacheEntry = map.put(key, e);
int currentSize;
if (oldCacheEntry == null) {
currentSize = size.incrementAndGet();
} else {
currentSize = size.get();
}
putCounter.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 (currentSize > upperWaterMark && !isCleaning) {
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 = accessCounter.get();
int sz = size.get();
int numRemoved = 0;
int numKept = 0;
long newestEntry = timeCurrent;
long newNewestEntry = -1;
long newOldestEntry = Long.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 (Iterator> iter = map.valuesIterator(); iter.hasNext();) {
CacheEntry ce = iter.next();
// 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));
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 == Long.MAX_VALUE ? oldestEntry : newOldestEntry;
newOldestEntry = Long.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 == Long.MAX_VALUE ? oldestEntry : newOldestEntry;
newOldestEntry = Long.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 = 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 (CacheEntry ce : queue.getValues()) {
if (ce==null) continue;
evictEntry(ce.key);
numRemoved++;
}
// System.out.println("items removed:" + numRemoved + " numKept=" + numKept + " initialQueueSize="+ wantToRemove + " finalQueueSize=" + queue.size() + " sz-numRemoved=" + (sz-numRemoved));
}
oldestEntry = newOldestEntry == Long.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;
final Object[] heap;
PQueue(int maxSz) {
super(maxSz);
heap = getHeapArray();
myMaxSize = maxSz;
}
Iterable> getValues() {
return (Iterable) Collections.unmodifiableCollection(Arrays.asList(heap));
}
@Override
protected boolean lessThan(CacheEntry a, CacheEntry b) {
// reverse the parameter order so that the queue keeps the oldest items
return b.lastAccessedCopy < a.lastAccessedCopy;
}
// necessary because maxSize is private in base class
public CacheEntry myInsertWithOverflow(CacheEntry element) {
if (size() < myMaxSize) {
add(element);
return null;
} else if (size() > 0 && !lessThan(element, (CacheEntry) heap[1])) {
CacheEntry ret = (CacheEntry) heap[1];
heap[1] = element;
updateTop();
return ret;
} else {
return element;
}
}
}
/** A PriorityQueue maintains a partial ordering of its elements such that the
* least element can always be found in constant time. Put()'s and pop()'s
* require log(size) time.
*
* NOTE: This class will pre-allocate a full array of
* length maxSize+1 if instantiated via the
* {@link #PriorityQueue(int,boolean)} constructor with
* prepopulate set to true.
*
* @lucene.internal
*/
private static abstract class PriorityQueue {
private int size;
private final int maxSize;
private final T[] heap;
public PriorityQueue(int maxSize) {
this(maxSize, true);
}
public PriorityQueue(int maxSize, boolean prepopulate) {
size = 0;
int heapSize;
if (0 == maxSize)
// We allocate 1 extra to avoid if statement in top()
heapSize = 2;
else {
if (maxSize == Integer.MAX_VALUE) {
// Don't wrap heapSize to -1, in this case, which
// causes a confusing NegativeArraySizeException.
// Note that very likely this will simply then hit
// an OOME, but at least that's more indicative to
// caller that this values is too big. We don't +1
// in this case, but it's very unlikely in practice
// one will actually insert this many objects into
// the PQ:
heapSize = Integer.MAX_VALUE;
} else {
// NOTE: we add +1 because all access to heap is
// 1-based not 0-based. heap[0] is unused.
heapSize = maxSize + 1;
}
}
heap = (T[]) new Object[heapSize]; // T is unbounded type, so this unchecked cast works always
this.maxSize = maxSize;
if (prepopulate) {
// If sentinel objects are supported, populate the queue with them
T sentinel = getSentinelObject();
if (sentinel != null) {
heap[1] = sentinel;
for (int i = 2; i < heap.length; i++) {
heap[i] = getSentinelObject();
}
size = maxSize;
}
}
}
/** Determines the ordering of objects in this priority queue. Subclasses
* must define this one method.
* @return true iff parameter a is less than parameter b.
*/
protected abstract boolean lessThan(T a, T b);
/**
* This method can be overridden by extending classes to return a sentinel
* object which will be used by the {@link PriorityQueue#PriorityQueue(int,boolean)}
* constructor to fill the queue, so that the code which uses that queue can always
* assume it's full and only change the top without attempting to insert any new
* object.
*
* Those sentinel values should always compare worse than any non-sentinel
* value (i.e., {@link #lessThan} should always favor the
* non-sentinel values).
*
* By default, this method returns false, which means the queue will not be
* filled with sentinel values. Otherwise, the value returned will be used to
* pre-populate the queue. Adds sentinel values to the queue.
*
* If this method is extended to return a non-null value, then the following
* usage pattern is recommended:
*
*
* // extends getSentinelObject() to return a non-null value.
* PriorityQueue<MyObject> pq = new MyQueue<MyObject>(numHits);
* // save the 'top' element, which is guaranteed to not be null.
* MyObject pqTop = pq.top();
* <...>
* // now in order to add a new element, which is 'better' than top (after
* // you've verified it is better), it is as simple as:
* pqTop.change().
* pqTop = pq.updateTop();
*
*
* NOTE: if this method returns a non-null value, it will be called by
* the {@link PriorityQueue#PriorityQueue(int,boolean)} constructor
* {@link #size()} times, relying on a new object to be returned and will not
* check if it's null again. Therefore you should ensure any call to this
* method creates a new instance and behaves consistently, e.g., it cannot
* return null if it previously returned non-null.
*
* @return the sentinel object to use to pre-populate the queue, or null if
* sentinel objects are not supported.
*/
protected T getSentinelObject() {
return null;
}
/**
* Adds an Object to a PriorityQueue in log(size) time. If one tries to add
* more objects than maxSize from initialize an
* {@link ArrayIndexOutOfBoundsException} is thrown.
*
* @return the new 'top' element in the queue.
*/
public final T add(T element) {
size++;
heap[size] = element;
upHeap();
return heap[1];
}
/**
* Adds an Object to a PriorityQueue in log(size) time.
* It returns the object (if any) that was
* dropped off the heap because it was full. This can be
* the given parameter (in case it is smaller than the
* full heap's minimum, and couldn't be added), or another
* object that was previously the smallest value in the
* heap and now has been replaced by a larger one, or null
* if the queue wasn't yet full with maxSize elements.
*/
public T insertWithOverflow(T element) {
if (size < maxSize) {
add(element);
return null;
} else if (size > 0 && !lessThan(element, heap[1])) {
T ret = heap[1];
heap[1] = element;
updateTop();
return ret;
} else {
return element;
}
}
/** Returns the least element of the PriorityQueue in constant time. */
public final T top() {
// We don't need to check size here: if maxSize is 0,
// then heap is length 2 array with both entries null.
// If size is 0 then heap[1] is already null.
return heap[1];
}
/** Removes and returns the least element of the PriorityQueue in log(size)
time. */
public final T pop() {
if (size > 0) {
T result = heap[1]; // save first value
heap[1] = heap[size]; // move last to first
heap[size] = null; // permit GC of objects
size--;
downHeap(); // adjust heap
return result;
} else
return null;
}
/**
* Should be called when the Object at top changes values. Still log(n) worst
* case, but it's at least twice as fast to
*
*
* pq.top().change();
* pq.updateTop();
*
*
* instead of
*
*
* o = pq.pop();
* o.change();
* pq.push(o);
*
*
* @return the new 'top' element.
*/
public final T updateTop() {
downHeap();
return heap[1];
}
/** Returns the number of elements currently stored in the PriorityQueue. */
public final int size() {
return size;
}
/** Removes all entries from the PriorityQueue. */
public final void clear() {
for (int i = 0; i <= size; i++) {
heap[i] = null;
}
size = 0;
}
private final void upHeap() {
int i = size;
T node = heap[i]; // save bottom node
int j = i >>> 1;
while (j > 0 && lessThan(node, heap[j])) {
heap[i] = heap[j]; // shift parents down
i = j;
j = j >>> 1;
}
heap[i] = node; // install saved node
}
private final void downHeap() {
int i = 1;
T node = heap[i]; // save top node
int j = i << 1; // find smaller child
int k = j + 1;
if (k <= size && lessThan(heap[k], heap[j])) {
j = k;
}
while (j <= size && lessThan(heap[j], node)) {
heap[i] = heap[j]; // shift up child
i = j;
j = i << 1;
k = j + 1;
if (k <= size && lessThan(heap[k], heap[j])) {
j = k;
}
}
heap[i] = node; // install saved node
}
/** This method returns the internal heap array as Object[].
* @lucene.internal
*/
protected final Object[] getHeapArray() {
return heap;
}
}
private void evictEntry(long key) {
CacheEntry o = map.remove(key);
if (o == null) return;
size.decrementAndGet();
evictionCounter.incrementAndGet();
evictedEntry(o.key,o.value);
}
public int size() {
return size.get();
}
@Override
public Iterator valuesIterator() {
final Iterator> iter = map.valuesIterator();
return new Iterator(){
@Override
public boolean hasNext() {
return iter.hasNext();
}
@Override
public V next() {
return iter.next().value;
}
@Override
public void remove() {
iter.remove(); //TODO is exposing remove ok? any impact on cache?
}
};
}
@Override
public LongMapIterator longMapIterator() {
final LongMapIterator> iter = map.longMapIterator();
return new LongMapIterator() {
@Override
public boolean moveToNext() {
return iter.moveToNext();
}
@Override
public long key() {
return iter.key();
}
@Override
public V value() {
return iter.value().value;
}
@Override
public void remove() {
iter.remove(); //TODO is exposing remove ok? any impact on cache?
}
};
}
public void clear() {
map.clear();
}
public LongMap> getMap() {
return map;
}
private static final class CacheEntry implements Comparable> {
final long key;
final V value;
volatile long lastAccessed = 0;
long lastAccessedCopy = 0;
public CacheEntry(long key, V value, long lastAccessed) {
this.key = key;
this.value = value;
this.lastAccessed = lastAccessed;
}
@Override
public int compareTo(CacheEntry that) {
if (this.lastAccessedCopy == that.lastAccessedCopy) return 0;
return this.lastAccessedCopy < that.lastAccessedCopy ? 1 : -1;
}
@Override
public int hashCode() {
return value.hashCode();
}
@Override
public boolean equals(Object obj) {
return value.equals(obj);
}
@Override
public String toString() {
return "key: " + key + " value: " + value + " lastAccessed:" + lastAccessed;
}
}
/** override this method to get notified about evicted entries*/
protected void evictedEntry(long key, V value){
}
}