org.apache.solr.util.ConcurrentLRUCache Maven / Gradle / Ivy
Show all versions of solr-core Show documentation
/*
* 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.solr.util;
import org.apache.lucene.util.Accountable;
import org.apache.lucene.util.PriorityQueue;
import org.apache.lucene.util.RamUsageEstimator;
import org.apache.solr.common.util.Cache;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.apache.solr.common.util.TimeSource;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.TreeSet;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.TimeUnit;
//import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.atomic.LongAdder;
import java.util.concurrent.locks.ReentrantLock;
import java.lang.invoke.MethodHandles;
import java.lang.ref.WeakReference;
import java.util.function.Function;
import static org.apache.lucene.util.RamUsageEstimator.HASHTABLE_RAM_BYTES_PER_ENTRY;
import static org.apache.lucene.util.RamUsageEstimator.QUERY_DEFAULT_RAM_BYTES_USED;
/**
* 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.
*
*
* @since solr 1.4
*/
public class ConcurrentLRUCache implements Cache, Accountable {
private static final Logger log = LoggerFactory.getLogger(MethodHandles.lookup().lookupClass());
private static final long BASE_RAM_BYTES_USED =
RamUsageEstimator.shallowSizeOfInstance(ConcurrentLRUCache.class) +
new Stats().ramBytesUsed() +
RamUsageEstimator.primitiveSizes.get(long.class) +
RamUsageEstimator.shallowSizeOfInstance(ConcurrentHashMap.class);
private final ConcurrentHashMap> map;
private int upperWaterMark, lowerWaterMark;
private final ReentrantLock markAndSweepLock = new ReentrantLock(true);
private boolean isCleaning = false; // not volatile... piggybacked on other volatile vars
private boolean newThreadForCleanup;
private volatile boolean islive = true;
private final Stats stats = new Stats();
private int acceptableWaterMark;
private long oldestEntry = 0; // not volatile, only accessed in the cleaning method
private final TimeSource timeSource = TimeSource.NANO_TIME;
private final AtomicLong oldestEntryNs = new AtomicLong(0);
private long maxIdleTimeNs;
private final EvictionListener evictionListener;
private CleanupThread cleanupThread;
private boolean runCleanupThread;
private long ramLowerWatermark, ramUpperWatermark;
private final LongAdder ramBytes = new LongAdder();
public ConcurrentLRUCache(long ramLowerWatermark, long ramUpperWatermark,
boolean runCleanupThread, EvictionListener evictionListener) {
this(ramLowerWatermark, ramUpperWatermark, runCleanupThread, evictionListener, -1);
}
public ConcurrentLRUCache(long ramLowerWatermark, long ramUpperWatermark,
boolean runCleanupThread, EvictionListener evictionListener,
int maxIdleTimeSec) {
this.ramLowerWatermark = ramLowerWatermark;
this.ramUpperWatermark = ramUpperWatermark;
this.evictionListener = evictionListener;
this.map = new ConcurrentHashMap<>();
this.newThreadForCleanup = false;
this.acceptableWaterMark = -1;
this.lowerWaterMark = Integer.MIN_VALUE;
this.upperWaterMark = Integer.MAX_VALUE;
setMaxIdleTime(maxIdleTimeSec);
setRunCleanupThread(runCleanupThread);
}
public ConcurrentLRUCache(int upperWaterMark, final int lowerWaterMark, int acceptableWatermark,
int initialSize, boolean runCleanupThread, boolean runNewThreadForCleanup,
EvictionListener evictionListener) {
this(upperWaterMark, lowerWaterMark, acceptableWatermark, initialSize, runCleanupThread,
runNewThreadForCleanup, evictionListener, -1);
}
public ConcurrentLRUCache(int upperWaterMark, final int lowerWaterMark, int acceptableWatermark,
int initialSize, boolean runCleanupThread, boolean runNewThreadForCleanup,
EvictionListener evictionListener, int maxIdleTimeSec) {
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;
this.ramLowerWatermark = Long.MIN_VALUE;
this.ramUpperWatermark = Long.MAX_VALUE;
setMaxIdleTime(maxIdleTimeSec);
setRunCleanupThread(runCleanupThread);
}
public ConcurrentLRUCache(int size, int lowerWatermark) {
this(size, lowerWatermark, (int) Math.floor((lowerWatermark + size) / 2),
(int) Math.ceil(0.75 * size), false, false, null, -1);
}
public void setAlive(boolean live) {
islive = live;
}
public void setUpperWaterMark(int upperWaterMark) {
if (upperWaterMark < 1) throw new IllegalArgumentException("upperWaterMark must be >= 1");
this.upperWaterMark = upperWaterMark;
}
public void setLowerWaterMark(int lowerWaterMark) {
this.lowerWaterMark = lowerWaterMark;
}
public void setAcceptableWaterMark(int acceptableWaterMark) {
this.acceptableWaterMark = acceptableWaterMark;
}
public void setRamUpperWatermark(long ramUpperWatermark) {
if (ramUpperWatermark < 1) {
throw new IllegalArgumentException("ramUpperWaterMark must be >= 1");
}
this.ramUpperWatermark = ramUpperWatermark;
}
public void setRamLowerWatermark(long ramLowerWatermark) {
if (ramLowerWatermark < 0) {
throw new IllegalArgumentException("ramLowerWaterMark must be >= 0");
}
this.ramLowerWatermark = ramLowerWatermark;
}
public void setMaxIdleTime(int maxIdleTime) {
long oldMaxIdleTimeNs = maxIdleTimeNs;
maxIdleTimeNs = maxIdleTime > 0 ? TimeUnit.NANOSECONDS.convert(maxIdleTime, TimeUnit.SECONDS) : Long.MAX_VALUE;
if (cleanupThread != null && maxIdleTimeNs < oldMaxIdleTimeNs) {
cleanupThread.wakeThread();
}
}
public synchronized void setRunCleanupThread(boolean runCleanupThread) {
this.runCleanupThread = runCleanupThread;
if (this.runCleanupThread) {
if (cleanupThread == null) {
cleanupThread = new CleanupThread(this);
cleanupThread.start();
}
} else {
if (cleanupThread != null) {
cleanupThread.stopThread();
cleanupThread = null;
}
}
}
@Override
public V get(K key) {
CacheEntry e = map.get(key);
if (e == null) {
if (islive) stats.missCounter.increment();
return null;
}
if (islive) e.lastAccessed = stats.accessCounter.incrementAndGet();
return e.value;
}
@Override
public V remove(K key) {
CacheEntry cacheEntry = map.remove(key);
if (cacheEntry != null) {
stats.size.decrement();
ramBytes.add(-cacheEntry.ramBytesUsed() - HASHTABLE_RAM_BYTES_PER_ENTRY);
return cacheEntry.value;
}
return null;
}
@Override
public V computeIfAbsent(K key, Function mappingFunction) {
// prescreen access first
V val = get(key);
if (val != null) {
return val;
}
AtomicBoolean newEntry = new AtomicBoolean();
CacheEntry entry = map.computeIfAbsent(key, k -> {
V value = mappingFunction.apply(key);
// preserve the semantics of computeIfAbsent
if (value == null) {
return null;
}
CacheEntry e = new CacheEntry<>(key, value, timeSource.getEpochTimeNs(), stats.accessCounter.incrementAndGet());
oldestEntryNs.updateAndGet(x -> x > e.createTime || x == 0 ? e.createTime : x);
stats.size.increment();
ramBytes.add(e.ramBytesUsed() + HASHTABLE_RAM_BYTES_PER_ENTRY); // added key + value + entry
if (islive) {
stats.putCounter.increment();
} else {
stats.nonLivePutCounter.increment();
}
newEntry.set(true);
return e;
});
if (newEntry.get()) {
maybeMarkAndSweep();
} else {
if (islive && entry != null) {
entry.lastAccessed = stats.accessCounter.incrementAndGet();
}
}
return entry != null ? entry.value : null;
}
@Override
public V put(K key, V val) {
if (val == null) return null;
CacheEntry e = new CacheEntry<>(key, val, timeSource.getEpochTimeNs(), stats.accessCounter.incrementAndGet());
return putCacheEntry(e);
}
/**
* Visible for testing to create synthetic cache entries.
* @lucene.internal
*/
public V putCacheEntry(CacheEntry e) {
// initialize oldestEntryNs
oldestEntryNs.updateAndGet(x -> x > e.createTime || x == 0 ? e.createTime : x);
CacheEntry oldCacheEntry = map.put(e.key, e);
if (oldCacheEntry == null) {
stats.size.increment();
ramBytes.add(e.ramBytesUsed() + HASHTABLE_RAM_BYTES_PER_ENTRY); // added key + value + entry
} else {
ramBytes.add(-oldCacheEntry.ramBytesUsed());
ramBytes.add(e.ramBytesUsed());
}
if (islive) {
stats.putCounter.increment();
} else {
stats.nonLivePutCounter.increment();
}
maybeMarkAndSweep();
return oldCacheEntry == null ? null : oldCacheEntry.value;
}
private void maybeMarkAndSweep() {
// 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 invocation 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 acquires the lock or returns if it can't.
//
// Thread safety note: isCleaning read is piggybacked (comes after) other volatile reads
// in this method.
long idleCutoff = timeSource.getEpochTimeNs() - maxIdleTimeNs;
int currentSize = stats.size.intValue();
if ((currentSize > upperWaterMark || ramBytes.sum() > ramUpperWatermark || oldestEntryNs.get() < idleCutoff) && !isCleaning) {
if (newThreadForCleanup) {
new Thread(this::markAndSweep).start();
} else if (cleanupThread != null){
cleanupThread.wakeThread();
} else {
markAndSweep();
}
}
}
/**
* Removes items from the cache to bring the size down
* to an acceptable value.
* Visible for unit testing.
* @lucene.internal
*/
public 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 actually 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 {
if (maxIdleTimeNs != Long.MAX_VALUE) {
long idleCutoff = timeSource.getEpochTimeNs() - maxIdleTimeNs;
if (oldestEntryNs.get() < idleCutoff) {
markAndSweepByIdleTime();
}
}
if (upperWaterMark < size()) {
markAndSweepByCacheSize();
} else if (ramUpperWatermark < ramBytesUsed()) {
markAndSweepByRamSize();
} else if (upperWaterMark == Integer.MAX_VALUE && ramUpperWatermark == Long.MAX_VALUE) {
// should never happen
throw new AssertionError("ConcurrentLRUCache initialized with neither size limits nor ram limits");
}
} finally {
isCleaning = false; // set before markAndSweep.unlock() for visibility
markAndSweepLock.unlock();
}
}
/*
Must be called after acquiring markAndSweepLock
*/
private void markAndSweepByIdleTime() {
assert markAndSweepLock.isHeldByCurrentThread() : "markAndSweepLock held by another thread";
Iterator>> iterator = map.entrySet().iterator();
long idleCutoff = timeSource.getEpochTimeNs() - maxIdleTimeNs;
long currentOldestEntry = Long.MAX_VALUE;
while (iterator.hasNext()) {
Map.Entry> entry = iterator.next();
if (entry.getValue().createTime < idleCutoff) {
iterator.remove();
stats.evictionIdleCounter.increment();
postRemoveEntry(entry.getValue());
} else {
if (entry.getValue().createTime < currentOldestEntry) {
currentOldestEntry = entry.getValue().createTime;
}
}
}
if (currentOldestEntry != Long.MAX_VALUE) {
oldestEntryNs.set(currentOldestEntry);
}
}
/*
Must be called after acquiring markAndSweepLock
*/
private void markAndSweepByRamSize() {
assert markAndSweepLock.isHeldByCurrentThread() : "markAndSweepLock held by another thread";
List> entriesInAccessOrder = new ArrayList<>(map.size());
map.forEach((o, kvCacheEntry) -> {
kvCacheEntry.lastAccessedCopy = kvCacheEntry.lastAccessed; // important because we want to avoid volatile read during comparisons
entriesInAccessOrder.add(kvCacheEntry);
});
Collections.sort(entriesInAccessOrder); // newer access is smaller, older access is bigger
// iterate in oldest to newest order
for (int i = entriesInAccessOrder.size() - 1; i >= 0; i--) {
CacheEntry kvCacheEntry = entriesInAccessOrder.get(i);
evictEntry(kvCacheEntry.key);
if (ramBytes.sum() <= ramLowerWatermark) {
break; // we are done!
}
}
}
/*
* 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.
* Must be called after acquiring markAndSweepLock
*/
private void markAndSweepByCacheSize() {
assert markAndSweepLock.isHeldByCurrentThread() : "markAndSweepLock held by another thread";
long oldestEntry = this.oldestEntry;
isCleaning = true;
this.oldestEntry = oldestEntry; // volatile write to make isCleaning visible
long timeCurrent = stats.accessCounter.longValue();
int sz = stats.size.intValue();
int numRemoved = 0;
int numKept = 0;
long newestEntry = timeCurrent;
long newNewestEntry = -1;
long newOldestEntry = Long.MAX_VALUE;
int wantToKeep = lowerWaterMark;
int wantToRemove = sz - lowerWaterMark;
@SuppressWarnings({"unchecked", "rawtypes"})
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 == 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 its 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 its 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) {
@SuppressWarnings({"rawtypes"})
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;
}
private static class PQueue extends PriorityQueue> {
int myMaxSize;
final Object[] heap;
PQueue(int maxSz) {
super(maxSz);
heap = getHeapArray();
myMaxSize = maxSz;
}
@SuppressWarnings("unchecked")
Iterable> getValues() {
return (Iterable) Collections.unmodifiableCollection(Arrays.asList(heap));
}
@Override
protected boolean lessThan(@SuppressWarnings({"rawtypes"})CacheEntry a,
@SuppressWarnings({"rawtypes"})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
@SuppressWarnings("unchecked")
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;
}
}
}
private void evictEntry(K key) {
CacheEntry o = map.remove(key);
postRemoveEntry(o);
}
private void postRemoveEntry(CacheEntry o) {
if (o == null) return;
ramBytes.add(-(o.ramBytesUsed() + HASHTABLE_RAM_BYTES_PER_ENTRY));
stats.size.decrement();
stats.evictionCounter.increment();
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) {
Map result = new LinkedHashMap<>();
if (n <= 0)
return result;
TreeSet> tree = new TreeSet<>();
markAndSweepLock.lock();
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) {
Map result = new LinkedHashMap<>();
if (n <= 0)
return result;
TreeSet> tree = new TreeSet<>();
// we need to grab the lock since we are changing lastAccessedCopy
markAndSweepLock.lock();
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.intValue();
}
@Override
public void clear() {
map.clear();
ramBytes.reset();
}
public Map> getMap() {
return map;
}
public static class CacheEntry implements Comparable>, Accountable {
public static long BASE_RAM_BYTES_USED = RamUsageEstimator.shallowSizeOf(CacheEntry.class);
final K key;
final V value;
final long createTime;
final long ramBytesUsed; // cache
volatile long lastAccessed = 0;
long lastAccessedCopy = 0;
public CacheEntry(K key, V value, long createTime, long lastAccessed) {
this.key = key;
this.value = value;
this.createTime = createTime;
this.lastAccessed = lastAccessed;
this.ramBytesUsed =
BASE_RAM_BYTES_USED +
RamUsageEstimator.sizeOfObject(key, QUERY_DEFAULT_RAM_BYTES_USED) +
RamUsageEstimator.sizeOfObject(value, QUERY_DEFAULT_RAM_BYTES_USED);
}
public void setLastAccessed(long lastAccessed) {
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
public long ramBytesUsed() {
return ramBytesUsed;
}
@Override
public Collection getChildResources() {
return Collections.emptyList();
}
}
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 implements Accountable {
private static final long RAM_BYTES_USED =
// accounts for field refs
RamUsageEstimator.shallowSizeOfInstance(Stats.class) +
// LongAdder
6 * (
RamUsageEstimator.NUM_BYTES_ARRAY_HEADER +
RamUsageEstimator.primitiveSizes.get(long.class) +
2 * (RamUsageEstimator.NUM_BYTES_OBJECT_REF + RamUsageEstimator.primitiveSizes.get(long.class))
) +
// AtomicLong
RamUsageEstimator.primitiveSizes.get(long.class);
private final AtomicLong accessCounter = new AtomicLong(0);
private final LongAdder putCounter = new LongAdder();
private final LongAdder nonLivePutCounter = new LongAdder();
private final LongAdder missCounter = new LongAdder();
private final LongAdder size = new LongAdder();
private LongAdder evictionCounter = new LongAdder();
private LongAdder evictionIdleCounter = new LongAdder();
public long getCumulativeLookups() {
return (accessCounter.longValue() - putCounter.longValue() - nonLivePutCounter.longValue()) + missCounter.longValue();
}
public long getCumulativeHits() {
return accessCounter.longValue() - putCounter.longValue() - nonLivePutCounter.longValue();
}
public long getCumulativePuts() {
return putCounter.longValue();
}
public long getCumulativeEvictions() {
return evictionCounter.longValue();
}
public long getCumulativeIdleEvictions() {
return evictionIdleCounter.longValue();
}
public int getCurrentSize() {
return size.intValue();
}
public long getCumulativeNonLivePuts() {
return nonLivePutCounter.longValue();
}
public long getCumulativeMisses() {
return missCounter.longValue();
}
public void add(Stats other) {
accessCounter.addAndGet(other.accessCounter.get());
putCounter.add(other.putCounter.longValue());
nonLivePutCounter.add(other.nonLivePutCounter.longValue());
missCounter.add(other.missCounter.longValue());
evictionCounter.add(other.evictionCounter.longValue());
long maxSize = Math.max(size.longValue(), other.size.longValue());
size.reset();
size.add(maxSize);
}
@Override
public long ramBytesUsed() {
return RAM_BYTES_USED;
}
}
public static interface EvictionListener{
public void evictedEntry(K key, V value);
}
private static class CleanupThread extends Thread {
@SuppressWarnings({"rawtypes"})
private WeakReference cache;
private boolean stop = false;
public CleanupThread(@SuppressWarnings({"rawtypes"})ConcurrentLRUCache c) {
cache = new WeakReference<>(c);
}
@Override
public void run() {
while (true) {
@SuppressWarnings({"rawtypes"})
ConcurrentLRUCache c = cache.get();
if(c == null) break;
synchronized (this) {
if (stop) break;
long waitTimeMs = c.maxIdleTimeNs != Long.MAX_VALUE ? TimeUnit.MILLISECONDS.convert(c.maxIdleTimeNs, TimeUnit.NANOSECONDS) : 0L;
try {
this.wait(waitTimeMs);
} catch (InterruptedException e) {}
}
if (stop) break;
c = cache.get();
if (c == null) break;
c.markAndSweep();
}
}
void wakeThread() {
synchronized(this){
this.notify();
}
}
void stopThread() {
synchronized(this){
stop=true;
this.notify();
}
}
}
@Override
protected void finalize() throws Throwable {
try {
if(!isDestroyed && (cleanupThread != null)){
log.error("ConcurrentLRUCache created with a thread and was not destroyed prior to finalize(), indicates a bug -- POSSIBLE RESOURCE LEAK!!!");
destroy();
}
} finally {
super.finalize();
}
}
@Override
public long ramBytesUsed() {
return BASE_RAM_BYTES_USED + ramBytes.sum();
}
@Override
public Collection getChildResources() {
return Collections.emptyList();
}
}