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* 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.lucene.search;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.ConcurrentModificationException;
import java.util.IdentityHashMap;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.atomic.AtomicBoolean;
import org.apache.lucene.index.LeafReader.CoreClosedListener;
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.index.ReaderUtil;
import org.apache.lucene.index.Term;
import org.apache.lucene.util.Accountable;
import org.apache.lucene.util.Accountables;
import org.apache.lucene.util.RamUsageEstimator;
import org.apache.lucene.util.RoaringDocIdSet;
/**
* A {@link QueryCache} that evicts queries using a LRU (least-recently-used)
* eviction policy in order to remain under a given maximum size and number of
* bytes used.
*
* This class is thread-safe.
*
* Note that query eviction runs in linear time with the total number of
* segments that have cache entries so this cache works best with
* {@link QueryCachingPolicy caching policies} that only cache on "large"
* segments, and it is advised to not share this cache across too many indices.
*
* Typical usage looks like this:
*
* final int maxNumberOfCachedQueries = 256;
* final long maxRamBytesUsed = 50 * 1024L * 1024L; // 50MB
* // these cache and policy instances can be shared across several queries and readers
* // it is fine to eg. store them into static variables
* final QueryCache queryCache = new LRUQueryCache(maxNumberOfCachedQueries, maxRamBytesUsed);
* final QueryCachingPolicy defaultCachingPolicy = new UsageTrackingQueryCachingPolicy();
*
* // ...
*
* // Then at search time
* Query myQuery = ...;
* Query myCacheQuery = queryCache.doCache(myQuery, defaultCachingPolicy);
* // myCacheQuery is now a wrapper around the original query that will interact with the cache
* IndexSearcher searcher = ...;
* TopDocs topDocs = searcher.search(new ConstantScoreQuery(myCacheQuery), 10);
*
*
* This cache exposes some global statistics ({@link #getHitCount() hit count},
* {@link #getMissCount() miss count}, {@link #getCacheSize() number of cache
* entries}, {@link #getCacheCount() total number of DocIdSets that have ever
* been cached}, {@link #getEvictionCount() number of evicted entries}). In
* case you would like to have more fine-grained statistics, such as per-index
* or per-query-class statistics, it is possible to override various callbacks:
* {@link #onHit}, {@link #onMiss},
* {@link #onQueryCache}, {@link #onQueryEviction},
* {@link #onDocIdSetCache}, {@link #onDocIdSetEviction} and {@link #onClear}.
* It is better to not perform heavy computations in these methods though since
* they are called synchronously and under a lock.
*
* @see QueryCachingPolicy
* @lucene.experimental
*/
public class LRUQueryCache implements QueryCache, Accountable {
// memory usage of a simple term query
static final long QUERY_DEFAULT_RAM_BYTES_USED = 192;
static final long HASHTABLE_RAM_BYTES_PER_ENTRY =
2 * RamUsageEstimator.NUM_BYTES_OBJECT_REF // key + value
* 2; // hash tables need to be oversized to avoid collisions, assume 2x capacity
static final long LINKED_HASHTABLE_RAM_BYTES_PER_ENTRY =
HASHTABLE_RAM_BYTES_PER_ENTRY
+ 2 * RamUsageEstimator.NUM_BYTES_OBJECT_REF; // previous & next references
private final int maxSize;
private final long maxRamBytesUsed;
// maps queries that are contained in the cache to a singleton so that this
// cache does not store several copies of the same query
private final Map uniqueQueries;
// The contract between this set and the per-leaf caches is that per-leaf caches
// are only allowed to store sub-sets of the queries that are contained in
// mostRecentlyUsedQueries. This is why write operations are performed under a lock
private final Set mostRecentlyUsedQueries;
private final Map cache;
// these variables are volatile so that we do not need to sync reads
// but increments need to be performed under the lock
private volatile long ramBytesUsed;
private volatile long hitCount;
private volatile long missCount;
private volatile long cacheCount;
private volatile long cacheSize;
/**
* Create a new instance that will cache at most maxSize queries
* with at most maxRamBytesUsed bytes of memory.
*/
public LRUQueryCache(int maxSize, long maxRamBytesUsed) {
this.maxSize = maxSize;
this.maxRamBytesUsed = maxRamBytesUsed;
uniqueQueries = new LinkedHashMap<>(16, 0.75f, true);
mostRecentlyUsedQueries = uniqueQueries.keySet();
cache = new IdentityHashMap<>();
ramBytesUsed = 0;
}
/**
* Expert: callback when there is a cache hit on a given query.
* Implementing this method is typically useful in order to compute more
* fine-grained statistics about the query cache.
* @see #onMiss
* @lucene.experimental
*/
protected void onHit(Object readerCoreKey, Query query) {
hitCount += 1;
}
/**
* Expert: callback when there is a cache miss on a given query.
* @see #onHit
* @lucene.experimental
*/
protected void onMiss(Object readerCoreKey, Query query) {
assert query != null;
missCount += 1;
}
/**
* Expert: callback when a query is added to this cache.
* Implementing this method is typically useful in order to compute more
* fine-grained statistics about the query cache.
* @see #onQueryEviction
* @lucene.experimental
*/
protected void onQueryCache(Query query, long ramBytesUsed) {
this.ramBytesUsed += ramBytesUsed;
}
/**
* Expert: callback when a query is evicted from this cache.
* @see #onQueryCache
* @lucene.experimental
*/
protected void onQueryEviction(Query query, long ramBytesUsed) {
this.ramBytesUsed -= ramBytesUsed;
}
/**
* Expert: callback when a {@link DocIdSet} is added to this cache.
* Implementing this method is typically useful in order to compute more
* fine-grained statistics about the query cache.
* @see #onDocIdSetEviction
* @lucene.experimental
*/
protected void onDocIdSetCache(Object readerCoreKey, long ramBytesUsed) {
cacheSize += 1;
cacheCount += 1;
this.ramBytesUsed += ramBytesUsed;
}
/**
* Expert: callback when one or more {@link DocIdSet}s are removed from this
* cache.
* @see #onDocIdSetCache
* @lucene.experimental
*/
protected void onDocIdSetEviction(Object readerCoreKey, int numEntries, long sumRamBytesUsed) {
this.ramBytesUsed -= sumRamBytesUsed;
cacheSize -= numEntries;
}
/**
* Expert: callback when the cache is completely cleared.
* @lucene.experimental
*/
protected void onClear() {
ramBytesUsed = 0;
cacheSize = 0;
}
/** Whether evictions are required. */
boolean requiresEviction() {
final int size = mostRecentlyUsedQueries.size();
if (size == 0) {
return false;
} else {
return size > maxSize || ramBytesUsed() > maxRamBytesUsed;
}
}
synchronized DocIdSet get(Query key, LeafReaderContext context) {
assert key.getBoost() == 1f;
assert key instanceof BoostQuery == false;
assert key instanceof ConstantScoreQuery == false;
final Object readerKey = context.reader().getCoreCacheKey();
final LeafCache leafCache = cache.get(readerKey);
if (leafCache == null) {
onMiss(readerKey, key);
return null;
}
// this get call moves the query to the most-recently-used position
final Query singleton = uniqueQueries.get(key);
if (singleton == null) {
onMiss(readerKey, key);
return null;
}
final DocIdSet cached = leafCache.get(singleton);
if (cached == null) {
onMiss(readerKey, singleton);
} else {
onHit(readerKey, singleton);
}
return cached;
}
synchronized void putIfAbsent(Query query, LeafReaderContext context, DocIdSet set) {
// under a lock to make sure that mostRecentlyUsedQueries and cache remain sync'ed
// we don't want to have user-provided queries as keys in our cache since queries are mutable
assert query instanceof BoostQuery == false;
assert query instanceof ConstantScoreQuery == false;
assert query.getBoost() == 1f;
Query singleton = uniqueQueries.get(query);
if (singleton == null) {
uniqueQueries.put(query, query);
onQueryCache(singleton, LINKED_HASHTABLE_RAM_BYTES_PER_ENTRY + ramBytesUsed(query));
} else {
query = singleton;
}
final Object key = context.reader().getCoreCacheKey();
LeafCache leafCache = cache.get(key);
if (leafCache == null) {
leafCache = new LeafCache(key);
final LeafCache previous = cache.put(context.reader().getCoreCacheKey(), leafCache);
ramBytesUsed += HASHTABLE_RAM_BYTES_PER_ENTRY;
assert previous == null;
// we just created a new leaf cache, need to register a close listener
context.reader().addCoreClosedListener(new CoreClosedListener() {
@Override
public void onClose(Object ownerCoreCacheKey) {
clearCoreCacheKey(ownerCoreCacheKey);
}
});
}
leafCache.putIfAbsent(query, set);
evictIfNecessary();
}
synchronized void evictIfNecessary() {
// under a lock to make sure that mostRecentlyUsedQueries and cache keep sync'ed
if (requiresEviction()) {
Iterator iterator = mostRecentlyUsedQueries.iterator();
do {
final Query query = iterator.next();
final int size = mostRecentlyUsedQueries.size();
iterator.remove();
if (size == mostRecentlyUsedQueries.size()) {
// size did not decrease, because the hash of the query changed since it has been
// put into the cache
throw new ConcurrentModificationException("Removal from the cache failed! This " +
"is probably due to a query which has been modified after having been put into " +
" the cache or a badly implemented clone(). Query class: [" + query.getClass() +
"], query: [" + query + "]");
}
onEviction(query);
} while (iterator.hasNext() && requiresEviction());
}
}
/**
* Remove all cache entries for the given core cache key.
*/
public synchronized void clearCoreCacheKey(Object coreKey) {
final LeafCache leafCache = cache.remove(coreKey);
if (leafCache != null) {
ramBytesUsed -= HASHTABLE_RAM_BYTES_PER_ENTRY;
final int numEntries = leafCache.cache.size();
if (numEntries > 0) {
onDocIdSetEviction(coreKey, numEntries, leafCache.ramBytesUsed);
} else {
assert numEntries == 0;
assert leafCache.ramBytesUsed == 0;
}
}
}
/**
* Remove all cache entries for the given query.
*/
public synchronized void clearQuery(Query query) {
final Query singleton = uniqueQueries.remove(query);
if (singleton != null) {
onEviction(singleton);
}
}
private void onEviction(Query singleton) {
onQueryEviction(singleton, LINKED_HASHTABLE_RAM_BYTES_PER_ENTRY + ramBytesUsed(singleton));
for (LeafCache leafCache : cache.values()) {
leafCache.remove(singleton);
}
}
/**
* Clear the content of this cache.
*/
public synchronized void clear() {
cache.clear();
mostRecentlyUsedQueries.clear();
onClear();
}
// pkg-private for testing
synchronized void assertConsistent() {
if (requiresEviction()) {
throw new AssertionError("requires evictions: size=" + mostRecentlyUsedQueries.size()
+ ", maxSize=" + maxSize + ", ramBytesUsed=" + ramBytesUsed() + ", maxRamBytesUsed=" + maxRamBytesUsed);
}
for (LeafCache leafCache : cache.values()) {
Set keys = Collections.newSetFromMap(new IdentityHashMap());
keys.addAll(leafCache.cache.keySet());
keys.removeAll(mostRecentlyUsedQueries);
if (!keys.isEmpty()) {
throw new AssertionError("One leaf cache contains more keys than the top-level cache: " + keys);
}
}
long recomputedRamBytesUsed =
HASHTABLE_RAM_BYTES_PER_ENTRY * cache.size()
+ LINKED_HASHTABLE_RAM_BYTES_PER_ENTRY * uniqueQueries.size();
for (Query query : mostRecentlyUsedQueries) {
recomputedRamBytesUsed += ramBytesUsed(query);
}
for (LeafCache leafCache : cache.values()) {
recomputedRamBytesUsed += HASHTABLE_RAM_BYTES_PER_ENTRY * leafCache.cache.size();
for (DocIdSet set : leafCache.cache.values()) {
recomputedRamBytesUsed += set.ramBytesUsed();
}
}
if (recomputedRamBytesUsed != ramBytesUsed) {
throw new AssertionError("ramBytesUsed mismatch : " + ramBytesUsed + " != " + recomputedRamBytesUsed);
}
long recomputedCacheSize = 0;
for (LeafCache leafCache : cache.values()) {
recomputedCacheSize += leafCache.cache.size();
}
if (recomputedCacheSize != getCacheSize()) {
throw new AssertionError("cacheSize mismatch : " + getCacheSize() + " != " + recomputedCacheSize);
}
}
// pkg-private for testing
// return the list of cached queries in LRU order
synchronized List cachedQueries() {
return new ArrayList<>(mostRecentlyUsedQueries);
}
@Override
public Weight doCache(Weight weight, QueryCachingPolicy policy) {
while (weight instanceof CachingWrapperWeight) {
weight = ((CachingWrapperWeight) weight).in;
}
return new CachingWrapperWeight(weight, policy);
}
@Override
public long ramBytesUsed() {
return ramBytesUsed;
}
@Override
public Collection getChildResources() {
synchronized (this) {
return Accountables.namedAccountables("segment", cache);
}
}
/**
* Return the number of bytes used by the given query. The default
* implementation returns {@link Accountable#ramBytesUsed()} if the query
* implements {@link Accountable} and 1024 otherwise.
*/
protected long ramBytesUsed(Query query) {
if (query instanceof Accountable) {
return ((Accountable) query).ramBytesUsed();
}
return QUERY_DEFAULT_RAM_BYTES_USED;
}
/**
* Default cache implementation: uses {@link RoaringDocIdSet}.
*/
protected DocIdSet cacheImpl(BulkScorer scorer, int maxDoc) throws IOException {
final RoaringDocIdSet.Builder builder = new RoaringDocIdSet.Builder(maxDoc);
scorer.score(new LeafCollector() {
@Override
public void setScorer(Scorer scorer) throws IOException {}
@Override
public void collect(int doc) throws IOException {
builder.add(doc);
}
}, null);
return builder.build();
}
/**
* Return the total number of times that a {@link Query} has been looked up
* in this {@link QueryCache}. Note that this number is incremented once per
* segment so running a cached query only once will increment this counter
* by the number of segments that are wrapped by the searcher.
* Note that by definition, {@link #getTotalCount()} is the sum of
* {@link #getHitCount()} and {@link #getMissCount()}.
* @see #getHitCount()
* @see #getMissCount()
*/
public final long getTotalCount() {
return getHitCount() + getMissCount();
}
/**
* Over the {@link #getTotalCount() total} number of times that a query has
* been looked up, return how many times a cached {@link DocIdSet} has been
* found and returned.
* @see #getTotalCount()
* @see #getMissCount()
*/
public final long getHitCount() {
return hitCount;
}
/**
* Over the {@link #getTotalCount() total} number of times that a query has
* been looked up, return how many times this query was not contained in the
* cache.
* @see #getTotalCount()
* @see #getHitCount()
*/
public final long getMissCount() {
return missCount;
}
/**
* Return the total number of {@link DocIdSet}s which are currently stored
* in the cache.
* @see #getCacheCount()
* @see #getEvictionCount()
*/
public final long getCacheSize() {
return cacheSize;
}
/**
* Return the total number of cache entries that have been generated and put
* in the cache. It is highly desirable to have a {@link #getHitCount() hit
* count} that is much higher than the {@link #getCacheCount() cache count}
* as the opposite would indicate that the query cache makes efforts in order
* to cache queries but then they do not get reused.
* @see #getCacheSize()
* @see #getEvictionCount()
*/
public final long getCacheCount() {
return cacheCount;
}
/**
* Return the number of cache entries that have been removed from the cache
* either in order to stay under the maximum configured size/ram usage, or
* because a segment has been closed. High numbers of evictions might mean
* that queries are not reused or that the {@link QueryCachingPolicy
* caching policy} caches too aggressively on NRT segments which get merged
* early.
* @see #getCacheCount()
* @see #getCacheSize()
*/
public final long getEvictionCount() {
return getCacheCount() - getCacheSize();
}
// this class is not thread-safe, everything but ramBytesUsed needs to be called under a lock
private class LeafCache implements Accountable {
private final Object key;
private final Map cache;
private volatile long ramBytesUsed;
LeafCache(Object key) {
this.key = key;
cache = new IdentityHashMap<>();
ramBytesUsed = 0;
}
private void onDocIdSetCache(long ramBytesUsed) {
this.ramBytesUsed += ramBytesUsed;
LRUQueryCache.this.onDocIdSetCache(key, ramBytesUsed);
}
private void onDocIdSetEviction(long ramBytesUsed) {
this.ramBytesUsed -= ramBytesUsed;
LRUQueryCache.this.onDocIdSetEviction(key, 1, ramBytesUsed);
}
DocIdSet get(Query query) {
assert query instanceof BoostQuery == false;
assert query instanceof ConstantScoreQuery == false;
assert query.getBoost() == 1f;
return cache.get(query);
}
void putIfAbsent(Query query, DocIdSet set) {
assert query instanceof BoostQuery == false;
assert query instanceof ConstantScoreQuery == false;
assert query.getBoost() == 1f;
if (cache.containsKey(query) == false) {
cache.put(query, set);
// the set was actually put
onDocIdSetCache(HASHTABLE_RAM_BYTES_PER_ENTRY + set.ramBytesUsed());
}
}
void remove(Query query) {
assert query instanceof BoostQuery == false;
assert query instanceof ConstantScoreQuery == false;
assert query.getBoost() == 1f;
DocIdSet removed = cache.remove(query);
if (removed != null) {
onDocIdSetEviction(HASHTABLE_RAM_BYTES_PER_ENTRY + removed.ramBytesUsed());
}
}
@Override
public long ramBytesUsed() {
return ramBytesUsed;
}
@Override
public Collection getChildResources() {
return Collections.emptyList();
}
}
private class CachingWrapperWeight extends ConstantScoreWeight {
private final Weight in;
private final QueryCachingPolicy policy;
// we use an AtomicBoolean because Weight.scorer may be called from multiple
// threads when IndexSearcher is created with threads
private final AtomicBoolean used;
CachingWrapperWeight(Weight in, QueryCachingPolicy policy) {
super(in.getQuery());
this.in = in;
this.policy = policy;
used = new AtomicBoolean(false);
}
@Override
public void extractTerms(Set terms) {
in.extractTerms(terms);
}
private boolean cacheEntryHasReasonableWorstCaseSize(int maxDoc) {
// The worst-case (dense) is a bit set which needs one bit per document
final long worstCaseRamUsage = maxDoc / 8;
final long totalRamAvailable = maxRamBytesUsed;
// Imagine the worst-case that a cache entry is large than the size of
// the cache: not only will this entry be trashed immediately but it
// will also evict all current entries from the cache. For this reason
// we only cache on an IndexReader if we have available room for
// 5 different filters on this reader to avoid excessive trashing
return worstCaseRamUsage * 5 < totalRamAvailable;
}
private DocIdSet cache(LeafReaderContext context) throws IOException {
final BulkScorer scorer = in.bulkScorer(context);
if (scorer == null) {
return DocIdSet.EMPTY;
} else {
return cacheImpl(scorer, context.reader().maxDoc());
}
}
private boolean shouldCache(LeafReaderContext context) throws IOException {
return cacheEntryHasReasonableWorstCaseSize(ReaderUtil.getTopLevelContext(context).reader().maxDoc())
&& policy.shouldCache(in.getQuery(), context);
}
@Override
public Scorer scorer(LeafReaderContext context) throws IOException {
if (used.compareAndSet(false, true)) {
policy.onUse(getQuery());
}
DocIdSet docIdSet = get(in.getQuery(), context);
if (docIdSet == null) {
if (shouldCache(context)) {
docIdSet = cache(context);
putIfAbsent(in.getQuery(), context, docIdSet);
} else {
return in.scorer(context);
}
}
assert docIdSet != null;
if (docIdSet == DocIdSet.EMPTY) {
return null;
}
final DocIdSetIterator disi = docIdSet.iterator();
if (disi == null) {
return null;
}
return new ConstantScoreScorer(this, 0f, disi);
}
@Override
public BulkScorer bulkScorer(LeafReaderContext context) throws IOException {
if (used.compareAndSet(false, true)) {
policy.onUse(getQuery());
}
DocIdSet docIdSet = get(in.getQuery(), context);
if (docIdSet == null) {
if (shouldCache(context)) {
docIdSet = cache(context);
putIfAbsent(in.getQuery(), context, docIdSet);
} else {
return in.bulkScorer(context);
}
}
assert docIdSet != null;
if (docIdSet == DocIdSet.EMPTY) {
return null;
}
final DocIdSetIterator disi = docIdSet.iterator();
if (disi == null) {
return null;
}
return new DefaultBulkScorer(new ConstantScoreScorer(this, 0f, disi));
}
}
}
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