blob: 68588c5aba2e5bffdf76420940e75fdbc4d08ece [file] [log] [blame]
/*
* 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.lucene.facet.taxonomy.writercache;
import org.apache.lucene.facet.taxonomy.FacetLabel;
/**
* LRU {@link TaxonomyWriterCache} - good choice for huge taxonomies.
*
* @lucene.experimental
*/
public class LruTaxonomyWriterCache implements TaxonomyWriterCache {
/**
* Determines cache type.
* For guaranteed correctness - not relying on no-collisions in the hash
* function, LRU_STRING should be used.
*/
public enum LRUType {
/** Use only the label's 64 bit longHashCode as the hash key. Do not
* check equals, unlike most hash maps.
* Note that while these hashes are very likely to be unique, the chance
* of a collision is still greater than zero. If such an unlikely event
* occurs, your document will get an incorrect facet.
*/
LRU_HASHED,
/** Use the label as the hash key; this is always
* correct but will usually use more RAM. */
LRU_STRING
}
private NameIntCacheLRU cache;
/** Creates this with {@link LRUType#LRU_STRING} method. */
public LruTaxonomyWriterCache(int cacheSize) {
// TODO (Facet): choose between NameHashIntCacheLRU and NameIntCacheLRU.
// For guaranteed correctness - not relying on no-collisions in the hash
// function, NameIntCacheLRU should be used:
// On the other hand, NameHashIntCacheLRU takes less RAM but if there
// are collisions two different paths would be mapped to the same
// ordinal...
this(cacheSize, LRUType.LRU_STRING);
}
/** Creates this with the specified method. */
public LruTaxonomyWriterCache(int cacheSize, LRUType lruType) {
// TODO (Facet): choose between NameHashIntCacheLRU and NameIntCacheLRU.
// For guaranteed correctness - not relying on no-collisions in the hash
// function, NameIntCacheLRU should be used:
// On the other hand, NameHashIntCacheLRU takes less RAM but if there
// are collisions two different paths would be mapped to the same
// ordinal...
if (lruType == LRUType.LRU_HASHED) {
this.cache = new NameHashIntCacheLRU(cacheSize);
} else {
this.cache = new NameIntCacheLRU(cacheSize);
}
}
@Override
public synchronized boolean isFull() {
return cache.getSize() == cache.getMaxSize();
}
@Override
public synchronized void clear() {
cache.clear();
}
@Override
public synchronized void close() {
cache.clear();
cache = null;
}
@Override
public int size() {
return cache.getSize();
}
@Override
public synchronized int get(FacetLabel categoryPath) {
Integer res = cache.get(categoryPath);
if (res == null) {
return -1;
}
return res.intValue();
}
@Override
public synchronized boolean put(FacetLabel categoryPath, int ordinal) {
boolean ret = cache.put(categoryPath, ordinal);
// If the cache is full, we need to clear one or more old entries
// from the cache. However, if we delete from the cache a recent
// addition that isn't yet in our reader, for this entry to be
// visible to us we need to make sure that the changes have been
// committed and we reopen the reader. Because this is a slow
// operation, we don't delete entries one-by-one but rather in bulk
// (put() removes the 1/3rd oldest entries).
if (ret) {
cache.makeRoomLRU();
}
return ret;
}
}