org.elasticsearch.percolator.MultiDocumentPercolatorIndex Maven / Gradle / Ivy
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Elasticsearch subproject :server
/*
* Licensed to Elasticsearch under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch 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.elasticsearch.percolator;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.index.*;
import org.apache.lucene.index.memory.MemoryIndex;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.util.CloseableThreadLocal;
import org.elasticsearch.ElasticsearchException;
import org.elasticsearch.index.engine.Engine;
import org.elasticsearch.index.mapper.ParseContext;
import org.elasticsearch.index.mapper.ParsedDocument;
import org.elasticsearch.index.mapper.internal.UidFieldMapper;
import java.io.IOException;
import java.util.List;
/**
* Implementation of {@link PercolatorIndex} that can hold multiple Lucene documents by
* opening multiple {@link MemoryIndex} based IndexReaders and wrapping them via a single top level reader.
*/
class MultiDocumentPercolatorIndex implements PercolatorIndex {
private final CloseableThreadLocal cache;
MultiDocumentPercolatorIndex(CloseableThreadLocal cache) {
this.cache = cache;
}
@Override
public void prepare(PercolateContext context, ParsedDocument parsedDocument) {
IndexReader[] memoryIndices = new IndexReader[parsedDocument.docs().size()];
List docs = parsedDocument.docs();
int rootDocIndex = docs.size() - 1;
assert rootDocIndex > 0;
MemoryIndex rootDocMemoryIndex = null;
for (int i = 0; i < docs.size(); i++) {
ParseContext.Document d = docs.get(i);
MemoryIndex memoryIndex;
if (rootDocIndex == i) {
// the last doc is always the rootDoc, since that is usually the biggest document it make sense
// to reuse the MemoryIndex it uses
memoryIndex = rootDocMemoryIndex = cache.get();
} else {
memoryIndex = new MemoryIndex(true);
}
Analyzer analyzer = context.mapperService().documentMapper(parsedDocument.type()).mappers().indexAnalyzer();
memoryIndices[i] = indexDoc(d, analyzer, memoryIndex).createSearcher().getIndexReader();
}
try {
MultiReader mReader = new MultiReader(memoryIndices, true);
LeafReader slowReader = SlowCompositeReaderWrapper.wrap(mReader);
final IndexSearcher slowSearcher = new IndexSearcher(slowReader);
slowSearcher.setQueryCache(null);
DocSearcher docSearcher = new DocSearcher(slowSearcher, rootDocMemoryIndex);
context.initialize(docSearcher, parsedDocument);
} catch (IOException e) {
throw new ElasticsearchException("Failed to create index for percolator with nested document ", e);
}
}
MemoryIndex indexDoc(ParseContext.Document d, Analyzer analyzer, MemoryIndex memoryIndex) {
for (IndexableField field : d.getFields()) {
if (field.fieldType().indexOptions() == IndexOptions.NONE && field.name().equals(UidFieldMapper.NAME)) {
continue;
}
try {
// TODO: instead of passing null here, we can have a CTL