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LUCENE-4410: Make FilteredQuery more flexible with regards to how filters are applied 

git-svn-id: https://svn.apache.org/repos/asf/lucene/dev/trunk@1388365 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Simon Willnauer 2012-09-21 08:06:36 +00:00
parent 262de45645
commit 1d39a2e8b8
6 changed files with 480 additions and 168 deletions
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6
lucene/CHANGES.txt
View File

@ -5,6 +5,10 @@ For more information on past and future Lucene versions, please see:
http://s.apache.org/luceneversions
======================= Lucene 5.0.0 =======================
New Features
* LUCENE-4410: FilteredQuery now exposes a FilterStrategy that exposes
how filters are applied during query execution. (Simon Willnauer)
Changes in backwards compatibility policy
@ -49,7 +53,7 @@ New Features
* SOLR-3441: ElisionFilterFactory is now MultiTermAware
(Jack Krupansky via hossman)
API Changes
* LUCENE-4391: All methods of Lucene40Codec but getPostingsFormatForField are

526
lucene/core/src/java/org/apache/lucene/search/FilteredQuery.java
View File

@ -42,6 +42,7 @@ public class FilteredQuery extends Query {
private final Query query;
private final Filter filter;
private final FilterStrategy strategy;
/**
* Constructs a new query which applies a filter to the results of the original query.
@ -50,28 +51,28 @@ public class FilteredQuery extends Query {
* @param filter Filter to apply to query results, cannot be <code>null</code>.
*/
public FilteredQuery (Query query, Filter filter) {
this(query, filter, RANDOM_ACCESS_FILTER_STRATEGY);
}
/**
* Expert: Constructs a new query which applies a filter to the results of the original query.
* {@link Filter#getDocIdSet} will be called every time this query is used in a search.
* @param query Query to be filtered, cannot be <code>null</code>.
* @param filter Filter to apply to query results, cannot be <code>null</code>.
* @param strategy a filter strategy used to create a filtered scorer.
*
* @see FilterStrategy
*/
public FilteredQuery (Query query, Filter filter, FilterStrategy strategy) {
if (query == null || filter == null)
throw new IllegalArgumentException("Query and filter cannot be null.");
if (strategy == null)
throw new IllegalArgumentException("FilterStrategy can not be null");
this.strategy = strategy;
this.query = query;
this.filter = filter;
}
/**
* Expert: decides if a filter should be executed as "random-access" or not.
* random-access means the filter "filters" in a similar way as deleted docs are filtered
* in lucene. This is faster when the filter accepts many documents.
* However, when the filter is very sparse, it can be faster to execute the query+filter
* as a conjunction in some cases.
*
* The default implementation returns true if the first document accepted by the
* filter is < 100.
*
* @lucene.internal
*/
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return firstFilterDoc < 100;
}
/**
* Returns a Weight that applies the filter to the enclosed query's Weight.
* This is accomplished by overriding the Scorer returned by the Weight.
@ -121,7 +122,7 @@ public class FilteredQuery extends Query {
// return a filtering scorer
@Override
public Scorer scorer(AtomicReaderContext context, boolean scoreDocsInOrder, boolean topScorer, Bits acceptDocs) throws IOException {
public Scorer scorer(AtomicReaderContext context, boolean scoreDocsInOrder, boolean topScorer, final Bits acceptDocs) throws IOException {
assert filter != null;
final DocIdSet filterDocIdSet = filter.getDocIdSet(context, acceptDocs);
@ -129,110 +130,202 @@ public class FilteredQuery extends Query {
// this means the filter does not accept any documents.
return null;
}
return strategy.filteredScorer(context, scoreDocsInOrder, topScorer, weight, filterDocIdSet);
final DocIdSetIterator filterIter = filterDocIdSet.iterator();
if (filterIter == null) {
// this means the filter does not accept any documents.
return null;
}
final int firstFilterDoc = filterIter.nextDoc();
if (firstFilterDoc == DocIdSetIterator.NO_MORE_DOCS) {
return null;
}
final Bits filterAcceptDocs = filterDocIdSet.bits();
final boolean useRandomAccess = (filterAcceptDocs != null && FilteredQuery.this.useRandomAccess(filterAcceptDocs, firstFilterDoc));
if (useRandomAccess) {
// if we are using random access, we return the inner scorer, just with other acceptDocs
return weight.scorer(context, scoreDocsInOrder, topScorer, filterAcceptDocs);
} else {
assert firstFilterDoc > -1;
// we are gonna advance() this scorer, so we set inorder=true/toplevel=false
// we pass null as acceptDocs, as our filter has already respected acceptDocs, no need to do twice
final Scorer scorer = weight.scorer(context, true, false, null);
return (scorer == null) ? null : new Scorer(this) {
private int scorerDoc = -1, filterDoc = firstFilterDoc;
// optimization: we are topScorer and collect directly using short-circuited algo
@Override
public void score(Collector collector) throws IOException {
int filterDoc = firstFilterDoc;
int scorerDoc = scorer.advance(filterDoc);
// the normalization trick already applies the boost of this query,
// so we can use the wrapped scorer directly:
collector.setScorer(scorer);
for (;;) {
if (scorerDoc == filterDoc) {
// Check if scorer has exhausted, only before collecting.
if (scorerDoc == DocIdSetIterator.NO_MORE_DOCS) {
break;
}
collector.collect(scorerDoc);
filterDoc = filterIter.nextDoc();
scorerDoc = scorer.advance(filterDoc);
} else if (scorerDoc > filterDoc) {
filterDoc = filterIter.advance(scorerDoc);
} else {
scorerDoc = scorer.advance(filterDoc);
}
}
}
private int advanceToNextCommonDoc() throws IOException {
for (;;) {
if (scorerDoc < filterDoc) {
scorerDoc = scorer.advance(filterDoc);
} else if (scorerDoc == filterDoc) {
return scorerDoc;
} else {
filterDoc = filterIter.advance(scorerDoc);
}
}
}
@Override
public int nextDoc() throws IOException {
// don't go to next doc on first call
// (because filterIter is already on first doc):
if (scorerDoc != -1) {
filterDoc = filterIter.nextDoc();
}
return advanceToNextCommonDoc();
}
@Override
public int advance(int target) throws IOException {
if (target > filterDoc) {
filterDoc = filterIter.advance(target);
}
return advanceToNextCommonDoc();
}
@Override
public int docID() {
return scorerDoc;
}
@Override
public float score() throws IOException {
return scorer.score();
}
@Override
public float freq() throws IOException { return scorer.freq(); }
@Override
public Collection<ChildScorer> getChildren() {
return Collections.singleton(new ChildScorer(scorer, "FILTERED"));
}
};
}
}
};
}
/**
* A scorer that consults the filter iff a document was matched by the
* delegate scorer. This is useful if the filter computation is more expensive
* than document scoring or if the filter has a linear running time to compute
* the next matching doc like exact geo distances.
*/
private static final class QueryFirstScorer extends Scorer {
private final Scorer scorer;
private int scorerDoc = -1;
private Bits filterbits;
protected QueryFirstScorer(Weight weight, Bits filterBits, Scorer other) {
super(weight);
this.scorer = other;
this.filterbits = filterBits;
}
// optimization: we are topScorer and collect directly
@Override
public void score(Collector collector) throws IOException {
// the normalization trick already applies the boost of this query,
// so we can use the wrapped scorer directly:
collector.setScorer(scorer);
for (;;) {
final int scorerDoc = scorer.nextDoc();
if (scorerDoc == DocIdSetIterator.NO_MORE_DOCS) {
break;
}
if (filterbits.get(scorerDoc)) {
collector.collect(scorerDoc);
}
}
}
@Override
public int nextDoc() throws IOException {
int doc;
for(;;) {
doc = scorer.nextDoc();
if (doc == Scorer.NO_MORE_DOCS || filterbits.get(doc)) {
return scorerDoc = doc;
}
}
}
@Override
public int advance(int target) throws IOException {
int doc = scorer.advance(target);
if (doc != Scorer.NO_MORE_DOCS && !filterbits.get(doc)) {
return scorerDoc = nextDoc();
} else {
return scorerDoc = doc;
}
}
@Override
public int docID() {
return scorerDoc;
}
@Override
public float score() throws IOException {
return scorer.score();
}
@Override
public float freq() throws IOException { return scorer.freq(); }
@Override
public Collection<ChildScorer> getChildren() {
return Collections.singleton(new ChildScorer(scorer, "FILTERED"));
}
}
/**
* A Scorer that uses a "leap-frog" approach (also called "zig-zag join"). The scorer and the filter
* take turns trying to advance to each other's next matching document, often
* jumping past the target document. When both land on the same document, it's
* collected.
*/
private static class LeapFrogScorer extends Scorer {
private final DocIdSetIterator secondary;
private final DocIdSetIterator primary;
private final Scorer scorer;
private int primaryDoc = -1;
protected int secondaryDoc = -1;
protected LeapFrogScorer(Weight weight, DocIdSetIterator primary, DocIdSetIterator secondary, Scorer scorer) {
super(weight);
this.primary = primary;
this.secondary = secondary;
this.scorer = scorer;
}
// optimization: we are topScorer and collect directly using short-circuited algo
@Override
public final void score(Collector collector) throws IOException {
int primDoc = primaryNext();
int secDoc = secondary.advance(primDoc);
// the normalization trick already applies the boost of this query,
// so we can use the wrapped scorer directly:
collector.setScorer(scorer);
for (;;) {
if (primDoc == secDoc) {
// Check if scorer has exhausted, only before collecting.
if (primDoc == DocIdSetIterator.NO_MORE_DOCS) {
break;
}
collector.collect(primDoc);
primDoc = primary.nextDoc();
secDoc = secondary.advance(primDoc);
} else if (secDoc > primDoc) {
primDoc = primary.advance(secDoc);
} else {
secDoc = secondary.advance(primDoc);
}
}
}
private final int advanceToNextCommonDoc() throws IOException {
for (;;) {
if (secondaryDoc < primaryDoc) {
secondaryDoc = secondary.advance(primaryDoc);
} else if (secondaryDoc == primaryDoc) {
return primaryDoc;
} else {
primaryDoc = primary.advance(secondaryDoc);
}
}
}
@Override
public final int nextDoc() throws IOException {
primaryDoc = primaryNext();
return advanceToNextCommonDoc();
}
protected int primaryNext() throws IOException {
return primary.nextDoc();
}
@Override
public final int advance(int target) throws IOException {
if (target > primaryDoc) {
primaryDoc = primary.advance(target);
}
return advanceToNextCommonDoc();
}
@Override
public final int docID() {
assert scorer.docID() == primaryDoc;
return primaryDoc;
}
@Override
public final float score() throws IOException {
return scorer.score();
}
@Override
public final float freq() throws IOException { return scorer.freq(); }
@Override
public final Collection<ChildScorer> getChildren() {
return Collections.singleton(new ChildScorer(scorer, "FILTERED"));
}
}
// TODO once we have way to figure out if we use RA or LeapFrog we can remove this scorer
private static final class PrimaryAdvancedLeapFrogScorer extends LeapFrogScorer {
private final int firstFilteredDoc;
protected PrimaryAdvancedLeapFrogScorer(Weight weight, int firstFilteredDoc, DocIdSetIterator filterIter, Scorer other) {
super(weight, filterIter, other, other);
this.firstFilteredDoc = firstFilteredDoc;
}
@Override
protected int primaryNext() throws IOException {
if (secondaryDoc != -1) {
return super.primaryNext();
} else {
return firstFilteredDoc;
}
}
}
/** Rewrites the query. If the wrapped is an instance of
* {@link MatchAllDocsQuery} it returns a {@link ConstantScoreQuery}. Otherwise
* it returns a new {@code FilteredQuery} wrapping the rewritten query. */
@ -297,15 +390,214 @@ public class FilteredQuery extends Query {
return false;
assert o instanceof FilteredQuery;
final FilteredQuery fq = (FilteredQuery) o;
return fq.query.equals(this.query) && fq.filter.equals(this.filter);
return fq.query.equals(this.query) && fq.filter.equals(this.filter) && fq.strategy.equals(this.strategy);
}
/** Returns a hash code value for this object. */
@Override
public int hashCode() {
int hash = super.hashCode();
hash = hash * 31 + strategy.hashCode();
hash = hash * 31 + query.hashCode();
hash = hash * 31 + filter.hashCode();
return hash;
}
/**
* A {@link FilterStrategy} that conditionally uses a random access filter if
* the given {@link DocIdSet} supports random access (returns a non-null value
* from {@link DocIdSet#bits()}) and
* {@link RandomAccessFilterStrategy#useRandomAccess(Bits, int)} returns
* <code>true</code>. Otherwise this strategy falls back to a "zig-zag join" (
* {@link FilteredQuery#LEAP_FROG_FILTER_FIRST_STRATEGY}) strategy.
*
* <p>
* Note: this strategy is the default strategy in {@link FilteredQuery}
* </p>
*/
public static final FilterStrategy RANDOM_ACCESS_FILTER_STRATEGY = new RandomAccessFilterStrategy();
/**
* A filter strategy that uses a "leap-frog" approach (also called "zig-zag join").
* The scorer and the filter
* take turns trying to advance to each other's next matching document, often
* jumping past the target document. When both land on the same document, it's
* collected.
* <p>
* Note: This strategy uses the filter to lead the iteration.
* </p>
*/
public static final FilterStrategy LEAP_FROG_FILTER_FIRST_STRATEGY = new LeapFrogFilterStragey(false);
/**
* A filter strategy that uses a "leap-frog" approach (also called "zig-zag join").
* The scorer and the filter
* take turns trying to advance to each other's next matching document, often
* jumping past the target document. When both land on the same document, it's
* collected.
* <p>
* Note: This strategy uses the query to lead the iteration.
* </p>
*/
public static final FilterStrategy LEAP_FROG_QUERY_FIRST_STRATEGY = new LeapFrogFilterStragey(true);
/**
* A filter strategy that advances the Query or rather its {@link Scorer} first and consults the
* filter {@link DocIdSet} for each matched document.
* <p>
* Note: this strategy requires a {@link DocIdSet#bits()} to return a non-null value. Otherwise
* this strategy falls back to {@link FilteredQuery#LEAP_FROG_QUERY_FIRST_STRATEGY}
* </p>
* <p>
* Use this strategy if the filter computation is more expensive than document
* scoring or if the filter has a linear running time to compute the next
* matching doc like exact geo distances.
* </p>
*/
public static final FilterStrategy QUERY_FIRST_FILTER_STRATEGY = new QueryFirstFilterStrategy();
/** Abstract class that defines how the filter ({@link DocIdSet}) applied during document collection. */
public static abstract class FilterStrategy {
/**
* Returns a filtered {@link Scorer} based on this strategy.
*
* @param context
* the {@link AtomicReaderContext} for which to return the {@link Scorer}.
* @param scoreDocsInOrder
* specifies whether in-order scoring of documents is required. Note
* that if set to false (i.e., out-of-order scoring is required),
* this method can return whatever scoring mode it supports, as every
* in-order scorer is also an out-of-order one. However, an
* out-of-order scorer may not support {@link Scorer#nextDoc()}
* and/or {@link Scorer#advance(int)}, therefore it is recommended to
* request an in-order scorer if use of these methods is required.
* @param topScorer
* if true, {@link Scorer#score(Collector)} will be called; if false,
* {@link Scorer#nextDoc()} and/or {@link Scorer#advance(int)} will
* be called.
* @param weight the {@link FilteredQuery} {@link Weight} to create the filtered scorer.
* @param docIdSet the filter {@link DocIdSet} to apply
* @return a filtered scorer
*
* @throws IOException if an {@link IOException} occurs
*/
public abstract Scorer filteredScorer(AtomicReaderContext context,
boolean scoreDocsInOrder, boolean topScorer, Weight weight,
DocIdSet docIdSet) throws IOException;
}
/**
* A {@link FilterStrategy} that conditionally uses a random access filter if
* the given {@link DocIdSet} supports random access (returns a non-null value
* from {@link DocIdSet#bits()}) and
* {@link RandomAccessFilterStrategy#useRandomAccess(Bits, int)} returns
* <code>true</code>. Otherwise this strategy falls back to a "zig-zag join" (
* {@link FilteredQuery#LEAP_FROG_FILTER_FIRST_STRATEGY}) strategy .
*/
public static class RandomAccessFilterStrategy extends FilterStrategy {
@Override
public Scorer filteredScorer(AtomicReaderContext context, boolean scoreDocsInOrder, boolean topScorer, Weight weight, DocIdSet docIdSet) throws IOException {
final DocIdSetIterator filterIter = docIdSet.iterator();
if (filterIter == null) {
// this means the filter does not accept any documents.
return null;
}
final int firstFilterDoc = filterIter.nextDoc();
if (firstFilterDoc == DocIdSetIterator.NO_MORE_DOCS) {
return null;
}
final Bits filterAcceptDocs = docIdSet.bits();
// force if RA is requested
final boolean useRandomAccess = (filterAcceptDocs != null && (useRandomAccess(filterAcceptDocs, firstFilterDoc)));
if (useRandomAccess) {
// if we are using random access, we return the inner scorer, just with other acceptDocs
return weight.scorer(context, scoreDocsInOrder, topScorer, filterAcceptDocs);
} else {
assert firstFilterDoc > -1;
// we are gonna advance() this scorer, so we set inorder=true/toplevel=false
// we pass null as acceptDocs, as our filter has already respected acceptDocs, no need to do twice
final Scorer scorer = weight.scorer(context, true, false, null);
// TODO once we have way to figure out if we use RA or LeapFrog we can remove this scorer
return (scorer == null) ? null : new PrimaryAdvancedLeapFrogScorer(weight, firstFilterDoc, filterIter, scorer);
}
}
/**
* Expert: decides if a filter should be executed as "random-access" or not.
* random-access means the filter "filters" in a similar way as deleted docs are filtered
* in Lucene. This is faster when the filter accepts many documents.
* However, when the filter is very sparse, it can be faster to execute the query+filter
* as a conjunction in some cases.
*
* The default implementation returns <code>true</code> if the first document accepted by the
* filter is < 100.
*
* @lucene.internal
*/
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
//TODO once we have a cost API on filters and scorers we should rethink this heuristic
return firstFilterDoc < 100;
}
}
private static final class LeapFrogFilterStragey extends FilterStrategy {
private final boolean scorerFirst;
private LeapFrogFilterStragey(boolean scorerFirst) {
this.scorerFirst = scorerFirst;
}
@Override
public Scorer filteredScorer(AtomicReaderContext context,
boolean scoreDocsInOrder, boolean topScorer, Weight weight,
DocIdSet docIdSet) throws IOException {
final DocIdSetIterator filterIter = docIdSet.iterator();
if (filterIter == null) {
// this means the filter does not accept any documents.
return null;
}
// we are gonna advance() this scorer, so we set inorder=true/toplevel=false
// we pass null as acceptDocs, as our filter has already respected acceptDocs, no need to do twice
final Scorer scorer = weight.scorer(context, true, false, null);
if (scorerFirst) {
return (scorer == null) ? null : new LeapFrogScorer(weight, filterIter, scorer, scorer);
} else {
return (scorer == null) ? null : new LeapFrogScorer(weight, scorer, filterIter, scorer);
}
}
}
/**
* A filter strategy that advances the {@link Scorer} first and consults the
* {@link DocIdSet} for each matched document.
* <p>
* Note: this strategy requires a {@link DocIdSet#bits()} to return a non-null value. Otherwise
* this strategy falls back to {@link FilteredQuery#LEAP_FROG_QUERY_FIRST_STRATEGY}
* </p>
* <p>
* Use this strategy if the filter computation is more expensive than document
* scoring or if the filter has a linear running time to compute the next
* matching doc like exact geo distances.
* </p>
*/
private static final class QueryFirstFilterStrategy extends FilterStrategy {
@Override
public Scorer filteredScorer(final AtomicReaderContext context,
boolean scoreDocsInOrder, boolean topScorer, Weight weight,
DocIdSet docIdSet) throws IOException {
Bits filterAcceptDocs = docIdSet.bits();
if (filterAcceptDocs == null) {
return LEAP_FROG_QUERY_FIRST_STRATEGY.filteredScorer(context, scoreDocsInOrder, topScorer, weight, docIdSet);
}
final Scorer scorer = weight.scorer(context, true, false, null);
return scorer == null ? null : new QueryFirstScorer(weight,
filterAcceptDocs, scorer);
}
}
}

56
lucene/core/src/test/org/apache/lucene/search/TestFilteredQuery.java
View File

@ -18,6 +18,7 @@ package org.apache.lucene.search;
*/
import java.util.BitSet;
import java.util.Random;
import org.apache.lucene.analysis.MockAnalyzer;
import org.apache.lucene.document.Document;
@ -31,6 +32,7 @@ import org.apache.lucene.store.Directory;
import org.apache.lucene.util.Bits;
import org.apache.lucene.util.DocIdBitSet;
import org.apache.lucene.util.LuceneTestCase;
import org.apache.lucene.util._TestUtil;
/**
* FilteredQuery JUnit tests.
@ -117,7 +119,7 @@ public class TestFilteredQuery extends LuceneTestCase {
}
private void tFilteredQuery(final boolean useRandomAccess) throws Exception {
Query filteredquery = new FilteredQueryRA(query, filter, useRandomAccess);
Query filteredquery = new FilteredQuery(query, filter, randomFilterStrategy(random(), useRandomAccess));
ScoreDoc[] hits = searcher.search (filteredquery, null, 1000).scoreDocs;
assertEquals (1, hits.length);
assertEquals (1, hits[0].doc);
@ -127,23 +129,23 @@ public class TestFilteredQuery extends LuceneTestCase {
assertEquals (1, hits.length);
assertEquals (1, hits[0].doc);
filteredquery = new FilteredQueryRA(new TermQuery (new Term ("field", "one")), filter, useRandomAccess);
filteredquery = new FilteredQuery(new TermQuery (new Term ("field", "one")), filter, randomFilterStrategy(random(), useRandomAccess));
hits = searcher.search (filteredquery, null, 1000).scoreDocs;
assertEquals (2, hits.length);
QueryUtils.check(random(), filteredquery,searcher);
filteredquery = new FilteredQueryRA(new MatchAllDocsQuery(), filter, useRandomAccess);
filteredquery = new FilteredQuery(new MatchAllDocsQuery(), filter, randomFilterStrategy(random(), useRandomAccess));
hits = searcher.search (filteredquery, null, 1000).scoreDocs;
assertEquals (2, hits.length);
QueryUtils.check(random(), filteredquery,searcher);
filteredquery = new FilteredQueryRA(new TermQuery (new Term ("field", "x")), filter, useRandomAccess);
filteredquery = new FilteredQuery(new TermQuery (new Term ("field", "x")), filter, randomFilterStrategy(random(), useRandomAccess));
hits = searcher.search (filteredquery, null, 1000).scoreDocs;
assertEquals (1, hits.length);
assertEquals (3, hits[0].doc);
QueryUtils.check(random(), filteredquery,searcher);
filteredquery = new FilteredQueryRA(new TermQuery (new Term ("field", "y")), filter, useRandomAccess);
filteredquery = new FilteredQuery(new TermQuery (new Term ("field", "y")), filter, randomFilterStrategy(random(), useRandomAccess));
hits = searcher.search (filteredquery, null, 1000).scoreDocs;
assertEquals (0, hits.length);
QueryUtils.check(random(), filteredquery,searcher);
@ -160,7 +162,7 @@ public class TestFilteredQuery extends LuceneTestCase {
BooleanQuery bq2 = new BooleanQuery();
tq = new TermQuery (new Term ("field", "one"));
filteredquery = new FilteredQueryRA(tq, f, useRandomAccess);
filteredquery = new FilteredQuery(tq, f, randomFilterStrategy(random(), useRandomAccess));
filteredquery.setBoost(boost);
bq2.add(filteredquery, Occur.MUST);
bq2.add(new TermQuery (new Term ("field", "five")), Occur.MUST);
@ -210,7 +212,7 @@ public class TestFilteredQuery extends LuceneTestCase {
TermRangeQuery rq = TermRangeQuery.newStringRange(
"sorter", "b", "d", true, true);
Query filteredquery = new FilteredQueryRA(rq, filter, useRandomAccess);
Query filteredquery = new FilteredQuery(rq, filter, randomFilterStrategy(random(), useRandomAccess));
ScoreDoc[] hits = searcher.search(filteredquery, null, 1000).scoreDocs;
assertEquals(2, hits.length);
QueryUtils.check(random(), filteredquery,searcher);
@ -225,9 +227,9 @@ public class TestFilteredQuery extends LuceneTestCase {
private void tBooleanMUST(final boolean useRandomAccess) throws Exception {
BooleanQuery bq = new BooleanQuery();
Query query = new FilteredQueryRA(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(0), useRandomAccess);
Query query = new FilteredQuery(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(0), randomFilterStrategy(random(), useRandomAccess));
bq.add(query, BooleanClause.Occur.MUST);
query = new FilteredQueryRA(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(1), useRandomAccess);
query = new FilteredQuery(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(1), randomFilterStrategy(random(), useRandomAccess));
bq.add(query, BooleanClause.Occur.MUST);
ScoreDoc[] hits = searcher.search(bq, null, 1000).scoreDocs;
assertEquals(0, hits.length);
@ -243,9 +245,9 @@ public class TestFilteredQuery extends LuceneTestCase {
private void tBooleanSHOULD(final boolean useRandomAccess) throws Exception {
BooleanQuery bq = new BooleanQuery();
Query query = new FilteredQueryRA(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(0), useRandomAccess);
Query query = new FilteredQuery(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(0), randomFilterStrategy(random(), useRandomAccess));
bq.add(query, BooleanClause.Occur.SHOULD);
query = new FilteredQueryRA(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(1), useRandomAccess);
query = new FilteredQuery(new TermQuery(new Term("field", "one")), new SingleDocTestFilter(1), randomFilterStrategy(random(), useRandomAccess));
bq.add(query, BooleanClause.Occur.SHOULD);
ScoreDoc[] hits = searcher.search(bq, null, 1000).scoreDocs;
assertEquals(2, hits.length);
@ -263,7 +265,7 @@ public class TestFilteredQuery extends LuceneTestCase {
private void tBoolean2(final boolean useRandomAccess) throws Exception {
BooleanQuery bq = new BooleanQuery();
Query query = new FilteredQueryRA(bq, new SingleDocTestFilter(0), useRandomAccess);
Query query = new FilteredQuery(bq, new SingleDocTestFilter(0), randomFilterStrategy(random(), useRandomAccess));
bq.add(new TermQuery(new Term("field", "one")), BooleanClause.Occur.SHOULD);
bq.add(new TermQuery(new Term("field", "two")), BooleanClause.Occur.SHOULD);
ScoreDoc[] hits = searcher.search(query, 1000).scoreDocs;
@ -279,16 +281,16 @@ public class TestFilteredQuery extends LuceneTestCase {
}
private void tChainedFilters(final boolean useRandomAccess) throws Exception {
Query query = new TestFilteredQuery.FilteredQueryRA(new TestFilteredQuery.FilteredQueryRA(
new MatchAllDocsQuery(), new CachingWrapperFilter(new QueryWrapperFilter(new TermQuery(new Term("field", "three")))), useRandomAccess),
new CachingWrapperFilter(new QueryWrapperFilter(new TermQuery(new Term("field", "four")))), useRandomAccess);
Query query = new FilteredQuery(new FilteredQuery(
new MatchAllDocsQuery(), new CachingWrapperFilter(new QueryWrapperFilter(new TermQuery(new Term("field", "three")))), randomFilterStrategy(random(), useRandomAccess)),
new CachingWrapperFilter(new QueryWrapperFilter(new TermQuery(new Term("field", "four")))), randomFilterStrategy(random(), useRandomAccess));
ScoreDoc[] hits = searcher.search(query, 10).scoreDocs;
assertEquals(2, hits.length);
QueryUtils.check(random(), query, searcher);
// one more:
query = new TestFilteredQuery.FilteredQueryRA(query,
new CachingWrapperFilter(new QueryWrapperFilter(new TermQuery(new Term("field", "five")))), useRandomAccess);
query = new FilteredQuery(query,
new CachingWrapperFilter(new QueryWrapperFilter(new TermQuery(new Term("field", "five")))), randomFilterStrategy(random(), useRandomAccess));
hits = searcher.search(query, 10).scoreDocs;
assertEquals(1, hits.length);
QueryUtils.check(random(), query, searcher);
@ -363,19 +365,17 @@ public class TestFilteredQuery extends LuceneTestCase {
assertRewrite(new FilteredQuery(new TermQuery(new Term("field", "one")), new PrefixFilter(new Term("field", "o"))), FilteredQuery.class);
assertRewrite(new FilteredQuery(new MatchAllDocsQuery(), new PrefixFilter(new Term("field", "o"))), ConstantScoreQuery.class);
}
public static final class FilteredQueryRA extends FilteredQuery {
private final boolean useRandomAccess;
public FilteredQueryRA(Query q, Filter f, boolean useRandomAccess) {
super(q,f);
this.useRandomAccess = useRandomAccess;
}
@Override
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return useRandomAccess;
private static FilteredQuery.FilterStrategy randomFilterStrategy(Random random, final boolean useRandomAccess) {
if (useRandomAccess) {
return new FilteredQuery.RandomAccessFilterStrategy() {
@Override
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return useRandomAccess;
}
};
}
return _TestUtil.randomFilterStrategy(random);
}
}

10
lucene/test-framework/src/java/org/apache/lucene/search/AssertingIndexSearcher.java
View File

@ -25,6 +25,7 @@ import org.apache.lucene.index.AtomicReaderContext;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.IndexReaderContext;
import org.apache.lucene.util.Bits;
import org.apache.lucene.util._TestUtil;
/**
* Helper class that adds some extra checks to ensure correct
@ -101,16 +102,11 @@ public class AssertingIndexSearcher extends IndexSearcher {
}
};
}
@Override
protected Query wrapFilter(Query query, Filter filter) {
if (random.nextBoolean())
return super.wrapFilter(query, filter);
return (filter == null) ? query : new FilteredQuery(query, filter) {
@Override
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return random.nextBoolean();
}
};
return (filter == null) ? query : new FilteredQuery(query, filter, _TestUtil.randomFilterStrategy(random));
}
}

16
lucene/test-framework/src/java/org/apache/lucene/search/SearchEquivalenceTestBase.java
View File

@ -173,20 +173,8 @@ public abstract class SearchEquivalenceTestBase extends LuceneTestCase {
protected void assertSubsetOf(Query q1, Query q2, Filter filter) throws Exception {
// TRUNK ONLY: test both filter code paths
if (filter != null && random().nextBoolean()) {
final boolean q1RandomAccess = random().nextBoolean();
final boolean q2RandomAccess = random().nextBoolean();
q1 = new FilteredQuery(q1, filter) {
@Override
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return q1RandomAccess;
}
};
q2 = new FilteredQuery(q2, filter) {
@Override
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return q2RandomAccess;
}
};
q1 = new FilteredQuery(q1, filter, _TestUtil.randomFilterStrategy(random()));
q2 = new FilteredQuery(q2, filter, _TestUtil.randomFilterStrategy(random()));
filter = null;
}

34
lucene/test-framework/src/java/org/apache/lucene/util/_TestUtil.java
View File

@ -29,7 +29,12 @@ import java.lang.reflect.Method;
import java.math.BigDecimal;
import java.math.BigInteger;
import java.nio.CharBuffer;
import java.util.*;
import java.util.Arrays;
import java.util.Enumeration;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Random;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.TimeUnit;
import java.util.regex.Pattern;
@ -72,6 +77,8 @@ import org.apache.lucene.index.Terms;
import org.apache.lucene.index.TermsEnum;
import org.apache.lucene.index.TieredMergePolicy;
import org.apache.lucene.search.FieldDoc;
import org.apache.lucene.search.FilteredQuery;
import org.apache.lucene.search.FilteredQuery.FilterStrategy;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.CompoundFileDirectory;
@ -975,4 +982,29 @@ public class _TestUtil {
}
}
}
public static final FilterStrategy randomFilterStrategy(final Random random) {
switch(random.nextInt(6)) {
case 5:
case 4:
return new FilteredQuery.RandomAccessFilterStrategy() {
@Override
protected boolean useRandomAccess(Bits bits, int firstFilterDoc) {
return random.nextBoolean();
}
};
case 3:
return FilteredQuery.RANDOM_ACCESS_FILTER_STRATEGY;
case 2:
return FilteredQuery.LEAP_FROG_FILTER_FIRST_STRATEGY;
case 1:
return FilteredQuery.LEAP_FROG_QUERY_FIRST_STRATEGY;
case 0:
return FilteredQuery.QUERY_FIRST_FILTER_STRATEGY;
default:
return FilteredQuery.RANDOM_ACCESS_FILTER_STRATEGY;
}
}
}