package org.apache.lucene.document;
/**
* Copyright 2006 The Apache Software Foundation
*
* Licensed 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.
*/
import org.apache.lucene.search.PhraseQuery; // for javadocs
import org.apache.lucene.search.spans.SpanQuery; // for javadocs
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.index.FieldInvertState;
import org.apache.lucene.util.StringHelper; // for javadocs
/**
*
*
**/
public abstract class AbstractField implements Fieldable {
protected String name = "body";
protected boolean storeTermVector = false;
protected boolean storeOffsetWithTermVector = false;
protected boolean storePositionWithTermVector = false;
protected boolean omitNorms = false;
protected boolean isStored = false;
protected boolean isIndexed = true;
protected boolean isTokenized = true;
protected boolean isBinary = false;
protected boolean lazy = false;
protected boolean omitTermFreqAndPositions = false;
protected float boost = 1.0f;
// the data object for all different kind of field values
protected Object fieldsData = null;
// pre-analyzed tokenStream for indexed fields
protected TokenStream tokenStream;
// length/offset for all primitive types
protected int binaryLength;
protected int binaryOffset;
protected AbstractField()
{
}
protected AbstractField(String name, Field.Store store, Field.Index index, Field.TermVector termVector) {
if (name == null)
throw new NullPointerException("name cannot be null");
this.name = StringHelper.intern(name); // field names are interned
this.isStored = store.isStored();
this.isIndexed = index.isIndexed();
this.isTokenized = index.isAnalyzed();
this.omitNorms = index.omitNorms();
this.isBinary = false;
setStoreTermVector(termVector);
}
/** Sets the boost factor hits on this field. This value will be
* multiplied into the score of all hits on this this field of this
* document.
*
* <p>The boost is multiplied by {@link org.apache.lucene.document.Document#getBoost()} of the document
* containing this field. If a document has multiple fields with the same
* name, all such values are multiplied together. This product is then
* used to compute the norm factor for the field. By
* default, in the {@link
* org.apache.lucene.search.Similarity#computeNorm(String,
* FieldInvertState)} method, the boost value is multipled
* by the {@link
* org.apache.lucene.search.Similarity#lengthNorm(String,
* int)} and then
* rounded by {@link org.apache.lucene.search.Similarity#encodeNormValue(float)} before it is stored in the
* index. One should attempt to ensure that this product does not overflow
* the range of that encoding.
*
* @see org.apache.lucene.document.Document#setBoost(float)
* @see org.apache.lucene.search.Similarity#computeNorm(String, FieldInvertState)
* @see org.apache.lucene.search.Similarity#encodeNormValue(float)
*/
public void setBoost(float boost) {
this.boost = boost;
}
/** Returns the boost factor for hits for this field.
*
* <p>The default value is 1.0.
*
* <p>Note: this value is not stored directly with the document in the index.
* Documents returned from {@link org.apache.lucene.index.IndexReader#document(int)} and
* {@link org.apache.lucene.search.Searcher#doc(int)} may thus not have the same value present as when
* this field was indexed.
*
* @see #setBoost(float)
*/
public float getBoost() {
return boost;
}
/** Returns the name of the field as an interned string.
* For example "date", "title", "body", ...
*/
public String name() { return name; }
protected void setStoreTermVector(Field.TermVector termVector) {
this.storeTermVector = termVector.isStored();
this.storePositionWithTermVector = termVector.withPositions();
this.storeOffsetWithTermVector = termVector.withOffsets();
}
/** True iff the value of the field is to be stored in the index for return
with search hits. It is an error for this to be true if a field is
Reader-valued. */
public final boolean isStored() { return isStored; }
/** True iff the value of the field is to be indexed, so that it may be
searched on. */
public final boolean isIndexed() { return isIndexed; }
/** True iff the value of the field should be tokenized as text prior to
indexing. Un-tokenized fields are indexed as a single word and may not be
Reader-valued. */
public final boolean isTokenized() { return isTokenized; }
/** True iff the term or terms used to index this field are stored as a term
* vector, available from {@link org.apache.lucene.index.IndexReader#getTermFreqVector(int,String)}.
* These methods do not provide access to the original content of the field,
* only to terms used to index it. If the original content must be
* preserved, use the <code>stored</code> attribute instead.
*
* @see org.apache.lucene.index.IndexReader#getTermFreqVector(int, String)
*/
public final boolean isTermVectorStored() { return storeTermVector; }
/**
* True iff terms are stored as term vector together with their offsets
* (start and end position in source text).
*/
public boolean isStoreOffsetWithTermVector(){
return storeOffsetWithTermVector;
}
/**
* True iff terms are stored as term vector together with their token positions.
*/
public boolean isStorePositionWithTermVector(){
return storePositionWithTermVector;
}
/** True iff the value of the filed is stored as binary */
public final boolean isBinary() {
return isBinary;
}
/**
* Return the raw byte[] for the binary field. Note that
* you must also call {@link #getBinaryLength} and {@link
* #getBinaryOffset} to know which range of bytes in this
* returned array belong to the field.
* @return reference to the Field value as byte[].
*/
public byte[] getBinaryValue() {
return getBinaryValue(null);
}
public byte[] getBinaryValue(byte[] result){
if (isBinary || fieldsData instanceof byte[])
return (byte[]) fieldsData;
else
return null;
}
/**
* Returns length of byte[] segment that is used as value, if Field is not binary
* returned value is undefined
* @return length of byte[] segment that represents this Field value
*/
public int getBinaryLength() {
if (isBinary) {
return binaryLength;
} else if (fieldsData instanceof byte[])
return ((byte[]) fieldsData).length;
else
return 0;
}
/**
* Returns offset into byte[] segment that is used as value, if Field is not binary
* returned value is undefined
* @return index of the first character in byte[] segment that represents this Field value
*/
public int getBinaryOffset() {
return binaryOffset;
}
/** True if norms are omitted for this indexed field */
public boolean getOmitNorms() { return omitNorms; }
/** @see #setOmitTermFreqAndPositions */
public boolean getOmitTermFreqAndPositions() { return omitTermFreqAndPositions; }
/** Expert:
*
* If set, omit normalization factors associated with this indexed field.
* This effectively disables indexing boosts and length normalization for this field.
*/
public void setOmitNorms(boolean omitNorms) { this.omitNorms=omitNorms; }
/** Expert:
*
* If set, omit term freq, positions and payloads from
* postings for this field.
*
* <p><b>NOTE</b>: While this option reduces storage space
* required in the index, it also means any query
* requiring positional information, such as {@link
* PhraseQuery} or {@link SpanQuery} subclasses will
* silently fail to find results.
*/
public void setOmitTermFreqAndPositions(boolean omitTermFreqAndPositions) { this.omitTermFreqAndPositions=omitTermFreqAndPositions; }
public boolean isLazy() {
return lazy;
}
/** Prints a Field for human consumption. */
@Override
public final String toString() {
StringBuilder result = new StringBuilder();
if (isStored) {
result.append("stored");
}
if (isIndexed) {
if (result.length() > 0)
result.append(",");
result.append("indexed");
}
if (isTokenized) {
if (result.length() > 0)
result.append(",");
result.append("tokenized");
}
if (storeTermVector) {
if (result.length() > 0)
result.append(",");
result.append("termVector");
}
if (storeOffsetWithTermVector) {
if (result.length() > 0)
result.append(",");
result.append("termVectorOffsets");
}
if (storePositionWithTermVector) {
if (result.length() > 0)
result.append(",");
result.append("termVectorPosition");
}
if (isBinary) {
if (result.length() > 0)
result.append(",");
result.append("binary");
}
if (omitNorms) {
result.append(",omitNorms");
}
if (omitTermFreqAndPositions) {
result.append(",omitTermFreqAndPositions");
}
if (lazy){
result.append(",lazy");
}
result.append('<');
result.append(name);
result.append(':');
if (fieldsData != null && lazy == false) {
result.append(fieldsData);
}
result.append('>');
return result.toString();
}
}