/*
* Licensed to ElasticSearch and Shay Banon 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.search.facet.histogram.bounded;
import org.apache.lucene.index.IndexReader;
import org.elasticsearch.common.CacheRecycler;
import org.elasticsearch.index.cache.field.data.FieldDataCache;
import org.elasticsearch.index.field.data.FieldDataType;
import org.elasticsearch.index.field.data.NumericFieldData;
import org.elasticsearch.index.mapper.MapperService;
import org.elasticsearch.search.facet.AbstractFacetCollector;
import org.elasticsearch.search.facet.Facet;
import org.elasticsearch.search.facet.FacetPhaseExecutionException;
import org.elasticsearch.search.facet.histogram.HistogramFacet;
import org.elasticsearch.search.internal.SearchContext;
import java.io.IOException;
/**
*
*/
public class BoundedValueHistogramFacetCollector extends AbstractFacetCollector {
private final String keyIndexFieldName;
private final String valueIndexFieldName;
private final long interval;
private final HistogramFacet.ComparatorType comparatorType;
private final FieldDataCache fieldDataCache;
private final FieldDataType keyFieldDataType;
private NumericFieldData keyFieldData;
private final FieldDataType valueFieldDataType;
private final HistogramProc histoProc;
public BoundedValueHistogramFacetCollector(String facetName, String keyFieldName, String valueFieldName, long interval, long from, long to, HistogramFacet.ComparatorType comparatorType, SearchContext context) {
super(facetName);
this.interval = interval;
this.comparatorType = comparatorType;
this.fieldDataCache = context.fieldDataCache();
MapperService.SmartNameFieldMappers smartMappers = context.smartFieldMappers(keyFieldName);
if (smartMappers == null || !smartMappers.hasMapper()) {
throw new FacetPhaseExecutionException(facetName, "No mapping found for field [" + keyFieldName + "]");
}
// add type filter if there is exact doc mapper associated with it
if (smartMappers.explicitTypeInNameWithDocMapper()) {
setFilter(context.filterCache().cache(smartMappers.docMapper().typeFilter()));
}
keyIndexFieldName = smartMappers.mapper().names().indexName();
keyFieldDataType = smartMappers.mapper().fieldDataType();
smartMappers = context.smartFieldMappers(valueFieldName);
if (smartMappers == null || !smartMappers.hasMapper()) {
throw new FacetPhaseExecutionException(facetName, "No mapping found for value_field [" + valueFieldName + "]");
}
valueIndexFieldName = smartMappers.mapper().names().indexName();
valueFieldDataType = smartMappers.mapper().fieldDataType();
long normalizedFrom = (((long) ((double) from / interval)) * interval);
long normalizedTo = (((long) ((double) to / interval)) * interval);
if ((to % interval) != 0) {
normalizedTo += interval;
}
long offset = -normalizedFrom;
int size = (int) ((normalizedTo - normalizedFrom) / interval);
histoProc = new HistogramProc(from, to, interval, offset, size);
}
@Override
protected void doCollect(int doc) throws IOException {
keyFieldData.forEachValueInDoc(doc, histoProc);
}
@Override
protected void doSetNextReader(IndexReader reader, int docBase) throws IOException {
keyFieldData = (NumericFieldData) fieldDataCache.cache(keyFieldDataType, reader, keyIndexFieldName);
histoProc.valueFieldData = (NumericFieldData) fieldDataCache.cache(valueFieldDataType, reader, valueIndexFieldName);
}
@Override
public Facet facet() {
return new InternalBoundedFullHistogramFacet(facetName, comparatorType, interval, -histoProc.offset, histoProc.size, histoProc.entries, true);
}
public static class HistogramProc implements NumericFieldData.LongValueInDocProc {
final long from;
final long to;
final long interval;
final long offset;
final int size;
final Object[] entries;
NumericFieldData valueFieldData;
final ValueAggregator valueAggregator = new ValueAggregator();
public HistogramProc(long from, long to, long interval, long offset, int size) {
this.from = from;
this.to = to;
this.interval = interval;
this.offset = offset;
this.size = size;
this.entries = CacheRecycler.popObjectArray(size);
}
@Override
public void onValue(int docId, long value) {
if (value <= from || value > to) { // bounds check
return;
}
int index = ((int) ((value + offset) / interval));
InternalBoundedFullHistogramFacet.FullEntry entry = (InternalBoundedFullHistogramFacet.FullEntry) entries[index];
if (entry == null) {
entry = new InternalBoundedFullHistogramFacet.FullEntry(index, 0, Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, 0, 0);
entries[index] = entry;
}
entry.count++;
valueAggregator.entry = entry;
valueFieldData.forEachValueInDoc(docId, valueAggregator);
}
public static class ValueAggregator implements NumericFieldData.DoubleValueInDocProc {
InternalBoundedFullHistogramFacet.FullEntry entry;
@Override
public void onValue(int docId, double value) {
entry.totalCount++;
entry.total += value;
if (value < entry.min) {
entry.min = value;
}
if (value > entry.max) {
entry.max = value;
}
}
}
}
}