FunctionScore: Fix 'avg' score mode to correctly implement weighted mean.

closes #8992
closes #9004
This commit is contained in:
Guillaume Hiron 2014-12-18 11:57:59 +01:00 committed by Ryan Ernst
parent e6a190ec58
commit 8738583de6
2 changed files with 22 additions and 9 deletions

View File

@ -177,7 +177,15 @@ public class FiltersFunctionScoreQuery extends Query {
}
// First: Gather explanations for all filters
List<ComplexExplanation> filterExplanations = new ArrayList<>();
float weightSum = 0;
for (FilterFunction filterFunction : filterFunctions) {
if (filterFunction.function instanceof WeightFactorFunction) {
weightSum += ((WeightFactorFunction) filterFunction.function).getWeight();
} else {
weightSum++;
}
Bits docSet = DocIdSets.toSafeBits(context.reader(),
filterFunction.filter.getDocIdSet(context, context.reader().getLiveDocs()));
if (docSet.get(doc)) {
@ -226,15 +234,13 @@ public class FiltersFunctionScoreQuery extends Query {
break;
default: // Avg / Total
double totalFactor = 0.0f;
int count = 0;
for (int i = 0; i < filterExplanations.size(); i++) {
totalFactor += filterExplanations.get(i).getValue();
count++;
}
if (count != 0) {
if (weightSum != 0) {
factor = totalFactor;
if (scoreMode == ScoreMode.Avg) {
factor /= count;
factor /= weightSum;
}
}
}
@ -300,17 +306,21 @@ public class FiltersFunctionScoreQuery extends Query {
}
} else { // Avg / Total
double totalFactor = 0.0f;
int count = 0;
float weightSum = 0;
for (int i = 0; i < filterFunctions.length; i++) {
if (docSets[i].get(docId)) {
totalFactor += filterFunctions[i].function.score(docId, subQueryScore);
count++;
if (filterFunctions[i].function instanceof WeightFactorFunction) {
weightSum+= ((WeightFactorFunction)filterFunctions[i].function).getWeight();
} else {
weightSum++;
}
}
}
if (count != 0) {
if (weightSum != 0) {
factor = totalFactor;
if (scoreMode == ScoreMode.Avg) {
factor /= count;
factor /= weightSum;
}
}
}

View File

@ -254,8 +254,11 @@ public class FunctionScoreTests extends ElasticsearchIntegrationTest {
expectedScore = Float.MAX_VALUE;
}
float weightSum = 0;
for (int i = 0; i < weights.length; i++) {
double functionScore = (double) weights[i] * scores[i];
weightSum += weights[i];
if ("avg".equals(scoreMode)) {
expectedScore += functionScore;
@ -271,7 +274,7 @@ public class FunctionScoreTests extends ElasticsearchIntegrationTest {
}
if ("avg".equals(scoreMode)) {
expectedScore /= weights.length;
expectedScore /= weightSum;
}
return expectedScore;
}