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Use float instead of double for query vectors. #46004

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Aug 28, 2019
Merged

Use float instead of double for query vectors. #46004

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3e88ac8
Use float instead of double for query vectors.
jtibshirani Aug 26, 2019
21ef8b5
Fix failing test cases.
jtibshirani Aug 26, 2019
772b41d
Merge remote-tracking branch 'upstream/master' into float-query-vector
jtibshirani Aug 26, 2019
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2 changes: 1 addition & 1 deletion x-pack/plugin/src/test/resources/rest-api-spec/test/vectors/15_dense_vector_l1l2.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,7 @@ setup:

- match: {hits.hits.1._id: "2"}
- gte: {hits.hits.1._score: 12.29}
- lte: {hits.hits.1._score: 12.30}
- lte: {hits.hits.1._score: 12.31}

- match: {hits.hits.2._id: "3"}
- gte: {hits.hits.2._score: 0.00}
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2 changes: 1 addition & 1 deletion x-pack/plugin/src/test/resources/rest-api-spec/test/vectors/35_sparse_vector_l1l2.yml
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Expand Up @@ -63,7 +63,7 @@ setup:

- match: {hits.hits.1._id: "2"}
- gte: {hits.hits.1._score: 12.29}
- lte: {hits.hits.1._score: 12.30}
- lte: {hits.hits.1._score: 12.31}

- match: {hits.hits.2._id: "3"}
- gte: {hits.hits.2._score: 0.00}
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4 changes: 2 additions & 2 deletions ...in/vectors/src/main/java/org/elasticsearch/xpack/vectors/mapper/VectorEncoderDecoder.java
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Expand Up @@ -130,7 +130,7 @@ public void swap(int i, int j) {
* @param values - values for the sparse query vector
* @param n - number of dimensions
*/
public static void sortSparseDimsDoubleValues(int[] dims, double[] values, int n) {
public static void sortSparseDimsFloatValues(int[] dims, float[] values, int n) {
new InPlaceMergeSorter() {
@Override
public int compare(int i, int j) {
Expand All @@ -143,7 +143,7 @@ public void swap(int i, int j) {
dims[i] = dims[j];
dims[j] = tempDim;

double tempValue = values[j];
float tempValue = values[j];
values[j] = values[i];
values[i] = tempValue;
}
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24 changes: 12 additions & 12 deletions .../plugin/vectors/src/main/java/org/elasticsearch/xpack/vectors/query/ScoreScriptUtils.java
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Expand Up @@ -14,7 +14,7 @@
import java.util.List;
import java.util.Map;

import static org.elasticsearch.xpack.vectors.mapper.VectorEncoderDecoder.sortSparseDimsDoubleValues;
import static org.elasticsearch.xpack.vectors.mapper.VectorEncoderDecoder.sortSparseDimsFloatValues;

public class ScoreScriptUtils {

Expand All @@ -37,7 +37,7 @@ public static double l1norm(List<Number> queryVector, VectorScriptDocValues.Dens
Iterator<Number> queryVectorIter = queryVector.iterator();
double l1norm = 0;
for (int dim = 0; dim < docVector.length; dim++){
l1norm += Math.abs(queryVectorIter.next().doubleValue() - docVector[dim]);
l1norm += Math.abs(queryVectorIter.next().floatValue() - docVector[dim]);
}
return l1norm;
}
Expand All @@ -59,7 +59,7 @@ public static double l2norm(List<Number> queryVector, VectorScriptDocValues.Dens
Iterator<Number> queryVectorIter = queryVector.iterator();
double l2norm = 0;
for (int dim = 0; dim < docVector.length; dim++){
double diff = queryVectorIter.next().doubleValue() - docVector[dim];
double diff = queryVectorIter.next().floatValue() - docVector[dim];
l2norm += diff * diff;
}
return Math.sqrt(l2norm);
Expand Down Expand Up @@ -97,11 +97,11 @@ public static final class CosineSimilarity {
// calculate queryVectorMagnitude once per query execution
public CosineSimilarity(List<Number> queryVector) {
this.queryVector = queryVector;
double doubleValue;

double dotProduct = 0;
for (Number value : queryVector) {
doubleValue = value.doubleValue();
dotProduct += doubleValue * doubleValue;
float floatValue = value.floatValue();
dotProduct += floatValue * floatValue;
}
this.queryVectorMagnitude = Math.sqrt(dotProduct);
}
Expand Down Expand Up @@ -130,7 +130,7 @@ private static double intDotProduct(List<Number> v1, float[] v2){
double v1v2DotProduct = 0;
Iterator<Number> v1Iter = v1.iterator();
for (int dim = 0; dim < v2.length; dim++) {
v1v2DotProduct += v1Iter.next().doubleValue() * v2[dim];
v1v2DotProduct += v1Iter.next().floatValue() * v2[dim];
}
return v1v2DotProduct;
}
Expand All @@ -139,15 +139,15 @@ private static double intDotProduct(List<Number> v1, float[] v2){
//**************FUNCTIONS FOR SPARSE VECTORS

public static class VectorSparseFunctions {
final double[] queryValues;
final float[] queryValues;
final int[] queryDims;

// prepare queryVector once per script execution
// queryVector represents a map of dimensions to values
public VectorSparseFunctions(Map<String, Number> queryVector) {
//break vector into two arrays dims and values
int n = queryVector.size();
queryValues = new double[n];
queryValues = new float[n];
queryDims = new int[n];
int i = 0;
for (Map.Entry<String, Number> dimValue : queryVector.entrySet()) {
Expand All @@ -156,11 +156,11 @@ public VectorSparseFunctions(Map<String, Number> queryVector) {
} catch (final NumberFormatException e) {
throw new IllegalArgumentException("Failed to parse a query vector dimension, it must be an integer!", e);
}
queryValues[i] = dimValue.getValue().doubleValue();
queryValues[i] = dimValue.getValue().floatValue();
i++;
}
// Sort dimensions in the ascending order and sort values in the same order as their corresponding dimensions
sortSparseDimsDoubleValues(queryDims, queryValues, n);
sortSparseDimsFloatValues(queryDims, queryValues, n);
}
}

Expand Down Expand Up @@ -317,7 +317,7 @@ public double cosineSimilaritySparse(VectorScriptDocValues.SparseVectorScriptDoc
}
}

private static double intDotProductSparse(double[] v1Values, int[] v1Dims, float[] v2Values, int[] v2Dims) {
private static double intDotProductSparse(float[] v1Values, int[] v1Dims, float[] v2Values, int[] v2Dims) {
double v1v2DotProduct = 0;
int v1Index = 0;
int v2Index = 0;
Expand Down
10 changes: 5 additions & 5 deletions ...in/vectors/src/test/java/org/elasticsearch/xpack/vectors/query/ScoreScriptUtilsTests.java
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Expand Up @@ -36,11 +36,11 @@ public void testDenseVectorFunctions() {
BytesRef encodedDocVector = mockEncodeDenseVector(docVector);
VectorScriptDocValues.DenseVectorScriptDocValues dvs = mock(VectorScriptDocValues.DenseVectorScriptDocValues.class);
when(dvs.getEncodedValue()).thenReturn(encodedDocVector);
List<Number> queryVector = Arrays.asList(0.5, 111.3, -13.0, 14.8, -156.0);
List<Number> queryVector = Arrays.asList(0.5f, 111.3f, -13.0f, 14.8f, -156.0f);

// test dotProduct
double result = dotProduct(queryVector, dvs);
assertEquals("dotProduct result is not equal to the expected value!", 65425.626, result, 0.001);
assertEquals("dotProduct result is not equal to the expected value!", 65425.624, result, 0.001);

// test cosineSimilarity
CosineSimilarity cosineSimilarity = new CosineSimilarity(queryVector);
Expand Down Expand Up @@ -91,7 +91,7 @@ public void testSparseVectorFunctions() {
// test dotProduct
DotProductSparse docProductSparse = new DotProductSparse(queryVector);
double result = docProductSparse.dotProductSparse(dvs);
assertEquals("dotProductSparse result is not equal to the expected value!", 65425.626, result, 0.001);
assertEquals("dotProductSparse result is not equal to the expected value!", 65425.624, result, 0.001);

// test cosineSimilarity
CosineSimilaritySparse cosineSimilaritySparse = new CosineSimilaritySparse(queryVector);
Expand Down Expand Up @@ -128,7 +128,7 @@ public void testSparseVectorMissingDimensions1() {
// test dotProduct
DotProductSparse docProductSparse = new DotProductSparse(queryVector);
double result = docProductSparse.dotProductSparse(dvs);
assertEquals("dotProductSparse result is not equal to the expected value!", 65425.626, result, 0.001);
assertEquals("dotProductSparse result is not equal to the expected value!", 65425.624, result, 0.001);

// test cosineSimilarity
CosineSimilaritySparse cosineSimilaritySparse = new CosineSimilaritySparse(queryVector);
Expand Down Expand Up @@ -165,7 +165,7 @@ public void testSparseVectorMissingDimensions2() {
// test dotProduct
DotProductSparse docProductSparse = new DotProductSparse(queryVector);
double result = docProductSparse.dotProductSparse(dvs);
assertEquals("dotProductSparse result is not equal to the expected value!", 65425.626, result, 0.001);
assertEquals("dotProductSparse result is not equal to the expected value!", 65425.624, result, 0.001);

// test cosineSimilarity
CosineSimilaritySparse cosineSimilaritySparse = new CosineSimilaritySparse(queryVector);
Expand Down