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// Copyright 2019 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.prelude.searcher;
import com.google.common.util.concurrent.MoreExecutors;
import com.yahoo.config.subscription.ConfigGetter;
import com.yahoo.config.subscription.RawSource;
import com.yahoo.language.Linguistics;
import com.yahoo.language.simple.SimpleLinguistics;
import com.yahoo.prelude.Index;
import com.yahoo.prelude.IndexFacts;
import com.yahoo.prelude.IndexModel;
import com.yahoo.prelude.SearchDefinition;
import com.yahoo.search.Query;
import com.yahoo.search.query.parser.Parsable;
import com.yahoo.search.query.parser.ParserEnvironment;
import com.yahoo.search.query.QueryTree;
import com.yahoo.search.rendering.RendererRegistry;
import com.yahoo.search.Result;
import com.yahoo.search.result.ErrorMessage;
import com.yahoo.search.searchchain.Execution;
import com.yahoo.search.Searcher;
import com.yahoo.search.searchers.ValidateNearestNeighborSearcher;
import com.yahoo.search.yql.YqlParser;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import com.yahoo.vespa.config.search.AttributesConfig;
import java.util.*;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertNull;
/**
* @author arnej
*/
public class ValidateNearestNeighborTestCase {
ValidateNearestNeighborSearcher searcher;
public ValidateNearestNeighborTestCase() {
searcher = new ValidateNearestNeighborSearcher(
ConfigGetter.getConfig(AttributesConfig.class,
"raw:",
new RawSource("attribute[5]\n" +
"attribute[0].name simple\n" +
"attribute[0].datatype INT32\n" +
"attribute[1].name dvector\n" +
"attribute[1].datatype TENSOR\n" +
"attribute[1].tensortype tensor(x[3])\n" +
"attribute[2].name fvector\n" +
"attribute[2].datatype TENSOR\n" +
"attribute[2].tensortype tensor<float>(x[3])\n" +
"attribute[3].name sparse\n" +
"attribute[3].datatype TENSOR\n" +
"attribute[3].tensortype tensor(x{})\n" +
"attribute[4].name matrix\n" +
"attribute[4].datatype TENSOR\n" +
"attribute[4].tensortype tensor(x[3],y[1])\n"
)));
}
private static TensorType tt_dense_dvector_3 = TensorType.fromSpec("tensor(x[3])");
private static TensorType tt_dense_fvector_3 = TensorType.fromSpec("tensor<float>(x[3])");
private static TensorType tt_dense_matrix_xy = TensorType.fromSpec("tensor(x[3],y[1])");
private static TensorType tt_sparse_vector_x = TensorType.fromSpec("tensor(x{})");
private Tensor makeTensor(TensorType tensorType) {
Tensor.Builder tensorBuilder = Tensor.Builder.of(tensorType);
double dv = 1.0;
String tensorDimension = "x";
for (long label = 0; label < 3; label++) {
tensorBuilder.cell()
.label(tensorDimension, label)
.value(dv);
dv += 1.0;
}
return tensorBuilder.build();
}
private Tensor makeMatrix(TensorType tensorType) {
Tensor.Builder tensorBuilder = Tensor.Builder.of(tensorType);
double dv = 1.0;
String tensorDimension = "x";
for (long label = 0; label < 3; label++) {
tensorBuilder.cell()
.label("y", 0L)
.label(tensorDimension, label)
.value(dv);
dv += 1.0;
}
return tensorBuilder.build();
}
@Test
public void testValidQueryDV() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(dvector,qvector);";
Tensor t = makeTensor(tt_dense_dvector_3);
Result r = doSearch(searcher, q, t);
assertNull(r.hits().getError());
}
@Test
public void testValidQueryFV() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(fvector,qvector);";
Tensor t = makeTensor(tt_dense_fvector_3);
Result r = doSearch(searcher, q, t);
assertNull(r.hits().getError());
}
private static void assertErrMsg(String message, Result r) {
assertEquals(ErrorMessage.createIllegalQuery(message), r.hits().getError());
}
@Test
public void testMissingTargetNumHits() {
String q = "select * from sources * where nearestNeighbor(dvector,qvector);";
Tensor t = makeTensor(tt_dense_dvector_3);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=dvector,queryTensorName=qvector,targetNumHits=0} has invalid targetNumHits", r);
}
@Test
public void testMissingQueryTensor() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(dvector,foo);";
Tensor t = makeTensor(tt_dense_dvector_3);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=dvector,queryTensorName=foo,targetNumHits=1} query tensor not found", r);
}
@Test
public void testQueryTensorWrongType() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(dvector,qvector);";
Result r = doSearch(searcher, q, "tensor string");
assertErrMsg("NEAREST_NEIGHBOR {field=dvector,queryTensorName=qvector,targetNumHits=1} query tensor should be a tensor, was: class java.lang.String", r);
r = doSearch(searcher, q, null);
assertErrMsg("NEAREST_NEIGHBOR {field=dvector,queryTensorName=qvector,targetNumHits=1} query tensor should be a tensor, was: null", r);
}
@Test
public void testWrongTensorType() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(fvector,qvector);";
Tensor t = makeTensor(tt_dense_dvector_3);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=fvector,queryTensorName=qvector,targetNumHits=1} field type tensor<float>(x[3]) does not match query tensor type tensor(x[3])", r);
}
@Test
public void testNotAttribute() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(foo,qvector);";
Tensor t = makeTensor(tt_dense_dvector_3);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=foo,queryTensorName=qvector,targetNumHits=1} field is not an attribute", r);
}
@Test
public void testWrongAttributeType() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(simple,qvector);";
Tensor t = makeTensor(tt_dense_dvector_3);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=simple,queryTensorName=qvector,targetNumHits=1} field is not a tensor", r);
}
@Test
public void testSparseTensor() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(sparse,qvector);";
Tensor t = makeTensor(tt_sparse_vector_x);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=sparse,queryTensorName=qvector,targetNumHits=1} tensor type tensor(x{}) is not a dense vector", r);
}
@Test
public void testMatrix() {
String q = "select * from sources * where [{\"targetNumHits\":1}]nearestNeighbor(matrix,qvector);";
Tensor t = makeMatrix(tt_dense_matrix_xy);
Result r = doSearch(searcher, q, t);
assertErrMsg("NEAREST_NEIGHBOR {field=matrix,queryTensorName=qvector,targetNumHits=1} tensor type tensor(x[3],y[1]) is not a dense vector", r);
}
private static Result doSearch(ValidateNearestNeighborSearcher searcher, String yqlQuery, Object qTensor) {
QueryTree queryTree = new YqlParser(new ParserEnvironment()).parse(new Parsable().setQuery(yqlQuery));
Query query = new Query();
query.getModel().getQueryTree().setRoot(queryTree.getRoot());
query.getRanking().getProperties().put("qvector", qTensor);
TreeMap<String, List<String>> masterClusters = new TreeMap<>();
masterClusters.put("cluster", Arrays.asList("document"));
SearchDefinition searchDefinition = new SearchDefinition("document");
Map<String, SearchDefinition> searchDefinitionMap = new HashMap<>();
searchDefinitionMap.put("document", searchDefinition);
IndexFacts indexFacts = new IndexFacts(new IndexModel(masterClusters, searchDefinitionMap, searchDefinition));
Execution.Context context = new Execution.Context(null, indexFacts, null, new RendererRegistry(MoreExecutors.directExecutor()), new SimpleLinguistics());
return new Execution(searcher, context).search(query);
}
}
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