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// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.search.searchers;
import com.yahoo.prelude.query.Item;
import com.yahoo.prelude.query.NearestNeighborItem;
import com.yahoo.prelude.query.ToolBox;
import com.yahoo.search.Query;
import com.yahoo.search.Result;
import com.yahoo.search.Searcher;
import com.yahoo.search.grouping.vespa.GroupingExecutor;
import com.yahoo.search.query.ranking.RankProperties;
import com.yahoo.search.result.ErrorMessage;
import com.yahoo.search.searchchain.Execution;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import com.yahoo.vespa.config.search.AttributesConfig;
import com.yahoo.yolean.chain.Before;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Optional;
/**
* Validates any NearestNeighborItem query items.
*
* @author arnej
*/
@Before(GroupingExecutor.COMPONENT_NAME) // Must happen before query.prepare()
public class ValidateNearestNeighborSearcher extends Searcher {
private final Map<String, List<TensorType>> validAttributes = new HashMap<>();
public ValidateNearestNeighborSearcher(AttributesConfig attributesConfig) {
for (AttributesConfig.Attribute a : attributesConfig.attribute()) {
if (! validAttributes.containsKey(a.name())) {
validAttributes.put(a.name(), new ArrayList<>());
}
if (a.datatype() == AttributesConfig.Attribute.Datatype.TENSOR) {
TensorType tt = TensorType.fromSpec(a.tensortype());
validAttributes.get(a.name()).add(tt);
}
}
}
@Override
public Result search(Query query, Execution execution) {
Optional<ErrorMessage> e = validate(query);
return e.isEmpty() ? execution.search(query) : new Result(query, e.get());
}
private Optional<ErrorMessage> validate(Query query) {
NNVisitor visitor = new NNVisitor(query.getRanking().getProperties(), validAttributes, query);
ToolBox.visit(visitor, query.getModel().getQueryTree().getRoot());
return visitor.errorMessage;
}
private static class NNVisitor extends ToolBox.QueryVisitor {
public Optional<ErrorMessage> errorMessage = Optional.empty();
private final Map<String, List<TensorType>> validAttributes;
private final Query query;
public NNVisitor(RankProperties rankProperties, Map<String, List<TensorType>> validAttributes, Query query) {
this.validAttributes = validAttributes;
this.query = query;
}
@Override
public boolean visit(Item item) {
if (item instanceof NearestNeighborItem) {
String error = validate((NearestNeighborItem)item);
if (error != null)
errorMessage = Optional.of(ErrorMessage.createIllegalQuery(error));
}
return true;
}
private static boolean isCompatible(TensorType fieldTensorType, TensorType queryTensorType) {
// Precondition: isTensorTypeThatSupportsHnswIndex(fieldTensorType)
var queryDimensions = queryTensorType.dimensions();
if (queryDimensions.size() == 1) {
var queryDimension = queryDimensions.get(0);
var fieldDimensions = fieldTensorType.dimensions();
for (var fieldDimension : fieldDimensions) {
if (fieldDimension.isIndexed()) {
return fieldDimension.equals(queryDimension);
}
}
}
return false;
}
private static boolean badQueryTensorType(TensorType queryTensorType) {
var queryDimensions = queryTensorType.dimensions();
if (queryDimensions.size() != 1) {
return true;
}
var dim = queryDimensions.get(0);
return ! dim.isIndexed();
}
private static boolean isTensorTypeThatSupportsHnswIndex(TensorType tt) {
List<TensorType.Dimension> dims = tt.dimensions();
if (dims.size() == 1) {
return dims.get(0).isIndexed();
}
if (dims.size() == 2) {
var dims0 = dims.get(0);
var dims1 = dims.get(1);
return ((dims0.isMapped() && dims1.isIndexed()) || (dims0.isIndexed() && dims1.isMapped()));
}
return false;
}
/** Returns an error message if this is invalid, or null if it is valid */
private String validate(NearestNeighborItem item) {
if (item.getTargetNumHits() < 1)
return item + " has invalid targetHits " + item.getTargetNumHits() + ": Must be >= 1";
String queryFeatureName = "query(" + item.getQueryTensorName() + ")";
Optional<Tensor> queryTensor = query.getRanking().getFeatures().getTensor(queryFeatureName);
if (queryTensor.isEmpty())
return item + " requires a tensor rank feature named '" + queryFeatureName + "' but this is not present";
if (badQueryTensorType(queryTensor.get().type())) {
return item + " tensor " + queryFeatureName + " must have exactly 1, indexed dimension, but was: " + queryTensor.get().type();
}
if ( ! validAttributes.containsKey(item.getIndexName())) {
return item + " field is not an attribute";
}
List<TensorType> allTensorTypes = validAttributes.get(item.getIndexName());
for (TensorType fieldType : allTensorTypes) {
if (isTensorTypeThatSupportsHnswIndex(fieldType) && isCompatible(fieldType, queryTensor.get().type())) {
return null;
}
}
for (TensorType fieldType : allTensorTypes) {
if (isTensorTypeThatSupportsHnswIndex(fieldType) && ! isCompatible(fieldType, queryTensor.get().type())) {
return item + " field type " + fieldType + " does not match query type " + queryTensor.get().type();
}
}
for (TensorType fieldType : allTensorTypes) {
if (! isTensorTypeThatSupportsHnswIndex(fieldType)) {
return item + " field type " + fieldType + " is not supported by nearest neighbor searcher";
}
}
return item + " field is not a tensor";
}
@Override
public void onExit() {}
}
}
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