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(improvement)(chat) Rename DrillDownDimensionProcessor to DimensionRecommendProcessor (#512)

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Co-authored-by: jolunoluo
This commit is contained in:
LXW
2023-12-15 11:48:41 +08:00
committed by GitHub
parent e9a479e2df
commit e6eac03ec6
2 changed files with 1 additions and 74 deletions
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2
chat/core/src/main/java/com/tencent/supersonic/chat/processor/execute/DimensionRecommendProcessor.java
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@@ -20,7 +20,7 @@ import java.util.Set;
import java.util.stream.Collectors;
/**
* DrillDownDimensionProcessor obtains metric recommended dimensions
* DimensionRecommendProcessor obtains metric recommended dimensions
*/
public class DimensionRecommendProcessor implements ExecuteResultProcessor {

73
chat/core/src/main/java/com/tencent/supersonic/chat/processor/execute/DrillDownDimensionProcessor.java
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@@ -1,73 +0,0 @@
package com.tencent.supersonic.chat.processor.execute;
import com.tencent.supersonic.chat.api.pojo.ModelSchema;
import com.tencent.supersonic.chat.api.pojo.RelatedSchemaElement;
import com.tencent.supersonic.chat.api.pojo.SchemaElement;
import com.tencent.supersonic.chat.api.pojo.SemanticParseInfo;
import com.tencent.supersonic.chat.api.pojo.request.ExecuteQueryReq;
import com.tencent.supersonic.chat.api.pojo.response.QueryResult;
import com.tencent.supersonic.chat.service.SemanticService;
import com.tencent.supersonic.common.pojo.enums.QueryType;
import com.tencent.supersonic.common.util.ContextUtils;
import org.apache.commons.compress.utils.Lists;
import org.springframework.util.CollectionUtils;
import java.util.Comparator;
import java.util.List;
import java.util.Objects;
import java.util.Optional;
import java.util.Set;
import java.util.stream.Collectors;
/**
* DrillDownDimensionProcessor obtains metric recommended dimensions based on setting
*/
public class DrillDownDimensionProcessor implements ExecuteResultProcessor {
private static final int recommend_dimension_size = 5;
@Override
public void process(QueryResult queryResult, SemanticParseInfo semanticParseInfo, ExecuteQueryReq queryReq) {
if (!QueryType.METRIC.equals(semanticParseInfo.getQueryType())
|| CollectionUtils.isEmpty(semanticParseInfo.getMetrics())) {
return;
}
SchemaElement element = semanticParseInfo.getMetrics().iterator().next();
List<SchemaElement> dimensionRecommend = getDimensions(element.getId(), element.getModel());
queryResult.setRecommendDimensions(dimensionRecommend);
}
private List<SchemaElement> getDimensions(Long metricId, Long modelId) {
SemanticService semanticService = ContextUtils.getBean(SemanticService.class);
ModelSchema modelSchema = semanticService.getModelSchema(modelId);
List<Long> drillDownDimensions = Lists.newArrayList();
Set<SchemaElement> metricElements = modelSchema.getMetrics();
if (!CollectionUtils.isEmpty(metricElements)) {
Optional<SchemaElement> metric = metricElements.stream().filter(schemaElement ->
metricId.equals(schemaElement.getId())
&& !CollectionUtils.isEmpty(schemaElement.getRelatedSchemaElements()))
.findFirst();
if (metric.isPresent()) {
drillDownDimensions = metric.get().getRelatedSchemaElements().stream()
.map(RelatedSchemaElement::getDimensionId).collect(Collectors.toList());
}
}
final List<Long> drillDownDimensionsFinal = drillDownDimensions;
return modelSchema.getDimensions().stream()
.filter(dim -> filterDimension(drillDownDimensionsFinal, dim))
.sorted(Comparator.comparing(SchemaElement::getUseCnt).reversed())
.limit(recommend_dimension_size)
.collect(Collectors.toList());
}
private boolean filterDimension(List<Long> drillDownDimensions, SchemaElement dimension) {
if (Objects.isNull(dimension)) {
return false;
}
if (!CollectionUtils.isEmpty(drillDownDimensions)) {
return drillDownDimensions.contains(dimension.getId());
}
return Objects.nonNull(dimension.getUseCnt());
}
}