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(improvement)(Chat)Optimize dimension recommendation logic and code structure #1706 (#1826)

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Co-authored-by: lxwcodemonkey
This commit is contained in:
LXW
2024-10-19 22:01:03 +08:00
committed by GitHub
parent 2250289c94
commit f196561d55
1 changed files with 12 additions and 21 deletions
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33
chat/server/src/main/java/com/tencent/supersonic/chat/server/processor/execute/DimensionRecommendProcessor.java
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@@ -8,16 +8,15 @@ import com.tencent.supersonic.common.util.ContextUtils;
import com.tencent.supersonic.headless.api.pojo.DataSetSchema;
import com.tencent.supersonic.headless.api.pojo.RelatedSchemaElement;
import com.tencent.supersonic.headless.api.pojo.SchemaElement;
import com.tencent.supersonic.headless.api.pojo.SchemaElementType;
import com.tencent.supersonic.headless.api.pojo.SemanticParseInfo;
import com.tencent.supersonic.headless.server.facade.service.SemanticLayerService;
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;
import org.springframework.util.CollectionUtils;
/**
* DimensionRecommendProcessor recommend some dimensions related to metrics based on configuration
@@ -38,8 +37,7 @@ public class DimensionRecommendProcessor implements ExecuteResultProcessor {
if (!firstMetric.isPresent()) {
return;
}
SchemaElement element = firstMetric.get();
List<SchemaElement> dimensionRecommended = getDimensions(element.getId(), dataSetId);
List<SchemaElement> dimensionRecommended = getDimensions(firstMetric.get().getId(), dataSetId);
queryResult.setRecommendedDimensions(dimensionRecommended);
}
@@ -49,23 +47,16 @@ public class DimensionRecommendProcessor implements ExecuteResultProcessor {
if (dataSetSchema == null) {
return Lists.newArrayList();
}
List<Long> drillDownDimensions = Lists.newArrayList();
Set<SchemaElement> metricElements = dataSetSchema.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());
}
SchemaElement metric = dataSetSchema.getElement(SchemaElementType.METRIC, metricId);
if (!CollectionUtils.isEmpty(metric.getRelatedSchemaElements())) {
List<Long> drillDownDimensions = metric.getRelatedSchemaElements().stream()
.map(RelatedSchemaElement::getDimensionId).collect(Collectors.toList());
return dataSetSchema.getDimensions().stream()
.filter(dim -> filterDimension(drillDownDimensions, dim))
.sorted(Comparator.comparing(SchemaElement::getUseCnt).reversed())
.limit(recommend_dimension_size).collect(Collectors.toList());
}
final List<Long> drillDownDimensionsFinal = drillDownDimensions;
return dataSetSchema.getDimensions().stream()
.filter(dim -> filterDimension(drillDownDimensionsFinal, dim))
.sorted(Comparator.comparing(SchemaElement::getUseCnt).reversed())
.limit(recommend_dimension_size).collect(Collectors.toList());
return Lists.newArrayList();
}
private boolean filterDimension(List<Long> drillDownDimensions, SchemaElement dimension) {