feat(dataset): 实现数据集模型配置中的全量维度指标扩展功能
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- 实现 expandIncludesAllModels 方法处理全量维度指标映射
- 根据模型ID分组收集维度和指标并合并到配置中
- 将 includesAll 标志重置为 false 避免重复扩展
- 确保在线状态的维度和指标被正确包含到数据集中
This commit is contained in:
jerryjzhang
2026-05-07 15:51:57 +08:00
parent 20cd98332c
commit 3752543921

View File

@@ -13,6 +13,7 @@ import com.tencent.supersonic.common.pojo.enums.TypeEnums;
import com.tencent.supersonic.common.pojo.exception.InvalidArgumentException;
import com.tencent.supersonic.common.util.BeanMapper;
import com.tencent.supersonic.headless.api.pojo.DataSetDetail;
import com.tencent.supersonic.headless.api.pojo.DataSetModelConfig;
import com.tencent.supersonic.headless.api.pojo.MetaFilter;
import com.tencent.supersonic.headless.api.pojo.QueryConfig;
import com.tencent.supersonic.headless.api.pojo.request.*;
@@ -52,6 +53,9 @@ public class DataSetServiceImpl extends ServiceImpl<DataSetDOMapper, DataSetDO>
@Autowired
private MetricService metricService;
@Autowired
private ModelService modelService;
@Override
public DataSetResp save(DataSetReq dataSetReq, User user) {
dataSetReq.createdBy(user.getName());
@@ -77,7 +81,13 @@ public class DataSetServiceImpl extends ServiceImpl<DataSetDOMapper, DataSetDO>
@Override
public DataSetResp getDataSet(Long id) {
DataSetDO dataSetDO = getById(id);
return convert(dataSetDO);
DataSetResp dataSetResp = convert(dataSetDO);
if (dataSetResp.getDataSetDetail() != null) {
expandIncludesAllModels(dataSetResp);
}
return dataSetResp;
}
@Override
@@ -273,6 +283,59 @@ public class DataSetServiceImpl extends ServiceImpl<DataSetDOMapper, DataSetDO>
.map(Object::toString).collect(Collectors.toList());
}
private void expandIncludesAllModels(DataSetResp dataSetResp) {
List<DataSetModelConfig> configs = dataSetResp.getDataSetDetail().getDataSetModelConfigs();
if (CollectionUtils.isEmpty(configs)) {
return;
}
Set<Long> includeAllModelIds = configs.stream()
.filter(DataSetModelConfig::getIncludesAll)
.map(DataSetModelConfig::getId)
.collect(Collectors.toSet());
if (CollectionUtils.isEmpty(includeAllModelIds)) {
return;
}
MetaFilter metaFilter = new MetaFilter();
metaFilter.setModelIds(new ArrayList<>(includeAllModelIds));
metaFilter.setStatus(StatusEnum.ONLINE.getCode());
List<DimensionResp> allDimensions = dimensionService.getDimensions(metaFilter);
List<MetricResp> allMetrics = metricService.getMetrics(metaFilter);
Map<Long, List<Long>> modelDimensionMap = allDimensions.stream()
.collect(Collectors.groupingBy(
DimensionResp::getModelId,
Collectors.mapping(DimensionResp::getId, Collectors.toList())
));
Map<Long, List<Long>> modelMetricMap = allMetrics.stream()
.collect(Collectors.groupingBy(
MetricResp::getModelId,
Collectors.mapping(MetricResp::getId, Collectors.toList())
));
for (DataSetModelConfig config : configs) {
if (Boolean.TRUE.equals(config.getIncludesAll())) {
Long modelId = config.getId();
List<Long> modelDimensions = modelDimensionMap.getOrDefault(modelId, Lists.newArrayList());
Set<Long> existingDimensions = new HashSet<>(config.getDimensions());
existingDimensions.addAll(modelDimensions);
config.setDimensions(new ArrayList<>(existingDimensions));
List<Long> modelMetrics = modelMetricMap.getOrDefault(modelId, Lists.newArrayList());
Set<Long> existingMetrics = new HashSet<>(config.getMetrics());
existingMetrics.addAll(modelMetrics);
config.setMetrics(new ArrayList<>(existingMetrics));
config.setIncludesAll(false);
}
}
}
public Long getDataSetIdFromSql(String sql, User user) {
List<DataSetResp> dataSets = null;
try {