result = list.stream().map(RbaseTableDispatch::getTableName).collect(Collectors.toList())解释一下这段代码

这段代码使用了Java8的Stream API来操作一个名为`list`的列表，具体解释如下：

1. `list.stream()`：将列表转换为Stream对象，以便进行后续的Stream操作。

2. `map(RbaseTableDispatch::getTableName)`：对Stream中的每一个元素，都调用其`getTableName()`方法，将返回值映射为一个新的Stream。

3. `collect(Collectors.toList())`：将Stream中的元素收集到List对象中。

综上，这段代码的作用是将列表`list`中每个元素的`tableName`属性提取出来，然后将这些属性值组成一个新的列表返回。其中，`RbaseTableDispatch::getTableName`可以写成`x -> x.getTableName()`的形式，表示对Stream中的每一个元素x都调用`getTableName()`方法。

相关问题

优化以下代码： private List<ErrorOutputFileVo> getErrorDataFileList(Long planId, String datasourceName, Long ruleTemplateId, String columnName, String tableName) { List<ErrorOutputFileVo> errorOutputFiles = new ArrayList<>(); // 按规则过滤taskId List<DataQualityPlanRelationEntity> dataQualityPlanRelationEntities = dataQualityPlanRelationService.relationInfoSearch(planId) .stream().filter(dataQualityPlanRelationEntity -> ruleTemplateId.equals(dataQualityPlanRelationEntity.getRuleId()) && columnName.equalsIgnoreCase(dataQualityPlanRelationEntity.getColumnName()) && tableName.equalsIgnoreCase(dataQualityPlanRelationEntity.getTableName())).collect(Collectors.toList()); if (CollectionUtil.isEmpty(dataQualityPlanRelationEntities)) { return errorOutputFiles; } Long datasourceId = getDatasourceId(datasourceName, dataQualityPlanRelationEntities); List<String> taskIds = dataQualityPlanRelationEntities.stream() .filter(relationInfo -> Objects.equals(datasourceId, relationInfo.getDatasourceId())) .map(DataQualityPlanRelationEntity::getTaskId) .map(String::valueOf).distinct() .collect(Collectors.toList()); // 获取质检结果 List<DqExecuteResult> dqExecuteResults = getDqExecuteResults(taskIds); if (CollectionUtil.isEmpty(dqExecuteResults)) { return errorOutputFiles; } for (DqExecuteResult dqExecuteResult : dqExecuteResults) { String errorOutputPath = dqExecuteResult.getErrorOutputPath(); Path path = new Path(errorOutputPath); R<List<String>> getFileResult = resourceClient.getFilesAtPath(path.toUri().getPath()); if (null != getFileResult && getFileResult.isSuccess()) { for (String currentPath : getFileResult.getData()) { if(StringUtil.isBlank(currentPath)){ continue; } String fileName = String.format("%s-%s-%s", tableName, columnName, dqExecuteResult.getTaskInstanceId()); String originFileName = new Path(currentPath).getName(); String[] originFileSplit = originFileName.split("-"); if(originFileSplit.length > 2){ fileName += String.format("%s-%s", originFileSplit[0], originFileSplit[1]); } // 将文件信息添加到列表 errorOutputFiles.add( ErrorOutputFileVo .builder() .datasourceId(datasourceId) .tableName(tableName) .fieldName(columnName) .fileName(fileName) .originFileName(originFileName) .taskDefinitionCode(dqExecuteResult.getTaskDefinitionCode()) .taskInstanceId(dqExecuteResult.getTaskInstanceId()).build()); } } } return errorOutputFiles; }

可以将代码优化为：

private List<ErrorOutputFileVo> getErrorDataFileList(Long planId, String datasourceName, Long ruleTemplateId, String columnName, String tableName) {
    List<ErrorOutputFileVo> errorOutputFiles = new ArrayList<>();
    // 按规则过滤taskId
    List<DataQualityPlanRelationEntity> dataQualityPlanRelationEntities = dataQualityPlanRelationService.relationInfoSearch(planId)
            .stream().filter(dataQualityPlanRelationEntity -> ruleTemplateId.equals(dataQualityPlanRelationEntity.getRuleId()) &&
                    columnName.equalsIgnoreCase(dataQualityPlanRelationEntity.getColumnName()) &&
                    tableName.equalsIgnoreCase(dataQualityPlanRelationEntity.getTableName()))
            .collect(Collectors.toList());
    if (CollectionUtil.isEmpty(dataQualityPlanRelationEntities)) {
        return errorOutputFiles;
    }

    Long datasourceId = getDatasourceId(datasourceName, dataQualityPlanRelationEntities);
    List<String> taskIds = dataQualityPlanRelationEntities.stream()
            .filter(relationInfo -> Objects.equals(datasourceId, relationInfo.getDatasourceId()))
            .map(DataQualityPlanRelationEntity::getTaskId)
            .map(String::valueOf)
            .distinct()
            .collect(Collectors.toList());

    // 获取质检结果
    List<DqExecuteResult> dqExecuteResults = getDqExecuteResults(taskIds);
    if (CollectionUtil.isEmpty(dqExecuteResults)) {
        return errorOutputFiles;
    }

    for (DqExecuteResult dqExecuteResult : dqExecuteResults) {
        String errorOutputPath = dqExecuteResult.getErrorOutputPath();
        Path path = new Path(errorOutputPath);
        R<List<String>> getFileResult = resourceClient.getFilesAtPath(path.toUri().getPath());

        if (getFileResult == null || !getFileResult.isSuccess()) {
            continue;
        }

        for (String currentPath : getFileResult.getData()) {
            if (StringUtil.isBlank(currentPath)) {
                continue;
            }

            String fileName = String.format("%s-%s-%s", tableName, columnName, dqExecuteResult.getTaskInstanceId());
            String originFileName = new Path(currentPath).getName();
            String[] originFileSplit = originFileName.split("-");

            if (originFileSplit.length > 2) {
                fileName += String.format("%s-%s", originFileSplit[0], originFileSplit[1]);
            }

            // 将文件信息添加到列表
            errorOutputFiles.add(
                    ErrorOutputFileVo.builder()
                            .datasourceId(datasourceId)
                            .tableName(tableName)
                            .fieldName(columnName)
                            .fileName(fileName)
                            .originFileName(originFileName)
                            .taskDefinitionCode(dqExecuteResult.getTaskDefinitionCode())
                            .taskInstanceId(dqExecuteResult.getTaskInstanceId())
                            .build());
        }
    }

    return errorOutputFiles;
}

优化点如下：

1. 将代码按逻辑块划分，提高可读性。
2. 避免 `null` 引用和空指针异常，增加代码的健壮性。
3. 删除不必要的变量赋值，使代码更加简洁。
4. 使用 `continue` 语句避免嵌套代码块，提高代码可读性。

优化以下代码： public Map<String, List<String>> getUniquenessTableFieldList(Long planId, String datasourceName) { Map<String,List<String>> tableColumnTree = new HashMap<>(); // 按规则和字段过滤taskId List<DataQualityPlanRelationEntity> collect = dataQualityPlanRelationService.relationInfoSearch(planId) .stream() // 过滤出唯一性校验的规则 .filter(dataQualityPlanRelationEntity -> dataQualityPlanRelationEntity.getRuleTemplateId().equals(6L)) .collect(Collectors.toList()); for (DataQualityPlanRelationEntity dataQualityPlanRelationEntity : collect) { if(CollectionUtil.isEmpty(tableColumnTree.get(dataQualityPlanRelationEntity.getTableName()))){ List<String> columnList = new ArrayList<>(); columnList.add(dataQualityPlanRelationEntity.getColumnName()); tableColumnTree.put(dataQualityPlanRelationEntity.getTableName(), columnList); } else { List<String> columnList = tableColumnTree.get(dataQualityPlanRelationEntity.getTableName()); if(columnList.contains(dataQualityPlanRelationEntity.getColumnName())){ columnList.add(dataQualityPlanRelationEntity.getColumnName()); } } } return tableColumnTree; }

可以尝试使用 Java 8 的 Stream API 来优化代码，如下所示：

public Map<String, List<String>> getUniquenessTableFieldList(Long planId, String datasourceName) {
    List<DataQualityPlanRelationEntity> collect = dataQualityPlanRelationService.relationInfoSearch(planId)
            .stream()
            .filter(dataQualityPlanRelationEntity -> dataQualityPlanRelationEntity.getRuleTemplateId().equals(6L))
            .collect(Collectors.toList());

    return collect.stream().collect(Collectors.groupingBy(
            DataQualityPlanRelationEntity::getTableName,
            Collectors.mapping(DataQualityPlanRelationEntity::getColumnName, Collectors.toList())
    ));
}

这段代码使用了 `groupingBy` 方法来将数据按表名分组，然后使用 `mapping` 方法将每个表名对应的 `DataQualityPlanRelationEntity` 对象的 `columnName` 属性提取出来，最终得到每个表名对应的字段列表。这样就省去了手动循环构建 `Map` 对象的复杂度。