MongoDB中的嵌套List操作

前言

MongoDB区别Mysql的地方，就是MongoDB支持文档嵌套，比如最近业务中就有一个在音频转写结果中进行对话场景，一个音频中对应多轮对话，这些音频数据和对话信息就存储在MongoDB中文档中。集合结构大致如下

{
    "_id":23424234234324234,
	"audioId": 2689944,
	"contextId": "cht000d24ab@dx187d1168a449a4b540",
	"dialogues": [{
		"ask": "今天是礼拜天？",
		"answer": "是的",
		"createTime": 1697356990966
	}, {
		"ask": "你也要加油哈",
		"answer": "奥利给！",
		"createTime": 1697378011483
	}, {
		"ask": "下周见",
		"answer": "拜拜！",
		"createTime": 1697378072063
	}]
}

下面简单介绍几个业务中用到的简单操作。

查询嵌套List的长度大小

    public Integer getDialoguesSize(Long audioId) {
        Integer datasSize = 0;
        List group = Arrays.asList(
                new Document("$match",
                        new Document("audioId",
                                new Document("$eq", audioId)
                        )
                ), new Document("$match",
                        new Document("dialogues",
                                new Document("$exists", true)
                        )
                ), new Document("$project",
                        new Document("datasSize",
                                new Document("$size", "$dialogues"))
                )
        );
        AggregateIterable aggregate = generalCollection.aggregate(group);
        Document document = aggregate.first();
        if (document != null) {
            datasSize = (Integer) document.get("datasSize");
        }
        return datasSize;
    }

根据嵌套List中属性查询

下面的代码主要查询指定audioId中的dialogues集合中小于createTime,并且根据limit分页查询，这里用到了MongoDB中的Aggregates和unwind来进行聚合查询,具体使用细节，可以参见MongoDB官方文档

    public AIDialoguesResultDTO queryAiResult(Long audioId, Long createTime, Integer limit) {
        AIDialoguesResultDTO aiDialoguesResultDTO = new AIDialoguesResultDTO();

        List pipeline = Arrays.asList(
                Aggregates.match(Filters.eq("audioId", audioId)),
                Aggregates.unwind("$dialogues"),
                Aggregates.match(Filters.lt("dialogues.createTime", createTime)),
                Aggregates.sort(Sorts.descending("dialogues.createTime")),
                Aggregates.limit(limit)
        );

        AggregateIterable aggregate = generalCollection.aggregate(pipeline);
        List aiDialoguesResultList = new ArrayList<>();
        String contextId = Constant.EMPTY_STR;
        for (Document document : aggregate) {
            AIDialoguesResult aiDialoguesResult = new AIDialoguesResult();
            List key = Collections.singletonList("dialogues");

            aiDialoguesResult.setAnswer(document.getEmbedded(key, Document.class).getString("answer"));
            aiDialoguesResult.setAsk(document.getEmbedded(key, Document.class).getString("ask"));
            aiDialoguesResult.setCreateTime(document.getEmbedded(key, Document.class).getLong("createTime"));
            aiDialoguesResultList.add(aiDialoguesResult);
            contextId = document.getString("contextId");
        }

        if (!CollectionUtils.isEmpty(aiDialoguesResultList)) {
            aiDialoguesResultList = aiDialoguesResultList.stream().sorted(Comparator.comparingLong(AIDialoguesResult::getCreateTime)).collect(Collectors.toList());
        }

        aiDialoguesResultDTO.setCount(aiDialoguesResultList.size());
        aiDialoguesResultDTO.setContextId(contextId);
        aiDialoguesResultDTO.setResult(aiDialoguesResultList);
        return aiDialoguesResultDTO;
    }

当然，我们还有一种比较简单的写法

    public AIDialoguesResultDTO queryAiResultBackupVersion(Long audioId, Long createTime, Integer limit) {
        Bson query = and(eq("audioId", audioId));
        AITextResult aiTextResult = mongoDao.findSingle(query, AITextResult.class);
        AIDialoguesResultDTO aiDialoguesResultDTO = new AIDialoguesResultDTO();
        if (Objects.isNull(aiTextResult)) {
            aiDialoguesResultDTO.setResult(Collections.emptyList());
            aiDialoguesResultDTO.setCount(0);
            aiDialoguesResultDTO.setContextId("");
        }
        List aiDialoguesResultList = aiTextResult.getDialogues();

        if (CollectionUtils.isEmpty(aiDialoguesResultList)) {
            return aiDialoguesResultDTO;
        }

        Long finalCreateTime = createTime;
        List afterFilterAiDialoguesResultList =
                aiDialoguesResultList.stream().filter(t -> t.getCreateTime()
                                < finalCreateTime).sorted(Comparator.comparingLong(AIDialoguesResult::getCreateTime).reversed())
                        .limit(limit).collect(Collectors.toList());

        if (CollectionUtils.isEmpty(afterFilterAiDialoguesResultList)) {
            aiDialoguesResultDTO.setCount(0);
        } else {
            aiDialoguesResultDTO.setCount(afterFilterAiDialoguesResultList.size());
        }
        afterFilterAiDialoguesResultList = afterFilterAiDialoguesResultList.
                stream().sorted(Comparator.comparingLong(AIDialoguesResult::getCreateTime)).collect(Collectors.toList());
        aiDialoguesResultDTO.setResult(afterFilterAiDialoguesResultList);
        aiDialoguesResultDTO.setContextId(aiTextResult.getContextId());
        return aiDialoguesResultDTO;
    }

上面这种写法比较直接，就是直接audioId进行匹配查询， 然后将当前文档中的dialogues全部加载到内存中，然后在内存中进行排序，分页返回，显然如果dialogues集合长度很大，对内存占用会比较高。

嵌套List的增量追加

对于dialogues数组，如果我们要向dialogues追加元素，我们可以把audioId对应的dialogues全部取出来，然后在List后面追加一个元素，大致代码如下

    public void saveAiResult(SaveAIResultDTO saveAIResultDTO) {
        Long audioId = saveAIResultDTO.getAudioId();
        Bson filter = Filters.eq("audioId", audioId);
        AITextResult aiTextResult = mongoDao.findSingle(filter, AITextResult.class);
        if (Objects.isNull(aiTextResult)) {
            aiTextResult = AITextResult.buildAiTextResult(saveAIResultDTO);
            mongoDao.saveOrUpdate(aiTextResult);
            return;
        }
        List aiDialoguesResults = aiTextResult.getDialogues();
        AIDialoguesResult aiDialoguesResult = new AIDialoguesResult();
        aiDialoguesResult.setCreateTime(new Date().getTime());
        aiDialoguesResult.setAsk(saveAIResultDTO.getAsk());
        aiDialoguesResult.setAnswer(saveAIResultDTO.getAnswer());
        aiDialoguesResults.add(aiDialoguesResult);
        aiTextResult.setDialogues(aiDialoguesResults);
        mongoDao.saveOrUpdate(aiTextResult);
    }

上面这种写法本身没有什么问题，但是如果dialogues集合大小比较大，每次追加都将dialogues全部取出来进行追加操作，可能比较占用内存，我们可以利用MongoDB中的push操作，直接追加

    public void saveAiResultIncremental(SaveAIResultDTO saveAIResultDTO) {
        Long audioId = saveAIResultDTO.getAudioId();
        Document query = new Document("audioId", audioId);
        Bson projection = Projections.fields(Projections.include("contextId"), Projections.excludeId());
        FindIterable result = generalCollection.find(query).projection(projection);
        AITextResult aiTextResult;

        if (!result.iterator().hasNext()) {
            aiTextResult = AITextResult.buildAiTextResult(saveAIResultDTO);
            mongoDao.saveOrUpdate(aiTextResult);
            return;
        }
     
        AIDialoguesResult aiDialoguesResult = new AIDialoguesResult();
        aiDialoguesResult.setCreateTime(new Date().getTime());
        aiDialoguesResult.setAsk(saveAIResultDTO.getAsk());
        aiDialoguesResult.setAnswer(saveAIResultDTO.getAnswer());
        Bson update = push("dialogues", aiDialoguesResult);
        Bson filter = Filters.eq("audioId", audioId);
        generalCollection.updateOne(filter, update);
    }

总结

既然选择了MongoDB,就不能继续沿用Mysql的查询风格，要学会利用MongoDB的特性，否则往往达不到预期效果。