Java 通過RestHighLevelClient 使用ES的date_histogram 根據年月日做統計

只寫了後臺，前端請求帶上dateType給後臺，後端返回封裝了json字符串的map

GsonUtil.getJsonStringByObject()是封裝的Gson.toJson的方法

前端接受解析結果 並設置echatrs參數 即可完成圖表繪製

/**
 * 消息趨勢統計 dateType由前端傳遞 包括年月周
 * 按年則統計過去12個月
 * 按月則統計過去30天
 * 按周則統計過去7天
**/
public Map<String, String> msgTrendCount(String dateType) {
    //每個索引的時間field name 可能不同 根據索引設置
	String rangeField = "messageSendTime";
    //索引名
	String index = EsIndexName.TG_MESSAGE.getIndexName();
	return dateHistogram(rangeField, dateType, index);
}




private Map<String, String> dateHistogram(String rangeField, String dateType, String... indices) {
	Map<String, String> map = new HashMap<>(4);
	try {

		LocalDateTime now = LocalDateTime.now();
		DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd hh:mm:ss");
		String from;
		//extended bounds參數
		String boundsStart;
		String boundsEnd;
		String to = formatter.format(now);
		String format = "yyyy-MM-dd";
		//bounds的格式化類型需要和format相同
		DateTimeFormatter boundsFormatter = DateTimeFormatter.ofPattern(format);
		//間隔 年類型較爲特殊
		DateHistogramInterval interval = DateHistogramInterval.DAY;
		switch (dateType) {
			case "week": {
				from = formatter.format(now.minusDays(6));
				boundsStart = boundsFormatter.format(now.minusDays(6));
				boundsEnd = boundsFormatter.format(now);
				break;
			}
			case "year": {
				from = formatter.format(now.minusMonths(11));
				format = "yyyy-MM";
				boundsFormatter = DateTimeFormatter.ofPattern(format);
				interval = DateHistogramInterval.MONTH;
				boundsStart = boundsFormatter.format(now.minusMonths(11));
				boundsEnd = boundsFormatter.format(now);
				break;
			}
			case "month":
			default: {
				from = formatter.format(now.minusDays(29));
				boundsStart = boundsFormatter.format(now.minusDays(29));
				boundsEnd = boundsFormatter.format(now);
				break;
			}
		}

		//範圍查詢
		BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
		boolQueryBuilder.must(QueryBuilders.rangeQuery(rangeField).from(from).to(to));
		//dateHistogram
		AggregationBuilder aggregationBuilder = AggregationBuilders.dateHistogram("dateHistogram")//自定義名稱
				.dateHistogramInterval(interval)//設置間隔
				.minDocCount(0)//返回空桶
				.field(rangeField)//指定時間字段
				.format(format)//設定返回格式
				.extendedBounds(new ExtendedBounds(boundsStart, boundsEnd));//設定範圍

		SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
		//指定size爲0 不返回文檔 因爲只需要數量
		searchSourceBuilder.query(boolQueryBuilder).aggregation(aggregationBuilder).size(0);

		SearchRequest searchRequest = new SearchRequest();
		searchRequest.source(searchSourceBuilder);
		searchRequest.indices(indices);
		SearchResponse searchResponse = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
		Aggregation agg = searchResponse.getAggregations().get("dateHistogram");

		List<? extends Histogram.Bucket> buckets = ((Histogram) agg).getBuckets();
		List<String> dateList = new ArrayList<>(30);
		List<String> countList = new ArrayList<>(30);
		for (Histogram.Bucket bucket : buckets) {
			// maybe：如果不是年 則將key中的年份去掉
			dateList.add(bucket.getKeyAsString());
			countList.add(String.valueOf(bucket.getDocCount()));
		}
		map.put("chartTime", GsonUtil.getJsonStringByObject(dateList));
		map.put("chartCount", GsonUtil.getJsonStringByObject(countList));
	} catch (Exception e) {
		log.error("統計日期直方圖出錯：" + e.getMessage());
	}
	return map;
}

之前費勁寫的好多代碼來做這個統計，分別用日期去一天天的查數量，最近學習瞭解了es自帶的 date_histogram

完全契合需求，遂將原笨拙的代碼刪除改爲es的自帶聚合 (果然人還是要多讀書呀。。。)

速度上目前文檔數量不大，沒有差別，但預計隨着後期文檔數量增加，肯定是es的聚合更加高效。