ES 时间聚合

原创已于 2022-03-24 18:56:14 修改 · 1.2k 阅读

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于 2022-03-24 18:54:06 首次发布

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本文档展示了如何使用Elasticsearch进行时间序列聚合，以获取每月汽车销售的数量。通过创建索引、插入样本数据，然后执行搜索请求，我们得到了从2014年1月至12月每个月的销售统计，揭示了各个月份的销售情况，例如2014年11月售出了2辆汽车。

ES 时间聚合

数据准备

PUT cars
{
  "mappings": {
      "transactions": {
        "properties": {
          "color": {
            "type": "keyword"
          },
          "make": {
            "type": "keyword"
          },
          "price": {
            "type": "long"
          },
          "sold": {
            "type": "date"
          }
        }
      }
    }
}

POST /cars/transactions/_bulk
{ "index": {}}
{ "price" : 10000, "color" : "red", "make" : "honda", "sold" : "2014-10-28" }
{ "index": {}}
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "index": {}}
{ "price" : 30000, "color" : "green", "make" : "ford", "sold" : "2014-05-18" }
{ "index": {}}
{ "price" : 15000, "color" : "blue", "make" : "toyota", "sold" : "2014-07-02" }
{ "index": {}}
{ "price" : 12000, "color" : "green", "make" : "toyota", "sold" : "2014-08-19" }
{ "index": {}}
{ "price" : 20000, "color" : "red", "make" : "honda", "sold" : "2014-11-05" }
{ "index": {}}
{ "price" : 80000, "color" : "red", "make" : "bmw", "sold" : "2014-01-01" }
{ "index": {}}
{ "price" : 25000, "color" : "blue", "make" : "ford", "sold" : "2014-02-12" }

使用

需求：每月销售多少台汽车？

GET /cars/transactions/_search
{
   "size" : 0,
   "aggs": {
      "sales": {
         "date_histogram": {
            "field": "sold",
            "interval": "month", 
            "format": "yyyy-MM-dd",
            "min_doc_count" : 0, 
            "extended_bounds" : { 
                "min" : "2014-01-01",
                "max" : "2014-12-31"
            }
         }
      }
   }
}

返回结果
"aggregations": {
    "sales": {
      "buckets": [
        {
          "key_as_string": "2014-01-01",
          "key": 1388534400000,
          "doc_count": 1
        },
        {
          "key_as_string": "2014-02-01",
          "key": 1391212800000,
          "doc_count": 1
        },
        {
          "key_as_string": "2014-03-01",
          "key": 1393632000000,
          "doc_count": 0
        },
        {
          "key_as_string": "2014-04-01",
          "key": 1396310400000,
          "doc_count": 0
        },
        {
          "key_as_string": "2014-05-01",
          "key": 1398902400000,
          "doc_count": 1
        },
        {
          "key_as_string": "2014-06-01",
          "key": 1401580800000,
          "doc_count": 0
        },
        {
          "key_as_string": "2014-07-01",
          "key": 1404172800000,
          "doc_count": 1
        },
        {
          "key_as_string": "2014-08-01",
          "key": 1406851200000,
          "doc_count": 1
        },
        {
          "key_as_string": "2014-09-01",
          "key": 1409529600000,
          "doc_count": 0
        },
        {
          "key_as_string": "2014-10-01",
          "key": 1412121600000,
          "doc_count": 1
        },
        {
          "key_as_string": "2014-11-01",
          "key": 1414800000000,
          "doc_count": 2
        },
        {
          "key_as_string": "2014-12-01",
          "key": 1417392000000,
          "doc_count": 0
        }
      ]
    }
  }

interval以月为间隔
format对日期进行格式化
min_doc_count强制返回所有 buckets，即使 buckets 可能为空
extended_bounds限定日期的最小范围值和最大范围值

@Test
public void test06(){
    DateHistogramAggregationBuilder dateHistogramAggregationBuilder = AggregationBuilders.dateHistogram("popular_sold").field("sold")
    	    .dateHistogramInterval(DateHistogramInterval.MONTH)
            .minDocCount(0)
            .format("yyyy-MM-dd")
            .extendedBounds(new ExtendedBounds("2014-01-01", "2014-12-31"));
    SearchResponse searchResponse = elasticsearchTemplate.getClient().prepareSearch("cars")
            .setTypes("transactions")
            .addAggregation(dateHistogramAggregationBuilder)
            .execute()
            .actionGet();
    InternalDateHistogram internalDateHistogram = searchResponse.getAggregations().get("popular_sold");
    List<InternalDateHistogram.Bucket> buckets = internalDateHistogram.getBuckets();
    for (InternalDateHistogram.Bucket bucket : buckets){
        String keyAsString = bucket.getKeyAsString();
        long docCount = bucket.getDocCount();
        System.out.println(keyAsString+"---"+docCount);
    }
}

返回结果
2014-01-01---1
2014-02-01---1
2014-03-01---0
2014-04-01---0
2014-05-01---1
2014-06-01---0
2014-07-01---1
2014-08-01---1
2014-09-01---0
2014-10-01---1
2014-11-01---2
2014-12-01---0