Elasticsearch-89-针对nested object的聚合分析案例

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对于nested object里面的数据,如何做聚合分析呢? 以上文的数据作为背景 来看两个案例

案例一

需求: 按照评论日期进行划分bucket,拿到每个月评论的stars的平均值
请求

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GET /website/blogs/_search
{
  "size": 0,
  "aggs": {
    "comments_path": {
      "nested": {
        "path": "comments"
      },
      "aggs": {
        "group_by_comments_date": {
          "date_histogram": {
            "field": "comments.date",
            "interval": "month",
            "format": "yyyy-MM"
          },
          "aggs": {
            "avg_stars": {
              "avg": {
                "field": "comments.stars"
              }
            }
          }
        }
      }
    }
  }
}

返回值:

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{
  "took": 7,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "comments_path": {
      "doc_count": 2,
      "group_by_comments_date": {
        "buckets": [
          {
            "key_as_string": "2016-09",
            "key": 1472688000000,
            "doc_count": 1,
            "avg_stars": {
              "value": 4
            }
          },
          {
            "key_as_string": "2016-10",
            "key": 1475280000000,
            "doc_count": 1,
            "avg_stars": {
              "value": 5
            }
          }
        ]
      }
    }
  }
}

看一下请求,第一个aggs,设置nested的path,然后第二个aggs是根据日期按月划分bucket的,第三个aggs是用来计算平均数的

案例二

需求: 根据评论的年龄来划分bucket,然后按博客的tags进行分组

这里,评论的年龄是comments里面的数据,但是tags是外面的数据,那么如何用nested object外面的数据来进行聚合呢,先看一下请求 

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GET /website/blogs/_search
{
  "size": 0,
  "aggs": {
    "comments_path": {
      "nested": {
        "path": "comments"
      },
      "aggs": {
        "group_by_age": {
          "histogram": {
            "field": "comments.age",
            "interval": 10
          },
          "aggs": {
            "reverse_path":{
              "reverse_nested": {},
              "aggs": {
                "group_by_tags": {
                  "terms": {
                    "field": "tags.keyword"
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

返回值:

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{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 5,
    "successful": 5,
    "failed": 0
  },
  "hits": {
    "total": 1,
    "max_score": 0,
    "hits": []
  },
  "aggregations": {
    "comments_path": {
      "doc_count": 2,
      "group_by_comments_age": {
        "buckets": [
          {
            "key": 20,
            "doc_count": 1,
            "reverse_path": {
              "doc_count": 1,
              "group_by_tags": {
                "doc_count_error_upper_bound": 0,
                "sum_other_doc_count": 0,
                "buckets": [
                  {
                    "key": "投资",
                    "doc_count": 1
                  },
                  {
                    "key": "理财",
                    "doc_count": 1
                  }
                ]
              }
            }
          },
          {
            "key": 30,
            "doc_count": 1,
            "reverse_path": {
              "doc_count": 1,
              "group_by_tags": {
                "doc_count_error_upper_bound": 0,
                "sum_other_doc_count": 0,
                "buckets": [
                  {
                    "key": "投资",
                    "doc_count": 1
                  },
                  {
                    "key": "理财",
                    "doc_count": 1
                  }
                ]
              }
            }
          }
        ]
      }
    }
  }
}

首先,第一个aggs还是先设置path,然后下钻第二个aggs根据年龄去分段划分bucket,继续下钻,第三个aggs的时候用了一个reverse_nested:{},加上这个之后,就可以使用nested object外面的数据了,最后再一次下钻,按照tags分组,因为tags是分词的,所以用了tags.keyword