68_数据建模实战_对嵌套的博客评论数据进行聚合分析

68_数据建模实战_对嵌套的博客评论数据进行聚合分析

我们讲解一下基于nested object中的数据进行聚合分析

聚合数据分析的需求1：按照评论日期进行bucket划分，然后拿到每个月的评论的评分的平均值

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"
              }
            }
          }
        }
      }
    }
  }
}

聚合搜索的结果:

{
"took": 52,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0,
"hits": []
},
"aggregations": {
"doc_count": 4,
"group_by_comments_date": {
"buckets": [
{
"key_as_string": "2016-08",
"key": 1470009600000,
"doc_count": 1,
"avg_stars": {
"value": 3
}
},
{
"key_as_string": "2016-09",
"key": 1472688000000,
"doc_count": 2,
"avg_stars": {
"value": 4.5
}
},
{
"key_as_string": "2016-10",
"key": 1475280000000,
"doc_count": 1,
"avg_stars": {
"value": 5
}
}
]
}
}
}
}

按照年龄段聚合----不同年龄段里标签

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

搜索结果如下
{
{
"took": 5,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 2,
"max_score": 0,
"hits": []
},
"aggregations": {
"comments_path": {
"doc_count": 4,
"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": 3,
"reverse_path": {
"doc_count": 2,
"group_by_tags": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "大侠",
"doc_count": 1
},
{
"key": "投资",
"doc_count": 1
},
{
"key": "理财",
"doc_count": 1
},
{
"key": "练功",
"doc_count": 1
}
]
}
}
}
]
}
}
}
}