如果属性有值，则将字符串数组连接到一个桶中的ElasticSearch聚合查询

Question

其目的是在ElasticSearch中创建一个聚合查询，如果属性具有一定的值，则将字符串数组连接到一个桶中。

存储在ES引擎中的JSON示例：

​

{
  "header": {
    "identifier": "oai:gup.ub.gu.se/264598",
    "datestamp": "2019-05-11 11:03:06",
    "setSpec": "GU_SWEPUB"
  },
  "metadata": {
    "mods": {
      "@attributes": {
        "version": "3.5"
      },
      "recordInfo": {
        "recordContentSource": "gu"
      },
      "note": [
        "not verified at registration",
        "Published",
        "3"
      ],
      "identifier": [
        "https://gup.ub.gu.se/publication/264598",
        "29405517",
        "10.1111/adb.12603"
      ],
      "titleInfo": {
        "title": "Activation of amylin receptors attenuates alcohol-mediated behaviours in rodents."
      },
      "abstract": "Alcohol expresses its reinforcing properties by activating areas of the mesolimbic dopamine system, which consists of dopaminergic neurons projecting from the ventral tegmental area to the nucleus accumbens. The findings that reward induced by food and addictive drugs involve common mechanisms raise the possibility that gut-brain hormones, which control appetite, such as amylin, could be involved in reward regulation. Amylin decreases food intake, and despite its implication in the regulation of natural rewards, tenuous evidence support amylinergic mediation of artificial rewards, such as alcohol. Therefore, the present experiments were designed to investigate the effect of salmon calcitonin (sCT), an amylin receptor agonist and analogue of endogenous amylin, on various alcohol-related behaviours in rodents. We showed that acute sCT administration attenuated the established effects of alcohol on the mesolimbic dopamine system, particularly alcohol-induced locomotor stimulation and accumbal dopamine release. Using the conditioned place preference model, we demonstrated that repeated sCT administration prevented the expression of alcohol's rewarding properties and that acute sCT administration blocked the reward-dependent memory consolidation. In addition, sCT pre-treatment attenuated alcohol intake in low alcohol-consuming rats, with a more evident decrease in high alcohol consumers in the intermittent alcohol access model. Lastly, sCT did not alter peanut butter intake, blood alcohol concentration and plasma corticosterone levels in mice. Taken together, the present data support that amylin signalling is involved in the expression of alcohol reinforcement and that amylin receptor agonists could be considered for the treatment of alcohol use disorder in humans.",
      "subject": [
        {
          "@attributes": {
            "lang": "swe",
            "authority": "uka.se"
          },
          "topic": "Neurovetenskaper"
        },
        {
          "@attributes": {
            "lang": "eng",
            "authority": "uka.se"
          },
          "topic": "Neurosciences"
        }
      ],
      "language": {
        "languageTerm": "eng"
      },
      "genre": [
        "publication/journal-article",
        "art",
        "ref"
      ],
      "name": [
        {
          "@attributes": {
            "type": "personal",
            "authority": "gu.se"
          },
          "namePart": [
            "Aimilia Lydia",
            "Kalafateli",
            "1987"
          ],
          "role": {
            "roleTerm": "aut"
          },
          "affiliation": [
            "Göteborgs universitet",
            "Institutionen för neurovetenskap och fysiologi, sektionen för farmakologi",
            "Gothenburg University",
            "Institute of Neuroscience and Physiology, Department of Pharmacology"
          ]
        },
        {
          "@attributes": {
            "type": "personal",
            "authority": "gu.se"
          },
          "namePart": [
            "Daniel",
            "Vallöf",
            "1988"
          ],
          "role": {
            "roleTerm": "aut"
          },
          "affiliation": [
            "Göteborgs universitet",
            "Institutionen för neurovetenskap och fysiologi, sektionen för farmakologi",
            "Gothenburg University",
            "Institute of Neuroscience and Physiology, Department of Pharmacology"
          ]
        },
        {
          "@attributes": {
            "type": "personal",
            "authority": "gu.se"
          },
          "namePart": [
            "Elisabeth",
            "Jerlhag",
            "1978"
          ],
          "role": {
            "roleTerm": "aut"
          },
          "affiliation": [
            "Göteborgs universitet",
            "Institutionen för neurovetenskap och fysiologi, sektionen för farmakologi",
            "Gothenburg University",
            "Institute of Neuroscience and Physiology, Department of Pharmacology"
          ]
        },
        {
          "@attributes": {
            "type": "corporate",
            "lang": "swe",
            "authority": "gu.se"
          },
          "namePart": [
            "Göteborgs universitet",
            "Sahlgrenska akademin",
            "Institutionen för neurovetenskap och fysiologi, sektionen för farmakologi"
          ]
        },
        {
          "@attributes": {
            "type": "corporate",
            "lang": "eng",
            "authority": "gu.se"
          },
          "namePart": [
            "Gothenburg University",
            "Sahlgrenska Academy",
            "Institute of Neuroscience and Physiology, Department of Pharmacology"
          ]
        }
      ],
      "originInfo": {
        "dateIssued": "2019"
      },
      "relatedItem": {
        "@attributes": {
          "type": "host"
        },
        "titleInfo": {
          "title": "Addiction biology"
        },
        "identifier": "1369-1600",
        "part": {
          "detail": [
            {
              "@attributes": {
                "type": "volume"
              },
              "number": "24"
            },
            {
              "@attributes": {
                "type": "issue"
              },
              "number": "3"
            }
          ],
          "extent": {
            "start": "388",
            "end": "402"
          }
        }
      },
      "typeOfResource": "text"
    }
  }
}

​

到目前为止创建的查询：

​

{
  "sort": [
    {
      "metadata.mods.originInfo.dateIssued.keyword": {
        "order": "desc"
      }
    }
  ],
  "query": {
    "multi_match": {
      "query": "Sahlgrenska Academy",
      "type": "best_fields",
      "fields": [
        "metadata.mods.name.namePart"
      ],
      "operator": "and"
    }
  },
  "aggs": {
    "yearSpan": {
      "terms": {
        "field": "metadata.mods.originInfo.dateIssued.keyword",
        "size": 2500
      }
    },
    "authorcloud": {
      "terms": {
        "field": "metadata.mods.name.namePart.keyword",
        "size": 150
      }
    },
    "cloud": {
      "terms": {
        "field": "metadata.mods.subject.topic.keyword",
        "size": 150
      }
    }
  },
  "stored_fields": []
}

​

我想更改上面的查询，以便AuthorCloud聚合只包含name.@attributes.type="personal“字段，并且数组name.namePart中的不同字符串连接到同一个桶中。这个数组在authorcloud中构建了一个单独的桶：

      "namePart": [
        "Aimilia Lydia",
        "Kalafateli",
        "1987"
      ],

产量：

​

bucket = "Aimilia Lydia Kalafateli 1987"

​

Answer 1

两年多了，但我发现自己也有同样的问题。

我能够使用"adjacency_matrix“聚合来完成它。

示例聚合

GET kibana_sample_data_ecommerce/_search
{
  "size": 0,
  "aggs": {
    "interactions": {
      "adjacency_matrix": {
        "filters": {
          "grpA": {
            "match": {
              "manufacturer.keyword": "Low Tide Media"
            }
          },
          "grpB": {
            "match": {
              "manufacturer.keyword": "Elitelligence"
            }
          },
          "grpC": {
            "match": {
              "manufacturer.keyword": "Oceanavigations"
            }
          }
        }
      }
    }
  }
}

示例响应

 {
   ...
   "aggregations" : {
     "interactions" : {
       "buckets" : [
         {
           "key" : "grpA",
           "doc_count" : 1553
         },
         {
           "key" : "grpA&grpB",
           "doc_count" : 590
         },
         {
           "key" : "grpA&grpC",
           "doc_count" : 329
         },
         {
           "key" : "grpB",
           "doc_count" : 1370
         },
         {
           "key" : "grpB&grpC",
           "doc_count" : 299
         },
         {
           "key" : "grpC",
           "doc_count" : 1218
         }
       ]
     }
   }
 }

注意，如果在同一个数组/字段中标识了两个或多个值，则对值进行分组。

这个解决方案是在这篇文章中找到的，还有许多关于弹性搜索聚合的有用信息。