使用 Range-Elasticsearch 过滤

Question

下面是单行的kibana JSON，

{
  "_index": "questionanswers",
  "_type": "doc",
  "_id": "3",
  "_version": 1,
  "_score": 0,
  "_source": {
    "question": {
      "id": 3,
      "text": "Your first salary",
      "answer_type": "FL",
      "question_type": "BQ"
    },
    "candidate": {
      "id": 13
    },
    "job": {
      "id": 6
    },
    "id": 3,
    "status": "AN",
    "answered_on": "2019-07-12T09:26:01+00:00",
    "answer": "12222222"
  },
  "fields": {
    "answered_on": [
      "2019-07-12T09:26:01.000Z"
    ]
  }
}

我有一个类似的 sql 查询，

Select * from questionanswers where question.id = 3 and answer between 1250 and 1253666

我已将其转换为 elasticsearch 查询，如下所示，

{
    "size": 1000,
    "query": {
        "bool": {
            "must": [
                {
                    "term": {
                        "question.id":3
                    }
                },
                {
                    "range": {
                        "answer": {
                            "from": 1250,
                            "to": 1253666999,
                            "include_lower": true,
                            "include_upper": true,
                            "boost": 1
                        }
                    }
                }
            ],
            "adjust_pure_negative": true,
            "boost": 1
        }
    }
}

这里 answer 被声明为 String ，但我持有 Date、Float 和 String 值。

 "question": {
      "id": 3,
      "text": "Your first salary",
      "answer_type": "FL",
      "question_type": "BQ"
    },

这里answer_type 告诉它期望的答案类型。

当我尝试运行此查询时，我没有得到想要的结果。我对这次打击得到了空洞的回应。 但实际上，有一行满足这个查询。 我的 elasticsearch 查询应该如何过滤，以便我可以使用

question.id = 3 , question.answer_type = "FL" and answer between 1250 and 1253666```

Answer 1

再次查看您的文档。 answer 是一个字符串值，您在查询中将其视为number。所以它显然不起作用。

将此字段的mapping 更改为数字。

这是我在测试索引中编入索引的文档，然后再次运行您的查询，它可以正常工作

为文档编制索引（见answer字段）

POST /so-index4/_doc/1
{
   "question": {
      "id": 3,
      "text": "Your first salary",
      "answer_type": "FL",
      "question_type": "BQ"
    },
    "candidate": {
      "id": 13
    },
    "job": {
      "id": 6
    },
    "id": 3,
    "status": "AN",
    "answered_on": "2019-07-12T09:26:01+00:00",
    "answer": 12222222,
  "fields": {
    "answered_on": [
      "2019-07-12T09:26:01.000Z"
    ]
  }
}

和查询（与您在上面提供的查询相同）

GET /so-index4/_search
{
    "size": 1000,
    "query": {
        "bool": {
            "must": [
                {
                    "term": {
                        "question.id":3
                    }
                },
                {
                    "range": {
                        "answer": {
                            "from": 1250,
                            "to": 1253666999,
                            "include_lower": true,
                            "include_upper": true,
                            "boost": 1
                        }
                    }
                }
            ],
            "adjust_pure_negative": true,
            "boost": 1
        }
    }
}

结果

{
  "took" : 5,
  "timed_out" : false,
  "_shards" : {
    "total" : 5,
    "successful" : 5,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : 1,
    "max_score" : 2.0,
    "hits" : [
      {
        "_index" : "so-index4",
        "_type" : "_doc",
        "_id" : "1",
        "_score" : 2.0,
        "_source" : {
          "question" : {
            "id" : 3,
            "text" : "Your first salary",
            "answer_type" : "FL",
            "question_type" : "BQ"
          },
          "candidate" : {
            "id" : 13
          },
          "job" : {
            "id" : 6
          },
          "id" : 3,
          "status" : "AN",
          "answered_on" : "2019-07-12T09:26:01+00:00",
          "answer" : 12222222,
          "fields" : {
            "answered_on" : [
              "2019-07-12T09:26:01.000Z"
            ]
          }
        }
      }
    ]
  }
}