Elasticsearch：如何在搜索中实现 should_not 过滤器

在 Elasticsearch 中，我们可以使用 bool query 来说实现一种组合的查询。它可以具有如下的一种形式的搜索：

POST _search
{
  "query": {
    "bool" : {
      "must" : {
        "term" : { "user.id" : "kimchy" }
      },
      "filter": {
        "term" : { "tags" : "production" }
      },
      "must_not" : {
        "range" : {
          "age" : { "gte" : 10, "lte" : 20 }
        }
      },
      "should" : [
        { "term" : { "tags" : "env1" } },
        { "term" : { "tags" : "deployed" } }
      ],
      "minimum_should_match" : 1,
      "boost" : 1.0
    }
  }
}

在上面，我看到了 must 和 must_not 这样的组合，他们表示必须满足以及禁止满足的意思。我们也同时看到了 should 这个 clause，它表示如果满足就可以增加分数，但是我们看到没有 should_not 这样的表达方法。在我们的实际的搜索中这个其实也是蛮有用的，比如我想对某些不满足一定条件的查询进行加分。
 

在今天的文章中，我们用一个例子来展示如何实现 shoud_not 这样的查询。

我们首先以我们之前的用过的数据来进行展示：

POST _bulk
{ "index" : { "_index" : "twitter", "_id": 1} }
{"user":"双榆树-张三","message":"今儿天气不错啊，出去转转去","uid":2,"age":20,"city":"北京","province":"北京","country":"中国","address":"中国北京市海淀区","location":{"lat":"39.970718","lon":"116.325747"}}
{ "index" : { "_index" : "twitter", "_id": 2 }}
{"user":"东城区-老刘","message":"出发，下一站云南！","uid":3,"age":30,"city":"北京","province":"北京","country":"中国","address":"中国北京市东城区台基厂三条3号","location":{"lat":"39.904313","lon":"116.412754"}}
{ "index" : { "_index" : "twitter", "_id": 3} }
{"user":"东城区-李四","message":"happy birthday!","uid":4,"age":30,"city":"北京","province":"北京","country":"中国","address":"中国北京市东城区","location":{"lat":"39.893801","lon":"116.408986"}}
{ "index" : { "_index" : "twitter", "_id": 4} }
{"user":"朝阳区-老贾","message":"123,gogogo","uid":5,"age":35,"city":"北京","province":"北京","country":"中国","address":"中国北京市朝阳区建国门","location":{"lat":"39.718256","lon":"116.367910"}}
{ "index" : { "_index" : "twitter", "_id": 5} }
{"user":"朝阳区-老王","message":"Happy BirthDay My Friend!","uid":6,"age":50,"city":"北京","province":"北京","country":"中国","address":"中国北京市朝阳区国贸","location":{"lat":"39.918256","lon":"116.467910"}}
{ "index" : { "_index" : "twitter", "_id": 6} }
{"user":"虹桥-老吴","message":"好友来了都今天我生日，好友来了,什么 birthday happy 就成!","uid":7,"age":90,"city":"上海","province":"上海","country":"中国","address":"中国上海市闵行区","location":{"lat":"31.175927","lon":"121.383328"}}

打入上面的 _bulk 指令，我们就创建了一个叫做 twitter 的索引。

我们首先来测试如下的搜索：

GET twitter/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "range": {
            "age": {
              "gte": 40
            }
          }
        }
      ],
      "should": [
        {
          "match": {
            "city": "上海"
          }
        }
      ]
    }
  }
}

上面的搜索表示的意思是：搜索出年龄大于40岁的文档，而且来自上海的文档的排名靠前。搜索的结果就是：

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 2.5404449,
    "hits" : [
      {
        "_index" : "twitter",
        "_type" : "_doc",
        "_id" : "6",
        "_score" : 2.5404449,
        "_source" : {
          "user" : "虹桥-老吴",
          "message" : "好友来了都今天我生日，好友来了,什么 birthday happy 就成!",
          "uid" : 7,
          "age" : 90,
          "city" : "上海",
          "province" : "上海",
          "country" : "中国",
          "address" : "中国上海市闵行区",
          "location" : {
            "lat" : "31.175927",
            "lon" : "121.383328"
          }
        }
      },
      {
        "_index" : "twitter",
        "_type" : "_doc",
        "_id" : "5",
        "_score" : 1.0,
        "_source" : {
          "user" : "朝阳区-老王",
          "message" : "Happy BirthDay My Friend!",
          "uid" : 6,
          "age" : 50,
          "city" : "北京",
          "province" : "北京",
          "country" : "中国",
          "address" : "中国北京市朝阳区国贸",
          "location" : {
            "lat" : "39.918256",
            "lon" : "116.467910"
          }
        }
      }
    ]
  }
}

从上面的搜索的结果，我们可以看出来 _id 为 6 的来自上海的文档排名靠前。

假如现在我们的问题变为：我们想搜索年龄大于49岁，但是不来自上海的排名得分靠前，我们该如何实现这个目的呢？按照这个要求，我们实现如下的 should_not 方法：

GET twitter/_search
{
  "query": {
    "bool": {
      "must": [
        {
          "range": {
            "age": {
              "gte": 40
            }
          }
        }
      ],
      "should": [
        {
          "bool": {
            "must_not": [
              {
                "match": {
                  "city": "上海"
                }
              }
            ]
          }
        }
      ]
    }
  }
}

请注意上面的 should 部分的写法。它使用了另外一个 bool query 来表达一个来自非上海的查询。上面的查询的结果是：

{
  "took" : 0,
  "timed_out" : false,
  "_shards" : {
    "total" : 1,
    "successful" : 1,
    "skipped" : 0,
    "failed" : 0
  },
  "hits" : {
    "total" : {
      "value" : 2,
      "relation" : "eq"
    },
    "max_score" : 1.0,
    "hits" : [
      {
        "_index" : "twitter",
        "_type" : "_doc",
        "_id" : "5",
        "_score" : 1.0,
        "_source" : {
          "user" : "朝阳区-老王",
          "message" : "Happy BirthDay My Friend!",
          "uid" : 6,
          "age" : 50,
          "city" : "北京",
          "province" : "北京",
          "country" : "中国",
          "address" : "中国北京市朝阳区国贸",
          "location" : {
            "lat" : "39.918256",
            "lon" : "116.467910"
          }
        }
      },
      {
        "_index" : "twitter",
        "_type" : "_doc",
        "_id" : "6",
        "_score" : 1.0,
        "_source" : {
          "user" : "虹桥-老吴",
          "message" : "好友来了都今天我生日，好友来了,什么 birthday happy 就成!",
          "uid" : 7,
          "age" : 90,
          "city" : "上海",
          "province" : "上海",
          "country" : "中国",
          "address" : "中国上海市闵行区",
          "location" : {
            "lat" : "31.175927",
            "lon" : "121.383328"
          }
        }
      }
    ]
  }
}

显然这次的结果，我们并没有改变所返回的数据的数量，但是我们确实改变了返回数据的次序，虽然在本例子中分数还是 1.0（这是因为 must_not 不影响分数）。在这次的查询中，我们可以看到来自北京的文档的排名提前了。