Elasticsearch 自动完成对数组字段的搜索 [英] Elasticsearch autocomplete search on array field

问题描述

我正在研究具有字符串类型数组的文档字段的自动完成建议.我的文档如下所示；

I am working on autocomplete suggestion on document field that has array of type string. My document is like below;

{

    "title": "Product1",
    "sales": "6",
    "rating": "0.0",
    "cost": "45.00",
    "tags": [
        "blog",
        "magazine",
        "responsive",
        "two columns",
        "wordpress"
    ],
    "category": "wordpress",
    "description": "Product1 Description",
    "createDate": "2013-12-19"
}

{

    "title": "Product1",
    "sales": "6",
    "rating": "0.0",
    "cost": "45.00",
    "tags": [
        "blog",
        "paypal",
        "responsive",
        "skrill",
        "wordland"
    ],
    "category": "wordpress",
    "description": "Product1 Description",
    "createDate": "2013-12-19"
}

我正在对 标签 字段执行自动完成搜索.我的查询就像;

I am performing autocomplete search on tags field. My query is like;

query: {
                    query_string: {
                        query: "word*",
                        fields: ["tags"]
                    }
                },
                facets: {
                    tags: {
                        terms: {
                            field: "tags"
                        }
                    }
                }

当用户输入word"时，我想显示wordland"和wordpress".但是，我无法做到这一点.

When user type "word" I want to display "wordland" and "wordpress". However, I couldn't manage to do that.

你能帮忙解决这个问题吗?

Could you please help on this?

谢谢

推荐答案

您是否尝试过 完成提示?解决您的问题的一种方法如下:

Have you tried completion suggest? One way to solve your problem is as follows:

1) 创建索引:

curl -XPUT "http://localhost:9200/test_index/"

2) 创建映射，使用完成建议类型:

2) Create the mapping, using the completion suggester type:

curl -XPUT "http://localhost:9200/test_index/product/_mapping" -d'
{
   "product": {
      "properties": {
         "category": {
            "type": "string"
         },
         "cost": {
            "type": "string"
         },
         "createDate": {
            "type": "date",
            "format": "dateOptionalTime"
         },
         "description": {
            "type": "string"
         },
         "rating": {
            "type": "string"
         },
         "sales": {
            "type": "string"
         },
         "tags": {
            "type": "string"
         },
         "title": {
            "type": "string"
         },
         "suggest": {
            "type": "completion",
            "index_analyzer": "simple",
            "search_analyzer": "simple",
            "payloads": false
         }
      }
   }
}'

3) 添加您的文档:

curl -XPUT "http://localhost:9200/test_index/product/1" -d'
{
   "title": "Product1",
   "sales": "6",
   "rating": "0.0",
   "cost": "45.00",
   "tags": [
      "blog",
      "magazine",
      "responsive",
      "two columns",
      "wordpress"
   ],
   "suggest": {
      "input": [
         "blog",
         "magazine",
         "responsive",
         "two columns",
         "wordpress"
      ]
   },
   "category": "wordpress",
   "description": "Product1 Description",
   "createDate": "2013-12-19"
}'

curl -XPUT "http://localhost:9200/test_index/product/2" -d'
{

    "title": "Product2",
    "sales": "6",
    "rating": "0.0",
    "cost": "45.00",
    "tags": [
        "blog",
        "paypal",
        "responsive",
        "skrill",
        "wordland"
    ],
   "suggest": {
      "input": [
         "blog",
        "paypal",
        "responsive",
        "skrill",
        "wordland"
      ]
   },
    "category": "wordpress",
    "description": "Product1 Description",
    "createDate": "2013-12-19"
}'

4) 然后使用 _suggest 端点进行查询:

4) And then query using the _suggest endpoint:

curl -XPOST "http://localhost:9200/test_index/_suggest" -d'
{
    "product_suggest":{
        "text":"word",
        "completion": {
            "field" : "suggest"
        }
    }
}'

您将得到您预期的结果:

and you will get the results back that you expected:

{
   "_shards": {
      "total": 2,
      "successful": 2,
      "failed": 0
   },
   "product_suggest": [
      {
         "text": "word",
         "offset": 0,
         "length": 4,
         "options": [
            {
               "text": "wordland",
               "score": 1
            },
            {
               "text": "wordpress",
               "score": 1
            }
         ]
      }
   ]
}

当然，这个解决方案可以稍微改进一下，特别是通过修剪一些重复的数据，但这应该会为您指明正确的方向.

This solution could be refined a bit, of course, particularly by pruning some duplicate data, but this should point you in the right direction.

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