带有短语建议的拼写错误建议（“您的意思是”）和 Elasticsearch 的空格校正

Question

我使用默认分析器“英语”来搜索文档，它非常好。 但是，当搜索查询拼写错误或按此类拼写错误的短语进行搜索时，我还需要“您的意思是”结果。

我需要什么分析器/过滤器/查询来实现这样的行为？

原文

Elasticsearch is a distributed, open source search and analytics engine for all types of data,
including textual, numerical, geospatial, structured, and unstructured. Elasticsearch is built
on Apache Lucene and was first released in 2010 by Elasticsearch N.V. (now known as Elastic).
Known for its simple REST APIs, distributed nature, speed, and scalability, Elasticsearch is
the central component of the Elastic Stack, a set of open source tools for data ingestion,
enrichment, storage, analysis, and visualization. Commonly referred to as the ELK Stack 
(after Elasticsearch, Logstash, and Kibana), the Elastic Stack now includes a rich collection
of lightweight shipping agents known as Beats for sending data to Elasticsearch.

搜索字词

搜索查询 => 你的意思是 XXX 吗？

遗漏的字母或类似的东西
Elastisearch => Elastic搜索
distribated => 分布式
亚太地区je => Apache

额外空间
弹性搜索 => 弹性搜索

没有空格
开源 => 开源

拼写错误的短语
serach engne => 搜索引擎

Answer 1

您的第一个丢失字母或其他内容的示例可以使用fuzzy query 来实现，第二个使用使用ngram 或edge-ngram tokenizer 的自定义分析器来实现，有关示例，请参阅my blog on autocomplete。

在示例文档中添加模糊查询示例

索引映射

{
    "mappings": {
        "properties": {
            "title": {
                "type": "text"
    
            }
        }
    }
}

索引您的示例文档并使用以下搜索查询

{
    "query": {
        "fuzzy": {
            "title": {
                "value": "distributed"
            }
        }
    }
}

并搜索资源

 "hits": [
            {
                "_index": "didyou",
                "_type": "_doc",
                "_id": "2",
                "_score": 0.89166296,
                "_source": {
                    "title": "distribated"
                }
            }
        ]

对于Elasticsearch

{
    "query": {
        "fuzzy": {
            "title": {
                "value": "Elasticsearch"
            }
        }
    }
}

并搜索结果

  "hits": [
            {
                "_index": "didyou",
                "_type": "_doc",
                "_id": "1",
                "_score": 0.8173577,
                "_source": {
                    "title": "Elastisearch"
                }
            }
        ]