溶液1
现在，如果你想在索引和存储内容之前完全去除html，你可以使用mapper attachment插件 - 当y您可以定义映射，您可以将content_type分类为“html”。“
映射器附件对许多事情很有用，特别是如果您处理多种文档类型，但最值得注意的是 - 我相信只是使用它来剥离html标签就足够了（您不能用html_strip char filter）
虽然只是一个预警 - 没有任何html标签会被存储，所以如果你确实需要这些标签，我会建议定义另一个字段来存储原始内容另一个注意：你不能指定multifields for mapper attachment documents，so you would need to store that that outside of the mapper attachment document。看到我的工作示例如下：
你“会需要导致该映射：
{
"html5-es" : {
"aliases" : { },
"mappings" : {
"document" : {
"properties" : {
"delete" : {
"type" : "boolean"
},
"file" : {
"type" : "attachment",
"fields" : {
"content" : {
"type" : "string",
"store" : true,
"term_vector" : "with_positions_offsets",
"analyzer" : "autocomplete"
},
"author" : {
"type" : "string",
"store" : true,
"term_vector" : "with_positions_offsets"
},
"title" : {
"type" : "string",
"store" : true,
"term_vector" : "with_positions_offsets",
"analyzer" : "autocomplete"
},
"name" : {
"type" : "string"
},
"date" : {
"type" : "date",
"format" : "strict_date_optional_time||epoch_millis"
},
"keywords" : {
"type" : "string"
},
"content_type" : {
"type" : "string"
},
"content_length" : {
"type" : "integer"
},
"language" : {
"type" : "string"
}
}
},
"hash_id" : {
"type" : "string"
},
"path" : {
"type" : "string"
},
"raw_content" : {
"type" : "string",
"store" : true,
"term_vector" : "with_positions_offsets",
"analyzer" : "raw"
},
"title" : {
"type" : "string"
}
}
}
},
"settings" : { //insert your own settings here },
"warmers" : { }
}
}
使得在NEST，我将装配的内容以这样：
Attachment attachment = new Attachment();
attachment.Content = Convert.ToBase64String(File.ReadAllBytes("path/to/document"));
attachment.ContentType = "html";
Document document = new Document();
document.File = attachment;
document.RawContent = InsertRawContentFromString(originalText);
我在感测试此 - 结果如下：
"file": {
"_content": "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",
"_content_length": 0,
"_content_type": "html",
"_date": "0001-01-01T00:00:00",
"_title": "Topic10"
},
"delete": false,
"raw_content": "<h1>Topic10</h1><p>Delete this text and replace it with your own content. Check your mailbox.</p><p> </p><p>asdf</p><p> </p><p>10</p><p> </p><p>Lavender.</p><p> </p><p>10/6 12:03</p><p> </p><p>5 09</p><p> </p><p>11 47</p><p> </p><p>Halloween is in October.</p><p> </p><p>jog</p>"
},
"highlight": {
"file.content": [
"\n <em>Topic10</em>\n\n Delete this text and replace it with your own content. Check your mailbox.\n\n \n\n asdf\n\n \n\n 10\n\n \n\n Lavender.\n\n \n\n 10/6 12:03\n\n \n\n 5 09\n\n \n\n 11 47\n\n \n\n Halloween is in October.\n\n \n\n jog\n\n "
]
}
解决方案2
您将需要建立使用标准分析仪对您的内容和SEARCH进行索引的NGram分析仪。
"analyzer" : {
"standard" : {
"type" : "standard"
},
"autocomplete" : {
"filter" : [ "standard", "lowercase" ],
"char_filter" : [ "html_strip" ],
"type" : "custom",
"tokenizer" : "ngram"
}
的这个实施例：
输入： “棕色”
NGRAM分析器：
- 并[b]，[BR]，[BRO]，[眉头]，[棕色]
- [R]，[RO]，[行]，[rown]
- [0]，[流]，[自己]
- [W]，[WN]
- [N]
所以当你做一个自动完成搜索，它将匹配任何这些索引碎片。但是，使用标准分析仪只搜索（返回结果页面）非常重要，这样它就不会仅匹配任何这些随机碎片。