我想创建有关如何基于令牌完成术语的建议,类似于像自动填充一样的谷歌,但只有一个令牌或单词。
我想搜索将被标记化的文件名。例如。 “BRAND_Connect_A1233.jpg”被标记为“品牌”,“连接”,“a1234”和“jpg”。
现在我想问一些建议,例如: “的 N ”。 该建议应该提供完整的匹配令牌,而不是完整的文件名:
“A12”的建议应为“A1234”,“A1233”,“A1233”......
使用查询,构面和过滤器可以正常工作。
首先我创建了一个包含tokenizer和过滤器的映射:
curl -XPUT 'localhost:9200/files/?pretty=1' -d '
{
"settings" : {
"analysis" : {
"analyzer" : {
"filename_search" : {
"tokenizer" : "filename",
"filter" : ["lowercase"]
},
"filename_index" : {
"tokenizer" : "filename",
"filter" : ["lowercase","edge_ngram"]
}
},
"tokenizer" : {
"filename" : {
"pattern" : "[^[;_\\.\\/]\\d]+",
"type" : "pattern"
}
},
"filter" : {
"edge_ngram" : {
"side" : "front",
"max_gram" : 20,
"min_gram" : 2,
"type" : "edgeNGram"
}
}
}
},
"mappings" : {
"file" : {
"properties" : {
"filename" : {
"type" : "string",
"search_analyzer" : "filename_search",
"index_analyzer" : "filename_index"
}
}
}
}
}'
两种分析仪都运行良好:
curl -XGET 'localhost:9200/files/_analyze?pretty=1&text=BRAND_ConnectBlue_A1234.jpg&analyzer=filename_search'
curl -XGET 'localhost:9200/files/_analyze?pretty=1&text=BRAND_ConnectBlue_A1234.jpg&analyzer=filename_index'
现在我添加了一些示例数据
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "BRAND_ConnectBlue_A1234.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "BRAND_Connect_A1233.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "BRAND_ConceptSpace_A1244.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "COMPANY_Connect_A1222.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "COMPANY_Concept_A1233.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "DEALER_Connect_B1234_.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "DEALER_Contour21_B1233.jpg"}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "DEALER_ConceptCube_B2233.jpg"}'
curl -X POST "localhost:9200/files/_refresh"
获得所需建议的各种方法无法提供预期结果。我试图命名分析仪,并尝试了各种分析仪和通配符组合。
curl -XGET 'localhost:9200/files/_suggest?pretty=true' -d '{
"text" : "con",
"simple_phrase" : {
"phrase" : {
"field" : "filename",
"size" : 15,
"real_word_error_likelihood" : 0.75,
"max_errors" : 0.1,
"gram_size" : 3
}
}
}'
curl -XGET 'localhost:9200/files/_suggest?pretty=true' -d '{
"my-suggestion" : {
"text" : "con",
"term" : {
"field" : "filename",
"analyzer": "filename_index"
}
}
}'
答案 0 :(得分:0)
您需要添加一个特殊的映射来使用完成建议器,如文档in the official ElasticSearch docs所示。我修改了你的例子来展示它是如何工作的。
首先创建索引。请注意filename_suggest
映射。
curl -XPUT 'localhost:9200/files/?pretty=1' -d '
{
"settings" : {
"analysis" : {
"analyzer" : {
"filename_search" : {
"tokenizer" : "filename",
"filter" : ["lowercase"]
},
"filename_index" : {
"tokenizer" : "filename",
"filter" : ["lowercase","edge_ngram"]
}
},
"tokenizer" : {
"filename" : {
"pattern" : "[^[;_\\.\\/]\\d]+",
"type" : "pattern"
}
},
"filter" : {
"edge_ngram" : {
"side" : "front",
"max_gram" : 20,
"min_gram" : 2,
"type" : "edgeNGram"
}
}
}
},
"mappings" : {
"file" : {
"properties" : {
"filename" : {
"type" : "string",
"analyzer": "filename_index",
"search_analyzer" : "filename_search"
},
"filename_suggest": {
"type": "completion",
"analyzer": "simple",
"search_analyzer": "simple",
"payloads": true
}
}
}
}
}'
添加一些数据。请注意filename_suggest
如何包含input
字段,其中包含要匹配的关键字。
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "BRAND_ConnectBlue_A1234.jpg", "filename_suggest": { "input": ["BRAND", "ConnectBlue", "A1234", "jpg"], "payload": {} } }'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "BRAND_Connect_A1233.jpg", "filename_suggest": { "input": ["BRAND", "Connect", "A1233", "jpg"], "payload": {} } }'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "BRAND_ConceptSpace_A1244.jpg", "filename_suggest": { "input": ["BRAND", "ConceptSpace", "A1244", "jpg"], "payload": {} } }'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "COMPANY_Connect_A1222.jpg", "filename_suggest": { "input": ["COMPANY", "Connect", "A1222", "jpg"], "payload": {} } }'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "COMPANY_Concept_A1233.jpg", "filename_suggest": { "input": ["COMPANY", "Concept", "A1233", "jpg"], "payload": {} } }'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "DEALER_Connect_B1234_.jpg", "filename_suggest": { "input": ["DEALER", "Connect", "B1234", "jpg"], "payload": {} } }'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "DEALER_Contour21_B1233.jpg", "filename_suggest": { "input": ["DEALER", "Contour21", "B1233", "jpg"], "payload": {} }}'
curl -X POST "localhost:9200/files/file" -d '{ "filename" : "DEALER_ConceptCube_B2233.jpg", "filename_suggest": { "input": ["DEALER", "ConceptCube", "B2233", "jpg"], "payload": {} }}'
curl -X POST "localhost:9200/files/_refresh"
现在执行查询:
curl -XPOST 'localhost:9200/files/_suggest?pretty=true' -d '{
"filename_suggest" : {
"text" : "con",
"completion": {
"field": "filename_suggest", "size": 10
}
}
}'
结果:
{
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"filename_suggest" : [ {
"text" : "con",
"offset" : 0,
"length" : 3,
"options" : [ {
"text" : "Connect",
"score" : 2.0,
"payload":{}
}, {
"text" : "Concept",
"score" : 1.0,
"payload":{}
}, {
"text" : "ConceptSpace",
"score" : 1.0,
"payload":{}
}, {
"text" : "ConnectBlue",
"score" : 1.0,
"payload":{}
}, {
"text" : "Contour21",
"score" : 1.0,
"payload":{}
} ]
} ]
}