000 ES suggest- 英文
发布于: 2021 年 04 月 29 日
Suggest 使用场景，自动补全或者智能纠错，基本使用下来，可以很好的满足
建立索引，注意 type 的选择
PUT /blogs { "mappings": { "properties": { "body": { "type": "text" } } } }复制代码
写入数据
POST _bulk/?refresh=true { "index" : { "_index" : "blogs" } } { "body": "Lucene is cool"} { "index" : { "_index" : "blogs" } } { "body": "Elasticsearch builds on top of lucene"} { "index" : { "_index" : "blogs" } } { "body": "Elasticsearch rocks"} { "index" : { "_index" : "blogs" } } { "body": "Elastic is the company behind ELK stack"} { "index" : { "_index" : "blogs" } } { "body": "elk rocks"} { "index" : { "_index" : "blogs" } } { "body": "elasticsearch is rock solid"}复制代码
Term suggest (missing model)，大家可以从返回的 result 推测出 missing mode 的意思，返回结果中并没有 options
POST /blogs/_search{ "suggest": { "my-suggestion": { "text": "lucne rock", "term": { "suggest_mode": "missing", "field": "body" } } }}
# result{ "took" : 1, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 0, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "suggest" : { "my-suggestion" : [ { "text" : "lucne", "offset" : 0, "length" : 5, "options" : [ { "text" : "lucene", "score" : 0.8, "freq" : 2 } ] }, { "text" : "rock", "offset" : 6, "length" : 4, "options" : [ ] } ] }}复制代码
Term suggest (popular model)，此时是有返回 options 的
POST /blogs/_search{ "suggest": { "my-suggestion": { "text": "lucne rock", "term": { "suggest_mode": "popular", "field": "body" } } }}
# result{ "took" : 582, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 0, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "suggest" : { "my-suggestion" : [ { "text" : "lucne", "offset" : 0, "length" : 5, "options" : [ { "text" : "lucene", "score" : 0.8, "freq" : 2 } ] }, { "text" : "rock", "offset" : 6, "length" : 4, "options" : [ { "text" : "rocks", "score" : 0.75, "freq" : 2 } ] } ] }}复制代码
Phrase suggest
POST /blogs/_search{ "suggest": { "my-suggestion": { "text": "lucne and elasticsear rock", "phrase": { "field": "body", "highlight": { "pre_tag": "<em>", "post_tag": "</em>" } } } }}
# result{ "took" : 221, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 0, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "suggest" : { "my-suggestion" : [ { "text" : "lucne and elasticsear rock", "offset" : 0, "length" : 26, "options" : [ { "text" : "lucene and elasticsearch rock", "highlighted" : "<em>lucene</em> and <em>elasticsearch</em> rock", "score" : 0.004993905 }, { "text" : "lucne and elasticsearch rock", "highlighted" : "lucne and <em>elasticsearch</em> rock", "score" : 0.0033391973 }, { "text" : "lucene and elasticsear rock", "highlighted" : "<em>lucene</em> and elasticsear rock", "score" : 0.0029183894 } ] } ] }}复制代码
Completion Suggester（prefix completion）
主要针对的应用场景就是"Auto Completion"。 此场景下用户每输入一个字符的时候，就需要即时发送一次查询请求到后端查找匹配项，在用户输入速度较高的情况下对后端响应速度要求比较苛刻。因此实现上它和前面两个 Suggester 采用了不同的数据结构，索引并非通过倒排来完成，而是将 analyze 过的数据编码成 FST 和索引一起存放。对于一个 open 状态的索引，FST 会被 ES 整个装载到内存里的，进行前缀查找速度极快。但是 FST 只能用于前缀查找，这也是 Completion Suggester 的局限所在。
# create index PUT /blogs_completion/{ "mappings": { "properties": { "body": { "type": "completion" } } }}
# add dataPOST _bulk/?refresh=true{ "index" : { "_index" : "blogs_completion" } }{ "body": "Lucene is cool"}{ "index" : { "_index" : "blogs_completion" } }{ "body": "Elasticsearch builds on top of lucene"}{ "index" : { "_index" : "blogs_completion" } }{ "body": "Elasticsearch rocks"}{ "index" : { "_index" : "blogs_completion"} }{ "body": "Elastic is the company behind ELK stack"}{ "index" : { "_index" : "blogs_completion" } }{ "body": "the elk stack rocks"}{ "index" : { "_index" : "blogs_completion"} }{ "body": "elasticsearch is rock solid”}
# prefix completionPOST blogs_completion/_search?pretty{ "size": 0, "suggest": { "blog-suggest": { "prefix": "elastic i", "completion": { "field": "body" } } }}
# prefix completion result{ "took" : 1, "timed_out" : false, "_shards" : { "total" : 1, "successful" : 1, "skipped" : 0, "failed" : 0 }, "hits" : { "total" : { "value" : 0, "relation" : "eq" }, "max_score" : null, "hits" : [ ] }, "suggest" : { "blog-suggest" : [ { "text" : "elastic i", "offset" : 0, "length" : 9, "options" : [ { "text" : "Elastic is the company behind ELK stack", "_index" : "blogs_completion", "_type" : "_doc", "_id" : "dllnEnkBgt5AqocFAwm-", "_score" : 1.0, "_source" : { "body" : "Elastic is the company behind ELK stack" } } ] } ] }}复制代码
Completion suggest 注意事项
值得注意的一点是 Completion Suggester 在索引原始数据的时候也要经过 analyze 阶段，取决于选用的 analyzer 不同，某些词可能会被转换，某些词可能被去除，这些会影响 FST 编码结果，也会影响查找匹配的效果。
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发布于: 2021 年 04 月 29 日阅读数: 13
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