简述
业务开发中经常会遇到这样一种情况,用户在搜索框输入时要实时展示搜索相关的结果。要实现这个场景常用的方案有Completion Suggester、search_as_you_type。那么这两种方式有什么区别呢?一起来了解下。
环境说明:
数据量:9000w+
es版本:7.10.1
脚本执行工具:kibana
Completion Suggester和search_as_you_type的区别
1.Completion Suggester是基于前缀匹配、且数据结构存储在内存中,超级快,缺点是耗内存
2.search_as_you_type可以是前缀、中缀匹配,可以很快,但是要选好查询方式
3.Api调用方式不同,Completion Suggester是通过Suggest语句查询,search_as_you_type和常规查询方式一致
举个栗子
如何实现前缀匹配需求
使用Completion Suggester,示例如下:
- PUT /es_demo
- {
- "mappings": {
- "properties": {
- "title_comp": {
- "type": "completion",
- "analyzer": "standard"
- }
- }
- }
- }
复制代码- POST _bulk
- {"index":{"_index":"es_demo","_id":"1"}}
- {"title_comp": "愤怒的小鸟"}
- {"index":{"_index":"es_demo","_id":"2"}}
- {"title_comp": "最后一只渡渡鸟"}
- {"index":{"_index":"es_demo","_id":"3"}}
- {"title_comp": "今天不加班啊"}
- {"index":{"_index":"es_demo","_id":"4"}}
- {"title_comp": "愤怒的青年"}
- {"index":{"_index":"es_demo","_id":"5"}}
- {"title_comp": "最后一只996程序猿"}
- {"index":{"_index":"es_demo","_id":"6"}}
- {"title_comp": "今日无事,勾栏听曲"}
复制代码
- 查询DSL
通过前缀查询,查找以“愤怒”开头的字符串
- GET /es_demo/_search
- {
- "suggest": {
- "title_suggest": {
- "prefix": "愤怒",
- "completion": {
- "field": "title_comp"
- }
- }
- }
- }
复制代码- @SpringBootTest
- public class SuggestTest {
- @Autowired
- private RestHighLevelClient restHighLevelClient;
- @Test
- public void testComp() {
- List<Map<String, Object>> list = suggestComplete("愤怒");
- list.forEach(m -> System.out.println("[" + m.get("title_comp") + "]"));
- }
- public List<Map<String, Object>> suggestComplete(String keyword) {
- CompletionSuggestionBuilder completionSuggestionBuilder = SuggestBuilders.completionSuggestion("title_comp");
- completionSuggestionBuilder.size(5)
- //跳过重复的
- .skipDuplicates(true);
- SuggestBuilder suggestBuilder = new SuggestBuilder();
- suggestBuilder.addSuggestion("suggest_title", completionSuggestionBuilder)
- .setGlobalText(keyword);
- SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
- searchSourceBuilder.suggest(suggestBuilder);
- SearchRequest searchRequest = new SearchRequest("es_demo").source(searchSourceBuilder);
- try {
- SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
- CompletionSuggestion completionSuggestion = response.getSuggest().getSuggestion("suggest_title");
- List<Map<String, Object>> suggestList = new LinkedList<>();
- for (CompletionSuggestion.Entry.Option option : completionSuggestion.getOptions()) {
- Map<String, Object> map = new HashMap<>();
- map.put("title_comp", option.getHit().getSourceAsMap().get("title_comp"));
- suggestList.add(map);
- }
- return suggestList;
- } catch (IOException e) {
- throw new RuntimeException("ES查询出错");
- }
- }
- }
复制代码 查询结果:如何实现中缀匹配需求
使用search_as_you_type,此处提供了hanlp_index和standard两种分词器的字段示例。示例如下:
- PUT /es_search_as_you_type
- {
- "mappings": {
- "properties": {
- "title": {
- "type": "text",
- "fields": {
- "han": {
- "type": "search_as_you_type",
- "analyzer": "hanlp_index"
- },
- "stan": {
- "type": "search_as_you_type",
- "analyzer": "standard"
- }
- }
- }
- }
- }
- }
复制代码- POST _bulk
- {"index":{"_index":"es_search_as_you_type","_id":"1"}}
- {"title": "愤怒的小鸟"}
- {"index":{"_index":"es_search_as_you_type","_id":"2"}}
- {"title": "最后一只渡渡鸟"}
- {"index":{"_index":"es_search_as_you_type","_id":"3"}}
- {"title": "今天不加班啊"}
- {"index":{"_index":"es_search_as_you_type","_id":"4"}}
- {"title": "愤怒的青年"}
- {"index":{"_index":"es_search_as_you_type","_id":"5"}}
- {"title": "最后一只996程序猿"}
- {"index":{"_index":"es_search_as_you_type","_id":"6"}}
- {"title": "今日无事,勾栏听曲"}
复制代码- GET /es_search_as_you_type/_search
- {
- "query": {
- "match": {
- "title.stan": {
- "query": "的小",
- "operator": "and"
- }
- }
- }
- }
复制代码- @SpringBootTest
- public class SuggestTest {
- @Autowired
- private RestHighLevelClient restHighLevelClient;
- @Test
- public void testSearchAsYouType() {
- List<Map<String, Object>> list = suggestSearchAsYouType("的小");
- list.forEach(m -> System.out.println("[" + m.get("title") + "]"));
- }
- public List<Map<String, Object>> suggestSearchAsYouType(String keyword) {
- //这里使用了search_as_you_type的2gram字段,可以根据自己需求调整配置
- MatchQueryBuilder matchQueryBuilder = matchQuery("title.stan._2gram", keyword).operator(Operator.AND);
- //需要返回的字段
- String[] includeFields = new String[]{"title"};
- SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder()
- .query(matchQueryBuilder).size(5)
- .fetchSource(includeFields, null)
- .trackTotalHits(false)
- .trackScores(true)
- .sort(SortBuilders.scoreSort());
- SearchRequest searchRequest = new SearchRequest("es_search_as_you_type").source(searchSourceBuilder);
- try {
- SearchResponse response = restHighLevelClient.search(searchRequest, RequestOptions.DEFAULT);
- org.elasticsearch.search.SearchHits hits = response.getHits();
- List<Map<String, Object>> suggestList = new LinkedList<>();
- for (org.elasticsearch.search.SearchHit hit : hits) {
- Map<String, Object> map = new HashMap<>();
- map.put("title", hit.getSourceAsMap().get("title").toString());
- suggestList.add(map);
- }
- return suggestList;
- } catch (IOException e) {
- throw new RuntimeException("ES查询出错");
- }
- }
- }
复制代码 查询结果:分词器说明
查看分词结果的方式
第一种
指定分词器- GET _analyze
- {
- "analyzer": "standard",
- "text": [
- "愤怒的小鸟"
- ]
- }
复制代码 第二种
指定使用某个字段的分词器- POST es_search_as_you_type/_analyze
- {
- "field": "title.stan",
- "text": [
- "愤怒的青年"
- ]
- }
复制代码 hanlp_index和standard分词器的区别
standard分词器
- 默认会过滤掉符号
- 中文以单个字为最小单位,英文则会以空格符或其他符号或中文分隔作为一个单词
例:- GET _analyze
- {
- "analyzer": "standard",
- "text": [
- "愤怒的小鸟"
- ]
- }
复制代码 分词结果:- {
- "tokens" : [
- {
- "token" : "愤",
- "start_offset" : 0,
- "end_offset" : 1,
- "type" : "<IDEOGRAPHIC>",
- "position" : 0
- },
- {
- "token" : "怒",
- "start_offset" : 1,
- "end_offset" : 2,
- "type" : "<IDEOGRAPHIC>",
- "position" : 1
- },
- {
- "token" : "的",
- "start_offset" : 2,
- "end_offset" : 3,
- "type" : "<IDEOGRAPHIC>",
- "position" : 2
- },
- {
- "token" : "小",
- "start_offset" : 3,
- "end_offset" : 4,
- "type" : "<IDEOGRAPHIC>",
- "position" : 3
- },
- {
- "token" : "鸟",
- "start_offset" : 4,
- "end_offset" : 5,
- "type" : "<IDEOGRAPHIC>",
- "position" : 4
- }
- ]
- }
复制代码 hanlp_index分词器
- 默认不会过滤符号
- 通过语义等对字符串进行分词,会分出词语
例:- GET _analyze
- {
- "analyzer": "hanlp_index",
- "text": [
- "愤怒的小鸟"
- ]
- }
复制代码 分词结果:- {
- "tokens" : [
- {
- "token" : "愤怒",
- "start_offset" : 0,
- "end_offset" : 2,
- "type" : "a",
- "position" : 0
- },
- {
- "token" : "的",
- "start_offset" : 2,
- "end_offset" : 3,
- "type" : "ude1",
- "position" : 1
- },
- {
- "token" : "小鸟",
- "start_offset" : 3,
- "end_offset" : 5,
- "type" : "n",
- "position" : 2
- }
- ]
- }
复制代码 生产实践中的查询情况
基本都是几百毫秒就解决。ps:如果一条数据字段很多,最好只返回几个需要的字段即可,否则数据传输就要占用较多时间。

总结
当然,无论是Completion Suggester还是search_as_you_type的查询配置方式都还有很多,例如Completion Suggester的Context Suggester,search_as_you_type的2gram、3gram,还有查询类型match_bool_prefix、match_phrase、match_phrase_prefix等等。各种组合起来都会产生不同的效果,笔者这里只是列举出一种还算可以的方式。关于其他的查询类型和配置如何使用以及分别是怎么工作的,下次有空再聊聊。
官方文档链接
https://www.elastic.co/guide/en/elasticsearch/reference/7.10/search-as-you-type.html
免责声明:如果侵犯了您的权益,请联系站长,我们会及时删除侵权内容,谢谢合作! |