ElasticSearch搜索实例含高亮显示及搜索的特殊字符过滤
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应用说明见代码注解。
1.简单搜索实例展示:
public void search() throws IOException { // 自定义集群结点名称 String clusterName = "elasticsearch_pudongping"; // 获取客户端 Client client = ESClient.initClient(clusterName); // 创建查询索引,参数productindex表示要查询的索引库为productindex SearchRequestBuilder searchRequestBuilder = client .prepareSearch("productindex"); // 设置查询索引类型,setTypes("productType1", "productType2","productType3"); // 用来设定在多个类型中搜索 searchRequestBuilder.setTypes("productIndex"); // 设置查询类型 1.SearchType.DFS_QUERY_THEN_FETCH = 精确查询 2.SearchType.SCAN = // 扫描查询,无序 searchRequestBuilder.setSearchType(SearchType.DFS_QUERY_THEN_FETCH); // 设置查询关键词 searchRequestBuilder .setQuery(QueryBuilders.fieldQuery("title", "Acer")); // 查询过滤器过滤价格在4000-5000内 这里范围为[4000,5000]区间闭包含,搜索结果包含价格为4000和价格为5000的数据 searchRequestBuilder.setFilter(FilterBuilders.rangeFilter("price") .from(4000).to(5000)); // 分页应用 searchRequestBuilder.setFrom(0).setSize(60); // 设置是否按查询匹配度排序 searchRequestBuilder.setExplain(true); // 执行搜索,返回搜索响应信息 SearchResponse response = searchRequestBuilder.execute().actionGet(); SearchHits searchHits = response.getHits(); SearchHit[] hits = searchHits.getHits(); for (int i = 0; i < hits.length; i++) { SearchHit hit = hits[i]; Map<String, Object> result = hit.getSource(); // 打印map集合:{id=26, onSale=true, title=宏基Acer乐3, price=4009.0, // description=null, createDate=1380530123140, type=2} System.out.println(result); } System.out.println("search success .."); }
说明:
client.prepareSearch用来创建一个SearchRequestBuilder,搜索即由SearchRequestBuilder执行。
client.prepareSearch方法有参数为一个或多个index,表现在数据库中,即零个或多个数据库名,你既可以使用(下面两个都可以表示在多个索引库中查找):
client.prepareSearch().setIndices("index1","index2","index3","index4");
或者:
client.prepareSearch("index1","index2","index3","index4");
SearchRequestBuilder常用方法说明:
(1) setIndices(String... indices):上文中描述过,参数可为一个或多个字符串,表示要进行检索的index; (2) setTypes(String... types):参数可为一个或多个字符串,表示要进行检索的type,当参数为0个或者不调用此方法时,表示查询所有的type; setSearchType(SearchType searchType):执行检索的类别,值为org.elasticsearch.action.search.SearchType的元素,SearchType是一个枚举类型的类, 其值如下所示: QUERY_THEN_FETCH:查询是针对所有的块执行的,但返回的是足够的信息,而不是文档内容(Document)。结果会被排序和分级,基于此,只有相关的块的文档对象会被返回。由于被取到的仅仅是这些,故而返回的hit的大小正好等于指定的size。这对于有许多块的index来说是很便利的(返回结果不会有重复的,因为块被分组了) QUERY_AND_FETCH:最原始(也可能是最快的)实现就是简单的在所有相关的shard上执行检索并返回结果。每个shard返回一定尺寸的结果。由于每个shard已经返回了一定尺寸的hit,这种类型实际上是返回多个shard的一定尺寸的结果给调用者。 DFS_QUERY_THEN_FETCH:与QUERY_THEN_FETCH相同,预期一个初始的散射相伴用来为更准确的score计算分配了的term频率。 DFS_QUERY_AND_FETCH:与QUERY_AND_FETCH相同,预期一个初始的散射相伴用来为更准确的score计算分配了的term频率。 SCAN:在执行了没有进行任何排序的检索时执行浏览。此时将会自动的开始滚动结果集。 COUNT:只计算结果的数量,也会执行facet。 (4) setSearchType(String searchType),与setSearchType(SearchType searchType)类似,区别在于其值为字符串型的SearchType,值可为dfs_query_then_fetch、dfsQueryThenFetch、dfs_query_and_fetch、dfsQueryAndFetch、query_then_fetch、queryThenFetch、query_and_fetch或queryAndFetch; (5) setScroll(Scroll scroll)、setScroll(TimeValue keepAlive)和setScroll(String keepAlive),设置滚动,参数为Scroll时,直接用new Scroll(TimeValue)构造一个Scroll,为TimeValue或String时需要将TimeValue和String转化为Scroll; (6) setTimeout(TimeValue timeout)和setTimeout(String timeout),设置搜索的超时时间; (7) setQuery,设置查询使用的Query; (8) setFilter,设置过滤器; (9) setMinScore,设置Score的最小数量; (10) setFrom,从哪一个Score开始查; (11) setSize,需要查询出多少条结果;
检索出结果后,通过response.getHits()可以得到所有的SearchHit,得到Hit后,便可迭代Hit取到对应的Document,转化成为需要的实体。
2.搜索高亮显示
spring-boot-starter-data-elasticsearch高亮显示场景的一个Demo
org.springframework.data.elasticsearch.core.query.NativeSearchQueryBuilder
org.springframework.data.elasticsearch.core.SearchResultMapper
org.springframework.data.domain.PageImpl
org.elasticsearch.action.search.SearchResponse
org.elasticsearch.search.SearchHit
org.elasticsearch.search.highlight.HighlightField
String preTag = "<font color=\'#dd4b39\'>";//google的色值 String postTag = "</font>"; SearchQuery searchQuery = new NativeSearchQueryBuilder() .withQuery(queryBuilder) .withFilter(QueryBuilders.termQuery("status", CommConstants.ItemStatus.Normal)) .withSort(SortBuilders.fieldSort("modifiedTime").order(SortOrder.DESC)) .withPageable(pageable) .withHighlightFields(new HighlightBuilder.Field("name").preTags(preTag).postTags(postTag) , new HighlightBuilder.Field("memo").preTags(preTag).postTags(postTag)) .build(); return elasticsearchTemplate.queryForPage(searchQuery, UserDocument.class, new SearchResultMapper() { @Override public <T> Page<T> mapResults(SearchResponse response, Class<T> clazz, Pageable pageable) { List<UserDocument> chunk = new ArrayList<>(); for (SearchHit searchHit : response.getHits()) { if (response.getHits().getHits().length <= 0) { return null; } UserDocument user = new UserDocument(); user.setId(Long.valueOf(searchHit.getId())); //name or memoe HighlightField name = searchHit.getHighlightFields().get("name"); if (name != null) { user.setName(name.fragments()[0].toString()); } HighlightField memo = searchHit.getHighlightFields().get("memo"); if (memo != null) { user.setMemo(memo.fragments()[0].toString()); } chunk.add(user); } if (chunk.size() > 0) { return new PageImpl<T>((List<T>) chunk); } return null; } });
@Test public void shouldReturnHighlightedFieldsForGivenQueryAndFields() { //given String documentId = randomNumeric(5); String actualMessage = "some test message"; String highlightedMessage = "some <em>test</em> message"; SampleEntity sampleEntity = SampleEntity.builder().id(documentId) .message(actualMessage) .version(System.currentTimeMillis()).build(); IndexQuery indexQuery = getIndexQuery(sampleEntity); elasticsearchTemplate.index(indexQuery); elasticsearchTemplate.refresh(SampleEntity.class); SearchQuery searchQuery = new NativeSearchQueryBuilder() .withQuery(termQuery("message", "test")) .withHighlightFields(new HighlightBuilder.Field("message")) .build(); Page<SampleEntity> sampleEntities = elasticsearchTemplate.queryForPage(searchQuery, SampleEntity.class, new SearchResultMapper() { @Override public <T> Page<T> mapResults(SearchResponse response, Class<T> clazz, Pageable pageable) { List<SampleEntity> chunk = new ArrayList<SampleEntity>(); for (SearchHit searchHit : response.getHits()) { if (response.getHits().getHits().length <= 0) { return null; } SampleEntity user = new SampleEntity(); user.setId(searchHit.getId()); user.setMessage((String) searchHit.getSource().get("message")); user.setHighlightedMessage(searchHit.getHighlightFields().get("message").fragments()[0].toString()); chunk.add(user); } if (chunk.size() > 0) { return new PageImpl<T>((List<T>) chunk); } return null; } }); assertThat(sampleEntities.getContent().get(0).getHighlightedMessage(), is(highlightedMessage)); }
http://stackoverflow.com/questions/37049764/how-to-provide-highlighting-with-spring-data-elasticsearch
SearchRequestBuilder中的addHighlightedField()方法可以定制在哪个域值的检索结果的关键字上增加高亮
public void search() throws IOException { // 自定义集群结点名称 String clusterName = "elasticsearch_pudongping"; // 获取客户端 Client client = ESClient.initClient(clusterName); // 创建查询索引,参数productindex表示要查询的索引库为productindex SearchRequestBuilder searchRequestBuilder = client .prepareSearch("productindex"); // 设置查询索引类型,setTypes("productType1", "productType2","productType3"); // 用来设定在多个类型中搜索 searchRequestBuilder.setTypes("productIndex"); // 设置查询类型 1.SearchType.DFS_QUERY_THEN_FETCH = 精确查询 2.SearchType.SCAN = 扫描查询,无序 searchRequestBuilder.setSearchType(SearchType.DFS_QUERY_THEN_FETCH); // 设置查询关键词 searchRequestBuilder .setQuery(QueryBuilders.fieldQuery("title", "Acer")); // 查询过滤器过滤价格在4000-5000内 这里范围为[4000,5000]区间闭包含,搜索结果包含价格为4000和价格为5000的数据 searchRequestBuilder.setFilter(FilterBuilders.rangeFilter("price") .from(4000).to(5000)); // 分页应用 searchRequestBuilder.setFrom(0).setSize(60); // 设置是否按查询匹配度排序 searchRequestBuilder.setExplain(true); //设置高亮显示 searchRequestBuilder.addHighlightedField("title"); searchRequestBuilder.setHighlighterPreTags("<span style=\\"color:red\\">"); searchRequestBuilder.setHighlighterPostTags("</span>"); // 执行搜索,返回搜索响应信息 SearchResponse response = searchRequestBuilder.execute().actionGet(); //获取搜索的文档结果 SearchHits searchHits = response.getHits(); SearchHit[] hits = searchHits.getHits(); ObjectMapper mapper = new ObjectMapper(); for (int i = 0; i < hits.length; i++) { SearchHit hit = hits[i]; //将文档中的每一个对象转换json串值 String json = hit.getSourceAsString(); //将json串值转换成对应的实体对象 Product product = mapper.readValue(json, Product.class); //获取对应的高亮域 Map<String, HighlightField> result = hit.highlightFields(); //从设定的高亮域中取得指定域 HighlightField titleField = result.get("title"); //取得定义的高亮标签 Text[] titleTexts = titleField.fragments(); //为title串值增加自定义的高亮标签 String title = ""; for(Text text : titleTexts){ title += text; } //将追加了高亮标签的串值重新填充到对应的对象 product.setTitle(title); //打印高亮标签追加完成后的实体对象 System.out.println(product); } System.out.println("search success .."); }
程序运行结果:
[id=8,title=宏基<span style="color:red">Acer</span>,description=宏基Acer蜂鸟系列,price=5000.0,onSale=true,type=1,createDate=Mon Sep 30 13:46:41 CST 2013] [id=21,title=宏基<span style="color:red">Acer</span>,description=宏基Acer蜂鸟系列,price=5000.0,onSale=true,type=1,createDate=Mon Sep 30 13:48:17 CST 2013] [id=7,title=宏基<span style="color:red">Acer</span>,description=宏基Acer蜂鸟系列,price=5000.0,onSale=true,type=1,createDate=Mon Sep 30 11:38:50 CST 2013] [id=5,title=宏基<span style="color:red">Acer</span>乐0,description=<null>,price=4000.0,onSale=true,type=1,createDate=Mon Sep 30 16:35:23 CST 2013] [id=12,title=宏基<span style="color:red">Acer</span>乐1,description=<null>,price=4003.0,onSale=false,type=2,createDate=Mon Sep 30 16:35:23 CST 2013] [id=19,title=宏基<span style="color:red">Acer</span>乐2,description=<null>,price=4006.0,onSale=false,type=1,createDate=Mon Sep 30 16:35:23 CST 2013] [id=26,title=宏基<span style="color:red">Acer</span>乐3,description=<null>,price=4009.0,onSale=true,type=2,createDate=Mon Sep 30 16:35:23 CST 2013] [id=33,title=宏基<span style="color:red">Acer</span>乐4,description=<null>,price=4012.0,onSale=false,type=1,createDate=Mon Sep 30 16:35:23 CST 2013]
从程序执行结果中我们可以看到,我们定义的高亮标签已经追加到指定的域上了.
当搜索索引的时候,你搜索关键字包含了特殊字符,那么程序就会报错
// fieldQuery 这个必须是你的索引字段哦,不然查不到数据,这里我只设置两个字段 id ,title String title = "title+-&&||!(){}[]^\\"~*?:\\\\"; title = QueryParser.escape(title);// 主要就是这一句把特殊字符都转义,那么lucene就可以识别 searchRequestBuilder.setQuery(QueryBuilders.fieldQuery("title", title));
转载请注明出处:[http://www.cnblogs.com/dennisit/p/3363851.html]
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