應用說明見代碼注解。
1.簡單搜索實例展示:
public void search() throws IOException { // 自定義集群結點名稱 String clusterName = "elasticsearch_pudongping"; // 獲取客戶端 Client client = ESClient.initClient(clusterName); // 創建查詢索引,參數productindex表示要查詢的索引庫為productindex SearchRequestBuilder searchRequestBuilder = client .prepareSearch("productindex"); // 設置查詢索引類型,setTypes("productType1", "productType2","productType3"); // 用來設定在多個類型中搜索 searchRequestBuilder.setTypes("productIndex"); // 設置查詢類型 1.SearchType.DFS_QUERY_THEN_FETCH = 精確查詢 2.SearchType.SCAN = // 掃描查詢,無序 searchRequestBuilder.setSearchType(SearchType.DFS_QUERY_THEN_FETCH); // 設置查詢關鍵詞 searchRequestBuilder .setQuery(QueryBuilders.fieldQuery("title", "Acer")); // 查詢過濾器過濾價格在4000-5000內 這里范圍為[4000,5000]區間閉包含,搜索結果包含價格為4000和價格為5000的數據 searchRequestBuilder.setFilter(FilterBuilders.rangeFilter("price") .from(4000).to(5000)); // 分頁應用 searchRequestBuilder.setFrom(0).setSize(60); // 設置是否按查詢匹配度排序 searchRequestBuilder.setExplain(true); // 執行搜索,返回搜索響應信息 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樂3, price=4009.0, // description=null, createDate=1380530123140, type=2} System.out.println(result); } System.out.println("search success .."); }
說明:
client.prepareSearch用來創建一個SearchRequestBuilder,搜索即由SearchRequestBuilder執行。
client.prepareSearch方法有參數為一個或多個index,表現在數據庫中,即零個或多個數據庫名,你既可以使用(下面兩個都可以表示在多個索引庫中查找):
client.prepareSearch().setIndices("index1","index2","index3","index4");
或者:
client.prepareSearch("index1","index2","index3","index4");
SearchRequestBuilder常用方法說明:
(1) setIndices(String... indices):上文中描述過,參數可為一個或多個字符串,表示要進行檢索的index; (2) setTypes(String... types):參數可為一個或多個字符串,表示要進行檢索的type,當參數為0個或者不調用此方法時,表示查詢所有的type; setSearchType(SearchType searchType):執行檢索的類別,值為org.elasticsearch.action.search.SearchType的元素,SearchType是一個枚舉類型的類, 其值如下所示: QUERY_THEN_FETCH:查詢是針對所有的塊執行的,但返回的是足夠的信息,而不是文檔內容(Document)。結果會被排序和分級,基於此,只有相關的塊的文檔對象會被返回。由於被取到的僅僅是這些,故而返回的hit的大小正好等於指定的size。這對於有許多塊的index來說是很便利的(返回結果不會有重復的,因為塊被分組了) QUERY_AND_FETCH:最原始(也可能是最快的)實現就是簡單的在所有相關的shard上執行檢索並返回結果。每個shard返回一定尺寸的結果。由於每個shard已經返回了一定尺寸的hit,這種類型實際上是返回多個shard的一定尺寸的結果給調用者。 DFS_QUERY_THEN_FETCH:與QUERY_THEN_FETCH相同,預期一個初始的散射相伴用來為更准確的score計算分配了的term頻率。 DFS_QUERY_AND_FETCH:與QUERY_AND_FETCH相同,預期一個初始的散射相伴用來為更准確的score計算分配了的term頻率。 SCAN:在執行了沒有進行任何排序的檢索時執行瀏覽。此時將會自動的開始滾動結果集。 COUNT:只計算結果的數量,也會執行facet。 (4) setSearchType(String searchType),與setSearchType(SearchType searchType)類似,區別在於其值為字符串型的SearchType,值可為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),設置滾動,參數為Scroll時,直接用new Scroll(TimeValue)構造一個Scroll,為TimeValue或String時需要將TimeValue和String轉化為Scroll; (6) setTimeout(TimeValue timeout)和setTimeout(String timeout),設置搜索的超時時間; (7) setQuery,設置查詢使用的Query; (8) setFilter,設置過濾器; (9) setMinScore,設置Score的最小數量; (10) setFrom,從哪一個Score開始查; (11) setSize,需要查詢出多少條結果;
檢索出結果后,通過response.getHits()可以得到所有的SearchHit,得到Hit后,便可迭代Hit取到對應的Document,轉化成為需要的實體。
2.搜索高亮顯示
spring-boot-starter-data-elasticsearch高亮顯示場景的一個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()方法可以定制在哪個域值的檢索結果的關鍵字上增加高亮
public void search() throws IOException { // 自定義集群結點名稱 String clusterName = "elasticsearch_pudongping"; // 獲取客戶端 Client client = ESClient.initClient(clusterName); // 創建查詢索引,參數productindex表示要查詢的索引庫為productindex SearchRequestBuilder searchRequestBuilder = client .prepareSearch("productindex"); // 設置查詢索引類型,setTypes("productType1", "productType2","productType3"); // 用來設定在多個類型中搜索 searchRequestBuilder.setTypes("productIndex"); // 設置查詢類型 1.SearchType.DFS_QUERY_THEN_FETCH = 精確查詢 2.SearchType.SCAN = 掃描查詢,無序 searchRequestBuilder.setSearchType(SearchType.DFS_QUERY_THEN_FETCH); // 設置查詢關鍵詞 searchRequestBuilder .setQuery(QueryBuilders.fieldQuery("title", "Acer")); // 查詢過濾器過濾價格在4000-5000內 這里范圍為[4000,5000]區間閉包含,搜索結果包含價格為4000和價格為5000的數據 searchRequestBuilder.setFilter(FilterBuilders.rangeFilter("price") .from(4000).to(5000)); // 分頁應用 searchRequestBuilder.setFrom(0).setSize(60); // 設置是否按查詢匹配度排序 searchRequestBuilder.setExplain(true); //設置高亮顯示 searchRequestBuilder.addHighlightedField("title"); searchRequestBuilder.setHighlighterPreTags("<span style=\"color:red\">"); searchRequestBuilder.setHighlighterPostTags("</span>"); // 執行搜索,返回搜索響應信息 SearchResponse response = searchRequestBuilder.execute().actionGet(); //獲取搜索的文檔結果 SearchHits searchHits = response.getHits(); SearchHit[] hits = searchHits.getHits(); ObjectMapper mapper = new ObjectMapper(); for (int i = 0; i < hits.length; i++) { SearchHit hit = hits[i]; //將文檔中的每一個對象轉換json串值 String json = hit.getSourceAsString(); //將json串值轉換成對應的實體對象 Product product = mapper.readValue(json, Product.class); //獲取對應的高亮域 Map<String, HighlightField> result = hit.highlightFields(); //從設定的高亮域中取得指定域 HighlightField titleField = result.get("title"); //取得定義的高亮標簽 Text[] titleTexts = titleField.fragments(); //為title串值增加自定義的高亮標簽 String title = ""; for(Text text : titleTexts){ title += text; } //將追加了高亮標簽的串值重新填充到對應的對象 product.setTitle(title); //打印高亮標簽追加完成后的實體對象 System.out.println(product); } System.out.println("search success .."); }
程序運行結果:
[id=8,title=宏基<span style="color:red">Acer</span>,description=宏基Acer蜂鳥系列,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蜂鳥系列,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蜂鳥系列,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>樂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>樂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>樂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>樂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>樂4,description=<null>,price=4012.0,onSale=false,type=1,createDate=Mon Sep 30 16:35:23 CST 2013]
從程序執行結果中我們可以看到,我們定義的高亮標簽已經追加到指定的域上了.
當搜索索引的時候,你搜索關鍵字包含了特殊字符,那么程序就會報錯
// fieldQuery 這個必須是你的索引字段哦,不然查不到數據,這里我只設置兩個字段 id ,title String title = "title+-&&||!(){}[]^\"~*?:\\"; title = QueryParser.escape(title);// 主要就是這一句把特殊字符都轉義,那么lucene就可以識別 searchRequestBuilder.setQuery(QueryBuilders.fieldQuery("title", title));
轉載請注明出處:[http://www.cnblogs.com/dennisit/p/3363851.html]