7搜索管理

7搜索管理

7.1 准备环境

7.1.1 创建映射

创建xc_course索引库。

创建如下映射

post：http://localhost:9200/xc_course/doc/_mapping

参考 “资料”–》搜索测试-初始化数据.txt

{ "properties": { "description": { "type": "text","analyzer": "ik_max_word","search_analyzer": "ik_smart" },"name": { "type": "text", "analyzer": "ik_max_word", "search_analyzer": "ik_smart" },"pic":{ "type":"text", "index":false }, "price": { "type": "float" },"studymodel": { "type": "keyword" },"timestamp": { "type": "date", "format": "yyyy‐MM‐dd HH:mm:ss||yyyy‐MM‐dd||epoch_millis" } } 
}

7.1.2 插入原始数据

向xc_course/doc中插入以下数据：

参考 “资料”–》搜索测试-初始化数据.txt

http://localhost:9200/xc_course/doc/1 {"name": "Bootstrap开发", "description": "Bootstrap是由Twitter推出的一个前台页面开发框架，是一个非常流行的开发框架，此框架集成了 多种页面效果。此开发框架包含了大量的CSS、JS程序代码，可以帮助开发者（尤其是不擅长页面开发的程序人员）轻松 的实现一个不受浏览器限制的精美界面效果。", "studymodel": "201002", "price":38.6, "timestamp":"2018‐04‐25 19:11:35", 		"pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg" 
}http://localhost:9200/xc_course/doc/2 {"name": "java编程基础","description": "java语言是世界第一编程语言，在软件开发领域使用人数最多。","studymodel": "201001", "price":68.6, "timestamp":"2018‐03‐25 19:11:35", "pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg" 
}http://localhost:9200/xc_course/doc/3 {"name": "spring开发基础", "description": "spring 在java领域非常流行，java程序员都在用。","studymodel": "201001","price":88.6, "timestamp":"2018‐02‐24 19:11:35", "pic":"group1/M00/00/00/wKhlQFs6RCeAY0pHAAJx5ZjNDEM428.jpg" 
}

7.1.3 简单搜索

简单搜索就是通过url进行查询，以get方式请求ES。

格式：get …/_search?q=…

q：搜索字符串。

例子：

?q=name:spring 搜索name中包括spring的文档。

7.3 DSL搜索

DSL(Domain Specifific Language)是ES提出的基于json的搜索方式，在搜索时传入特定的json格式的数据来完成不同的搜索需求。

DSL比URI搜索方式功能强大，在项目中建议使用DSL方式来完成搜索。

7.3.1 查询所有文档

查询所有索引库的文档。

发送：post http://localhost:9200/_search

查询指定索引库指定类型下的文档。（通过使用此方法）

发送：post http://localhost:9200/xc_course/doc/_search

{ "query": { "match_all": {} },"_source" : ["name","studymodel"] }

_source：source源过虑设置，指定结果中所包括的字段有哪些。

结果说明：

took：本次操作花费的时间，单位为毫秒。

timed_out：请求是否超时

_shards：说明本次操作共搜索了哪些分片

hits：搜索命中的记录

hits.total ： 符合条件的文档总数 hits.hits ：匹配度较高的前N个文档

hits.max_score：文档匹配得分，这里为最高分

_score：每个文档都有一个匹配度得分，按照降序排列。

_source：显示了文档的原始内容。

JavaClient：

@SpringBootTest 
@RunWith(SpringRunner.class) 
public class TestSearch { @Autowired RestHighLevelClient client; @Autowired RestClient restClient; //搜索type下的全部记录@Testpublic void testSearchAll() throws IOException, ParseException {//搜索请求对象SearchRequest searchRequest = new SearchRequest("xc_course");//指定类型searchRequest.types("doc");//搜索源构建对象SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();//搜索方式//matchAllQuery搜索全部searchSourceBuilder.query(QueryBuilders.matchAllQuery());//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});//向搜索请求对象中设置搜索源searchRequest.source(searchSourceBuilder);//执行搜索,向ES发起http请求SearchResponse searchResponse = client.search(searchRequest);//搜索结果SearchHits hits = searchResponse.getHits();//匹配到的总记录数long totalHits = hits.getTotalHits();//得到匹配度高的文档SearchHit[] searchHits = hits.getHits();//日期格式化对象SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");for(SearchHit hit:searchHits){//文档的主键String id = hit.getId();//源文档内容Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");//由于前边设置了源文档字段过虑，这时description是取不到的String description = (String) sourceAsMap.get("description");//学习模式String studymodel = (String) sourceAsMap.get("studymodel");//价格Double price = (Double) sourceAsMap.get("price");//日期Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));System.out.println(name);System.out.println(studymodel);System.out.println(description);}}
} 

7.3.2 分页查询

ES支持分页查询，传入两个参数：from和size。

form：表示起始文档的下标，从0开始。

size：查询的文档数量。

发送：post http://localhost:9200/xc_course/doc/_search

{"from" : 0, "size" : 1, "query": { "match_all": {} }, "_source" : ["name","studymodel"] }

JavaClient

SearchRequest searchRequest = new SearchRequest("xc_course"); 
searchRequest.types("xc_course"); 
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); 
searchSourceBuilder.query(QueryBuilders.matchAllQuery()); 
//分页查询，设置起始下标，从0开始 
searchSourceBuilder.from(0); 
//每页显示个数 
searchSourceBuilder.size(10); 
//source源字段过虑 
searchSourceBuilder.fetchSource(new String[]{"name","studymodel"}, new String[]{}); 
searchRequest.source(searchSourceBuilder); 
SearchResponse searchResponse = client.search(searchRequest); 

7.3.3 Term Query

Term Query为精确查询，在搜索时会整体匹配关键字，不再将关键字分词。

发送：post http://localhost:9200/xc_course/doc/_search

{ "query": { "term" : { "name": "spring" } },"_source" : ["name","studymodel"] }

上边的搜索会查询name包括“spring”这个词的文档。

JavaClient：

SearchRequest searchRequest = new SearchRequest("xc_course"); 
searchRequest.types("xc_course"); 
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); 
searchSourceBuilder.query(QueryBuilders.termQuery("name","spring")); 
//source源字段过虑 
searchSourceBuilder.fetchSource(new String[]{"name","studymodel"}, new String[]{}); 
searchRequest.source(searchSourceBuilder); 
SearchResponse searchResponse = client.search(searchRequest); 

7.3.4 根据id精确匹配

ES提供根据多个id值匹配的方法：

测试：

post： http://127.0.0.1:9200/xc_course/doc/_search

{ "query": { "ids" : { "type" : "doc", "values" : ["3", "4", "100"] } } }

JavaClient:

String[] split = new String[]{"1","2"}; 
List<String> idList = Arrays.asList(split); 
searchSourceBuilder.query(QueryBuilders.termsQuery("_id", idList)); 

7.3.5 match Query

1、基本使用

match Query即全文检索，它的搜索方式是先将搜索字符串分词，再使用各各词条从索引中搜索。

match query与Term query区别是match query在搜索前先将搜索关键字分词，再拿各各词语去索引中搜索。

发送：post http://localhost:9200/xc_course/doc/_search

{ "query": { "match" : { "description" : { "query" : "spring开发", "operator" : "or" } } } }

query：搜索的关键字，对于英文关键字如果有多个单词则中间要用半角逗号分隔，而对于中文关键字中间可以用

逗号分隔也可以不用。

operator：or 表示 只要有一个词在文档中出现则就符合条件，and表示每个词都在文档中出现则才符合条件。

上边的搜索的执行过程是：

1、将“spring开发”分词，分为spring、开发两个词

2、再使用spring和开发两个词去匹配索引中搜索。

3、由于设置了operator为or，只要有一个词匹配成功则就返回该文档。

JavaClient：

    //MatchQuery@Testpublic void testMatchQuery() throws IOException, ParseException {//搜索请求对象SearchRequest searchRequest = new SearchRequest("xc_course");//指定类型searchRequest.types("doc");//搜索源构建对象SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();//搜索方式//MatchQuerysearchSourceBuilder.query(QueryBuilders.matchQuery("description","spring开发框架").operator(Operator.OR));//设置源字段过虑,第一个参数结果集包括哪些字段，第二个参数表示结果集不包括哪些字段searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","timestamp"},new String[]{});//向搜索请求对象中设置搜索源searchRequest.source(searchSourceBuilder);//执行搜索,向ES发起http请求SearchResponse searchResponse = client.search(searchRequest);//搜索结果SearchHits hits = searchResponse.getHits();//匹配到的总记录数long totalHits = hits.getTotalHits();//得到匹配度高的文档SearchHit[] searchHits = hits.getHits();//日期格式化对象SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");for(SearchHit hit:searchHits){//文档的主键String id = hit.getId();//源文档内容Map<String, Object> sourceAsMap = hit.getSourceAsMap();String name = (String) sourceAsMap.get("name");//由于前边设置了源文档字段过虑，这时description是取不到的String description = (String) sourceAsMap.get("description");//学习模式String studymodel = (String) sourceAsMap.get("studymodel");//价格Double price = (Double) sourceAsMap.get("price");//日期Date timestamp = dateFormat.parse((String) sourceAsMap.get("timestamp"));System.out.println(name);System.out.println(studymodel);System.out.println(description);}}

2、minimum_should_match

上边使用的operator = or表示只要有一个词匹配上就得分，如果实现三个词至少有两个词匹配如何实现？

使用minimum_should_match可以指定文档匹配词的占比：

比如搜索语句如下：

{ "query": { "match" : { "description" : { "query" : "spring开发框架", "minimum_should_match": "80%" } } } }

“spring开发框架”会被分为三个词：spring、开发、框架

设置"minimum_should_match": "80%"表示，三个词在文档的匹配占比为80%，即3*0.8=2.4，向上取整得2，表

示至少有两个词在文档中要匹配成功。

对应的RestClient如下：

//匹配关键字 
searchSourceBuilder.query(QueryBuilders.matchQuery("description","spring开发框架").minimumShouldMatch("80%"));

7.3.6 multiQuery

上边学习的termQuery和matchQuery一次只能匹配一个Field，本节学习multiQuery，一次可以匹配多个字段。

1、基本使用

单项匹配是在一个field中去匹配，多项匹配是拿关键字去多个Field中匹配。

例子：

发送：post http://localhost:9200/xc_course/doc/_search

拿关键字 “spring css”去匹配name 和description字段。

{ "query": { "multi_match" : { "query" : "spring css", "minimum_should_match": "50%", "fields": [ "name", "description" ] }} }

2、提升boost

匹配多个字段时可以提升字段的boost（权重）来提高得分

例子：

提升boost之前，执行下边的查询：

{ "query": { "multi_match" : { "query" : "spring框架", "minimum_should_match": "50%", "fields": [ "name", "description" ] }} }

通过查询发现Bootstrap排在前边。

提升boost，通常关键字匹配上name的权重要比匹配上description的权重高，这里可以对name的权重提升。

{ "query": { "multi_match" : { "query" : "spring框架", "minimum_should_match": "50%", "fields": [ "name^10", "description" ] }} }

“name^10” 表示权重提升10倍，执行上边的查询，发现name中包括spring关键字的文档排在前边。

JavaClient:

MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring框架", "name", "description") .minimumShouldMatch("50%"); 
multiMatchQueryBuilder.field("name",10);//提升boost 

7.3.7 布尔查询

布尔查询对应于Lucene的BooleanQuery查询，实现将多个查询组合起来。

三个参数：

must：文档必须匹配must所包括的查询条件，相当于 “AND” should：文档应该匹配should所包括的查询条件其

中的一个或多个，相当于 “OR” must_not：文档不能匹配must_not所包括的该查询条件，相当于“NOT”

分别使用must、should、must_not测试下边的查询：

发送：POST http://localhost:9200/xc_course/doc/_search

{ "_source" : [ "name", "studymodel", "description"], "from" : 0, "size" : 1, "query": { "bool" : { "must":[{ "multi_match" : { "query" : "spring框架", "minimum_should_match": "50%", "fields": [ "name^10", "description" ] }},{ "term":{"studymodel" : "201001" } } ] } } }

must：表示必须，多个查询条件必须都满足。（通常使用must）

should：表示或者，多个查询条件只要有一个满足即可。

must_not：表示非。

JavaClient：

//BoolQuery，将搜索关键字分词，拿分词去索引库搜索 
@Test 
public void testBoolQuery() throws IOException { //创建搜索请求对象 SearchRequest searchRequest= new SearchRequest("xc_course"); searchRequest.types("doc"); //创建搜索源配置对象 SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); searchSourceBuilder.fetchSource(new String[]{"name","pic","studymodel"},new String[]{}); //multiQuery String keyword = "spring开发框架"; MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring框架", "name", "description") .minimumShouldMatch("50%"); multiMatchQueryBuilder.field("name",10); //TermQuery TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201001");//布尔查询 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); boolQueryBuilder.must(multiMatchQueryBuilder); boolQueryBuilder.must(termQueryBuilder); //设置布尔查询对象 searchSourceBuilder.query(boolQueryBuilder); searchRequest.source(searchSourceBuilder);//设置搜索源配置 SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); SearchHit[] searchHits = hits.getHits(); for(SearchHit hit:searchHits){ Map<String, Object> sourceAsMap = hit.getSourceAsMap(); System.out.println(sourceAsMap); } 
} 

7.3.8 过虑器

过虑是针对搜索的结果进行过虑，过虑器主要判断的是文档是否匹配，不去计算和判断文档的匹配度得分，所以过

虑器性能比查询要高，且方便缓存，推荐尽量使用过虑器去实现查询或者过虑器和查询共同使用。

过虑器在布尔查询中使用，下边是在搜索结果的基础上进行过虑：

{ "_source" : [ "name", "studymodel", "description","price"], "query": { "bool" : { "must":[{ "multi_match" : { "query" : "spring框架", "minimum_should_match": "50%", "fields": [ "name^10", "description" ] }} ],"filter": [ { "term": { "studymodel": "201001" }}, { "range": { "price": { "gte": 60 ,"lte" : 100}}} ] } } }

range：范围过虑，保留大于等于60 并且小于等于100的记录。

term：项匹配过虑，保留studymodel等于"201001"的记录。

注意：range和term一次只能对一个Field设置范围过虑。

client：

//布尔查询使用过虑器 
@Test 
public void testFilter() throws IOException { SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); //source源字段过虑 searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","description"}, new String[]{}); searchRequest.source(searchSourceBuilder); //匹配关键字 MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("spring框 架", "name", "description"); //设置匹配占比 multiMatchQueryBuilder.minimumShouldMatch("50%"); //提升另个字段的Boost值 multiMatchQueryBuilder.field("name",10); searchSourceBuilder.query(multiMatchQueryBuilder); //布尔查询 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); boolQueryBuilder.must(searchSourceBuilder.query()); //过虑 boolQueryBuilder.filter(QueryBuilders.termQuery("studymodel", "201001")); boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(60).lte(100)); SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { String index = hit.getIndex(); String type = hit.getType(); String id = hit.getId(); float score = hit.getScore(); String sourceAsString = hit.getSourceAsString(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); String name = (String) sourceAsMap.get("name"); String studymodel = (String) sourceAsMap.get("studymodel"); String description = (String) sourceAsMap.get("description"); System.out.println(name); System.out.println(studymodel); System.out.println(description); }
}

7.3.9 排序

可以在字段上添加一个或多个排序，支持在keyword、date、flfloat等类型上添加，text类型的字段上不允许添加排 序。

发送 POST http://localhost:9200/xc_course/doc/_search

过虑0–10元价格范围的文档，并且对结果进行排序，先按studymodel降序，再按价格升序

{ "_source" : [ "name", "studymodel", "description","price"], "query": { "bool" : { "filter": [ { "range": { "price": { "gte": 0 ,"lte" : 100}}} ] } }, "sort" : [ {"studymodel" : "desc" }, { "price" : "asc" } ] }

client：

@Test
public void testSort() throws IOException { SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); //source源字段过虑 searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","description"}, new String[]{}); searchRequest.source(searchSourceBuilder); //布尔查询 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); //过虑 boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100));//排序 searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC)); searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC)); SearchResponse searchResponse = client.search(searchRequest); SearchHits hits = searchResponse.getHits(); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { String index = hit.getIndex(); String type = hit.getType(); String id = hit.getId(); float score = hit.getScore(); String sourceAsString = hit.getSourceAsString(); Map<String, Object> sourceAsMap = hit.getSourceAsMap(); String name = (String) sourceAsMap.get("name"); String studymodel = (String) sourceAsMap.get("studymodel"); String description = (String) sourceAsMap.get("description"); System.out.println(name); System.out.println(studymodel); System.out.println(description); } 
} 

7.3.10 高亮显示

高亮显示可以将搜索结果一个或多个字突出显示，以便向用户展示匹配关键字的位置。

在搜索语句中添加highlight即可实现，如下：

Post： http://127.0.0.1:9200/xc_course/doc/_search

{ "_source" : [ "name", "studymodel", "description","price"], "query": { "bool" : { "must":[{ "multi_match" : { "query" : "开发框架", "minimum_should_match": "50%", "fields": [ "name^10", "description" ], "type":"best_fields" }} ],"filter": [ { "range": { "price": { "gte": 0 ,"lte" : 100}}} ] } }, "sort" : [{ "price" : "asc" } ],"highlight": { "pre_tags": ["<tag1>"], "post_tags": ["</tag2>"], "fields": { "name": {}, "description":{} } } }

client代码如下：

@Test
public void testHighlight() throws IOException { SearchRequest searchRequest = new SearchRequest("xc_course"); searchRequest.types("doc"); SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder(); //source源字段过虑 searchSourceBuilder.fetchSource(new String[]{"name","studymodel","price","description"}, new String[]{}); searchRequest.source(searchSourceBuilder); //匹配关键字 MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("开发", "name", "description"); searchSourceBuilder.query(multiMatchQueryBuilder); //布尔查询 BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery(); boolQueryBuilder.must(searchSourceBuilder.query()); //过虑 boolQueryBuilder.filter(QueryBuilders.rangeQuery("price").gte(0).lte(100)); //排序 searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC)); searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC)); //高亮设置 HighlightBuilder highlightBuilder = new HighlightBuilder(); highlightBuilder.preTags("<tag>");//设置前缀 highlightBuilder.postTags("</tag>");//设置后缀 // 设置高亮字段 highlightBuilder.fields().add(new HighlightBuilder.Field("name")); // highlightBuilder.fields().add(new HighlightBuilder.Field("description")); searchSourceBuilder.highlighter(highlightBuilder); SearchResponse searchResponse = client.search(searchRequest);SearchHits hits = searchResponse.getHits(); SearchHit[] searchHits = hits.getHits(); for (SearchHit hit : searchHits) { Map<String, Object> sourceAsMap = hit.getSourceAsMap(); //名称 String name = (String) sourceAsMap.get("name"); //取出高亮字段内容 Map<String, HighlightField> highlightFields = hit.getHighlightFields(); if(highlightFields!=null){ HighlightField nameField = highlightFields.get("name"); if(nameField!=null){ Text[] fragments = nameField.getFragments(); StringBuffer stringBuffer = new StringBuffer(); for (Text str : fragments) { stringBuffer.append(str.string()); }name = stringBuffer.toString(); } }String index = hit.getIndex(); String type = hit.getType(); String id = hit.getId(); float score = hit.getScore(); String sourceAsString = hit.getSourceAsString(); String studymodel = (String) sourceAsMap.get("studymodel"); String description = (String) sourceAsMap.get("description"); System.out.println(name); System.out.println(studymodel); System.out.println(description); } 
}