Elasticsearch 是一个分布式、高扩展、高实时的搜索与数据分析引擎。它能很方便的使大量数据具有搜索、分析和探索的能力。
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put/post请求：
http://localhost:9200/索引库名称{ "settings":{ "index":{ "number_of_shards":1, # 分片数量，存储到不同的节点，提高处理能力和高可用性 刚开始是一个 这里没有集成 "number_of_replicas":0 # 每个节点的副本数量，提高 高可用性 } } } get http://localhost:9200/索引库名称 查询创建索引的信息 2.post http://localhost:9200/索引库名称/类型名称/_mapping post 请求：http://localhost:9200/xc_course/doc/_mapping ~~~java { "properties": { "name": { "type": "text" // varchar }, "description": { "type": "text" }, "studymodel": { "type": "keyword" } } } ~ 3.put 或Post http://localhost:9200/xc_course/doc/id值 （如果不指定id值ES会自动生成ID） http://localhost:9200/xc_course/doc/1 java { "name":"Bootstrap开发框架", "description":"Bootstrap是由Twitter推出的一个前台页面开发框架，在行业之中使用较为广泛。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":"201001" } 4.根据课程id查询文档 发送：get http://localhost:9200/xc_course/doc/1 5. 发送 get http://localhost:9200/xc_course/doc/_search 查询全部的数据 6. 查询名称中包括spring 关键字的的记录 发送：get http://localhost:9200/xc_course/doc/_search?q=name:bootstrap 7.post 发送：localhost:9200/_analyze { "text":"郭", --这里没有写到main.dic文件中去就是一个一个的字 "analyzer":"ik_max_word" } {"text":"测试分词器，后边是测试内容：spring cloud实战", "analyzer":"ik_max_word" -- 分词器 精确一点 "analyzer":"ik_smart" -- 分词器 大体一下 } 8.GET： http://localhost:9200/(不止一个index那就要指定名字)_mapping 就是查看index 所有的属性和字段 { "gsx_frank": { "mappings": { "doc": { "properties": { "description": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "name": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "studymodel": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } } } } } } } body 请求体中的 application/json 9.delete请求：`http://localhost:9200/索引库名称` analyzer和search_analyzer 的区别 说明 分析器（analyzer）主要有两种情况会被使用： 插入文档时，将text类型的字段做分词然后插入倒排索引，。 在查询时，先对要查询的text类型的输入做分词，再去倒排索引搜索。 在索引（即插入文档）时，只会去看字段有没有定义analyzer，有定义的话就用定义的，没定义就用ES预设的。 在查询时，会先去看字段有没有定义search_analyzer，如果没有定义，就去看有没有analyzer，再没有定义，才会去使用ES预设的。 10. index 通过index属性指定是否索引。 默认为index=true，即要进行索引，只有进行索引才可以从索引库搜索到。 但是也有一些内容不需要索引，比如：商品图片地址只被用来展示图片，不进行搜索图片，此时可以将index设置为false。 删除索引，重新创建映射，将pic的index设置为false，尝试根据pic去搜索，结果搜索不到数据 "pic": { "type": "text", "index":false -- 这个字段就不可以被查到了 } 11. keyword关键字字段 上边介绍的text文本字段在映射时要设置分词器，keyword字段为关键字字段，通常搜索keyword是按照整体搜索，所以创建keyword字段的索引时是不进行分词的，比如：邮政编码、手机号码、身份证等。keyword字段通常用于过虑、排序、聚合等。 "price": { "type": "scaled_float", "scaling_factor": 100 比例因子 price*100 四首五入的去数值 },
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。
package com.guoshuxiang.service;
import org.elasticsearch.action.admin.indices.create.CreateIndexRequest;
import org.elasticsearch.action.admin.indices.create.CreateIndexResponse;
import org.elasticsearch.action.admin.indices.delete.DeleteIndexRequest;
import org.elasticsearch.action.delete.DeleteRequest;
import org.elasticsearch.action.delete.DeleteResponse;
import org.elasticsearch.action.get.GetRequest;
import org.elasticsearch.action.get.GetResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.index.IndexResponse;
import org.elasticsearch.action.support.master.AcknowledgedResponse;
import org.elasticsearch.action.update.UpdateRequest;
import org.elasticsearch.action.update.UpdateResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.xcontent.XContentType;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.HashMap;
import java.util.Map;
@Service
public class EsService {
@Autowired
private RestHighLevelClient client;
/**
* index 和添加映射放 在 一起的
*
* @throws Exception
*/
public void createIndex() throws Exception {
// 创建一个index
CreateIndexRequest createIndexRequest = new CreateIndexRequest("zg_love");
// 设置一个 微服务数量初始 1 备份数量 初始 0
createIndexRequest.settings(Settings.builder().put("number_of_shards", "1").put("number_of_replicas", "0"));
createIndexRequest.mapping("doc", "{\n" +
"\t\"properties\": {\n" +
"\t\t\"name\": {\n" +
"\t\t\t\"type\": \"text\",\n" +
"\t\t\t\"analyzer\": \"ik_max_word\",\n" +
"\t\t\t\"search_analyzer\": \"ik_smart\"\n" +
"\t\t},\n" +
"\t\t\"description\": {\n" +
"\t\t\t\"type\": \"text\",\n" +
"\t\t\t\"analyzer\": \"ik_max_word\",\n" +
"\t\t\t\"search_analyzer\": \"ik_smart\"\n" +
"\t\t},\n" +
"\t\t\"studymodel\": {\n" +
"\t\t\t\"type\": \"keyword\"\n" +
"\t\t},\n" +
"\t\t\"price\": {\n" +
"\t\t\t\"type\": \"float\"\n" +
"\t\t},\n" +
"\t\t\"timestamp\": {\n" +
"\t\t\t\"type\": \"date\",\n" +
"\t\t\t\"format\": \"yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||epoch_millis\"\n" +
"\t\t}\n" +
"\t}\n" +
"}", XContentType.JSON); // 指定传过的条件是json的格式
CreateIndexResponse createIndexResponse = client.indices().create(createIndexRequest, RequestOptions.DEFAULT);
System.out.println(createIndexResponse.isAcknowledged()); // 看看索引是否创建成功
}
/**
* 删除索引
*
* @throws Exception
*/
public void deleteIndex() throws Exception {
DeleteIndexRequest indexRequest = new DeleteIndexRequest("zg_love");
AcknowledgedResponse delete = client.indices().delete(indexRequest, RequestOptions.DEFAULT);
System.out.println(delete.isAcknowledged());
}
/**
* 创建index 和 删除 index 都要用到
* XXXXIndexRequest
* 直接对映射表操作的话就直接使用
* Get delete index update Request 的请求对(index)进行操作
*/
/**
* 添加一条数据
* @throws Exception
* CreateIndexRequest IndexRequest
* 前者是用来创建并配置索引的，后者是将数据与索引相关联，并且让数据可以被搜索。
*/
public void addDoc() throws Exception {
Map<String,Object> jsonMap = new HashMap<>();
jsonMap.put("name", "spring cloud实战");
jsonMap.put("description", "本课程主要从四个章节进行讲解： 1.微服务架构入门 2.spring cloud基础入门 3.实战Spring Boot 4.注册中心eureka。");
jsonMap.put("studymodel", "201001");
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
jsonMap.put("timestamp", dateFormat.format(new Date()));
jsonMap.put("price", 5.6f);
// 添加数据的请求 index doc 1 不指定的话会自动添加一个
IndexRequest indexRequest = new IndexRequest("zg_love","doc","1");
indexRequest.source(jsonMap); // 数据源要放进去 要把条件放进去
IndexResponse indexResponse = client.index(indexRequest, RequestOptions.DEFAULT);
System.out.println(indexResponse.status());
}
/**
* 修改一条数据
* @throws Exception
*/
public void update() throws Exception {
UpdateRequest updateRequest = new UpdateRequest("zg_love","doc","1");
Map<String,Object> jsonMap = new HashMap<>();
jsonMap.put("name","spring love you");
updateRequest.doc(jsonMap); // 更新是doc的方法来使用的
UpdateResponse updateResponse = client.update(updateRequest, RequestOptions.DEFAULT);
System.out.println(updateResponse.status());
}
/**
* 得到一条数据
* @throws Exception
*/
public void get() throws Exception{
GetRequest getRequest = new GetRequest("zg_love","doc","1");
// index 中存一条数据的就是 document -> 里面有好多 field的 字段
GetResponse documentFields = client.get(getRequest, RequestOptions.DEFAULT);
Map<String, Object> sourceAsMap = documentFields.getSourceAsMap();
System.out.println(sourceAsMap);
}
/**
* 删除一条数据
* @throws Exception
*/
public void delete() throws Exception{
DeleteRequest deleteRequest = new DeleteRequest("zg_love","doc","1");
DeleteResponse deleteResponse = client.delete(deleteRequest, RequestOptions.DEFAULT);
System.out.println(deleteResponse.status());
}
}
下面开始使用post 请求来查询数据 都是json 格式的形式来操作的
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": {} // 换成java 代码来使用 在这里
}
}
{
"from": 0,
"size": 1,
"query": {
"match_all": {}
},
"_source": ["name", "studymodel"]
}
//设置分页参数 这几个参数是同级的 {}
searchSourceBuilder.from((index - 1) * size);
searchSourceBuilder.size(size);
{
"query": {
"term": {
"name": "java" //%java%
}
},
"_source": ["name", "studymodel"]
}
//设置查询方式 (精准查询) %201002%
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", "201002");
{
"query": {
"terms": {
"price": [38.6,68.6] // 可以有多个值
}
},
"_source": ["name", "studymodel"]
}
// 这里有可变参数，不止一条数据 单个字段的多值查询
QueryBuilders.termsQuery("studymodel", stus); // 这里放的是数组
{
"query": {
"match": {
"description": {
"query": "spring框架",
"operator": "or",
"minimum_should_match": "80%"
}
}
}
}
MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("description", "spring开发框架");// 分词是中文和英文的状态小 ， text 类型 并且设置了 ik分词器才可以的
matchQueryBuilder.operator(Operator.OR); // 指定操作是 or 多个条件满足一个就行了
matchQueryBuilder.minimumShouldMatch("80%"); // 提高精准度
{
"query": {
"multi_match": {
"query": "spring css",
"minimum_should_match": "50%",
"fields": ["name^10", "description"]
}
}
//设置查询方式 (分词查询)
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders
.multiMatchQuery("spring框架", "name", "description"); // text field 参数
// 给field 增加 权重
multiMatchQueryBuilder.field("name", 10);
{
"query": {
"bool": {
"must": [{ // 还有可能是 should
"multi_match": {
"query": "spring框架",
"minimum_should_match": "50%",
"fields": ["name^10", "description"]
}
}, {
"term": {
"studymodel": "201002"
}
}]
}
}
}
// 构建boolean的条件
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
//条件一
if (!StringUtils.isEmpty(keyword)) {
// 多列查询
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keyword, "name", "description");
// 设置权重
multiMatchQueryBuilder.minimumShouldMatch("50%");
// 分词反满一个就行
multiMatchQueryBuilder.operator(Operator.OR);
// and 的关系 是并列下一个条件的
boolQueryBuilder.must(multiMatchQueryBuilder);
}
//条件二
if (!StringUtils.isEmpty(studymodel)) {
// 精确查询结果
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("studymodel", studymodel);
// and 构建多条件
boolQueryBuilder.must(termQueryBuilder);
}
{
// 这么多要操作的filed
"_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
}
}
}]
}
}
}
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("price"); // 这里是查询条件
rangeQueryBuilder.gte(min).lte(max); // 这里是最大最小的小于最大的
boolQueryBuilder.filter(rangeQueryBuilder); // 添加到过滤其中
"highlight": { // 这里和条件是一个级别的 最后都要放到 条件收集器中
"pre_tags": ["<span style=’color:red;’>"],
"post_tags": ["</span>"],
"fields": {
"name": {},
"description": {}
}
}
//设置高亮对象
HighlightBuilder highlightBuilder = new HighlightBuilder(); // 开头标签
highlightBuilder.preTags("<span style='color:red;'>");
highlightBuilder.postTags("</span>"); // 后面的标签
highlightBuilder.fields().add(new HighlightBuilder.Field("name")); // 添加一个给高亮的条件
highlightBuilder.fields().add(new HighlightBuilder.Field("description"));
searchSourceBuilder.highlighter(highlightBuilder); //最后将高亮并列在查询条件中
//获取高亮数据
Map<String, HighlightField> fieldMap = hit.getHighlightFields(); // 获取到键值对
HighlightField nameField = fieldMap.get("name"); //获取到关键的字
if (nameField != null) { // 不为空的
StringBuffer nameSbf = new StringBuffer(); //
Text[] fragments = nameField.fragments(); // 取到那个一满足的字段
for (Text text : fragments) {
nameSbf.append(text.toString()); // 循环满足的去拼接字符
}
course.setName(nameSbf.toString()); // 最后添加到字段类型中去
}
"sort": [{
"studymodel": "desc"
}, {
"price": "asc"
}]
//添加排序
searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC));
// 排序调用 sort() filed的条件对象 在调用 升序和降序
searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.DESC));
searchSourceBuilder.aggregation(AggregationBuilders.terms("brandGroup").field("brand_name").size(50));
public void all() throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder sourceBuilder = new SearchSourceBuilder();
MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
sourceBuilder.query(matchAllQueryBuilder);
searchRequest.source(sourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits(); //一共有多少条数据
System.out.println("总的记录是" + totalHits);
SearchHit[] searchHits = hits.getHits();//具体存放数据的地方
for (SearchHit hit : searchHits) {
String id = hit.getId();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
System.out.println(sourceAsMap);
}
}
/**
* 获取分页的数据 分页 limit 是一个大的函数 和条件是同级关系
*
* @param index 初始页码
* @param size 每页大小
* @throws Exception
*/
public void page(Integer index, Integer size) throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
// 构建大的条件
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.from((index - 1) * size);
searchSourceBuilder.size(size);
MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
searchSourceBuilder.query(matchAllQueryBuilder); // 封装的条件
searchRequest.source(searchSourceBuilder); // 最后条件放进去
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总的条数" + totalHits);
SearchHit[] hitsHits = hits.getHits();
for (SearchHit hit : hitsHits) {
String id = hit.getId();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
System.out.println(sourceAsMap);
}
}
/**
* 精确查询就是这个数据必须在一起,才可以查到一条数据不然是找到不到数据的
*
* @throws Exception
*/
public void term() throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("name", "spring");
searchSourceBuilder.query(termQueryBuilder);
// 指定要查询的字段
searchSourceBuilder.fetchSource(new String[]{"name", "studymodel", "price"}, null);
searchRequest.source(searchSourceBuilder); // 最后一定要带上条件啊不然就会查出全部的数据
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总的数据 : " + totalHits + "条");
SearchHit[] hitsHits = hits.getHits();
for (SearchHit hit : hitsHits) {
String id = hit.getId();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
System.out.println(sourceAsMap);
}
}
/**
* 单个列的精确查询
*
* @throws Exception
*/
public void terms() throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 多条件精确查询数据 字段 具体的字 ... 可变参数 这里的数据
TermsQueryBuilder termsQueryBuilder = QueryBuilders.termsQuery("name", "cloud");
searchSourceBuilder.query(termsQueryBuilder);
searchRequest.source(searchSourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总数据量:" + totalHits);
SearchHit[] searchHits = hits.getHits();
for (SearchHit hit : searchHits) {
String id = hit.getId();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
System.out.println(sourceAsMap);
}
}
/**
* 分词查询数据 必须是text 类型的数据才可以的
*
* @throws Exception
*/
public void match() throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 分子是match 来查询的
MatchQueryBuilder matchQueryBuilder = QueryBuilders.matchQuery("description", "spring开发入门");
matchQueryBuilder.operator(Operator.OR); // 默认就是 or的 关系 这里是分开的词有一个满足就行了
matchQueryBuilder.minimumShouldMatch("80%"); // 3 * 0.8 = 2.4 向下取整 2 至少有两个关键词才可以的
searchSourceBuilder.query(matchQueryBuilder);
searchRequest.source(searchSourceBuilder);
//执行请求获取响应
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总数据量:" + totalHits);
SearchHit[] searchHits = hits.getHits();
for (SearchHit hit : searchHits) {
String id = hit.getId();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
System.out.println(sourceAsMap);
}
}
/**
* 多列分词查询
*
* @throws Exception
*/
public void mutilMatch() throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// 这个词在两个关键字中来写啊
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery("实战语言", "name", "description");
multiMatchQueryBuilder.field("name", 10); // 扩大数据提高分数 优先在最前面
searchSourceBuilder.query(multiMatchQueryBuilder);
searchRequest.source(searchSourceBuilder);
//执行请求获取响应
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总数据量:" + totalHits);
SearchHit[] searchHits = hits.getHits();
for (SearchHit hit : searchHits) {
String id = hit.getId();
float score = hit.getScore();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
sourceAsMap.put("score", score);
System.out.println(sourceAsMap);
}
}
/**
* 注意：range 和 term一次只能对一个 Field 设置范围过虑。 不可以是多个
* @param keyword 分词的关键字
* @param studymodel 精确查询的关键字
* @throws Exception
*/
public void bool(String keyword, String studymodel) throws Exception {
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
// boolean 这是大条件
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
// 这里逻辑相反
if (!StringUtils.isEmpty(keyword)) { //多列分词查询
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keyword, "name", "description");
multiMatchQueryBuilder.minimumShouldMatch("50%");
multiMatchQueryBuilder.operator(Operator.OR);
multiMatchQueryBuilder.field("description",10);
boolQueryBuilder.must(multiMatchQueryBuilder); //
} // must 是全都满足条件的 上下两个条件都满足才行的
if (!StringUtils.isEmpty(studymodel)) { // 精确查询
TermsQueryBuilder termQueryBuilder = QueryBuilders.termsQuery("studymodel", studymodel);
boolQueryBuilder.must(termQueryBuilder);
}
searchSourceBuilder.query(boolQueryBuilder);
searchRequest.source(searchSourceBuilder);
//执行请求获取响应
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总数据量:" + totalHits);
SearchHit[] searchHits = hits.getHits();
for (SearchHit hit : searchHits) {
String id = hit.getId();
float score = hit.getScore();
Map<String, Object> sourceAsMap = hit.getSourceAsMap();
sourceAsMap.put("id", id);
sourceAsMap.put("score",score);
System.out.println(sourceAsMap);
}
}
public List<Course> filter(String keyword, String studymodel, Double min, Double max) throws Exception{
SearchRequest searchRequest = new SearchRequest("zg_love");
searchRequest.types("doc");
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
// 这里是原始数据 在这个数据上开始过滤数据
if (! StringUtils.isEmpty(keyword)){
MultiMatchQueryBuilder multiMatchQueryBuilder = QueryBuilders.multiMatchQuery(keyword, "name", "description");
multiMatchQueryBuilder.minimumShouldMatch("50%");
multiMatchQueryBuilder.field("description",10);
boolQueryBuilder.must(multiMatchQueryBuilder);
}
if(!StringUtils.isEmpty(studymodel)){
TermsQueryBuilder termsQueryBuilder = QueryBuilders.termsQuery("studymodel", studymodel);
boolQueryBuilder.filter(termsQueryBuilder);
}
if (min != null && max != null){
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("price");
rangeQueryBuilder.gte(min).lte(max);
boolQueryBuilder.filter(rangeQueryBuilder);
}
// 排序这是一个方法 在这里 所以直接写在 大的条件构造器中
searchSourceBuilder.sort(new FieldSortBuilder("studymodel").order(SortOrder.DESC));
searchSourceBuilder.sort(new FieldSortBuilder("price").order(SortOrder.ASC));
HighlightBuilder highlightBuilder = new HighlightBuilder();
highlightBuilder.preTags("<span style='color:red;'>");
highlightBuilder.postTags("</span>");
//
// //搜索 数据 另一种写法
// SearchRequestBuilder searchRequestBuilder = client.prepareSearch("blog2").
// setTypes("article").setQuery(QueryBuilders.termQuery("title","搜索 "));
// //高亮定义
// searchRequestBuilder.addHighlightedField("title");//对title字段进行高亮显示
// searchRequestBuilder.setHighlighterPreTags("<em>");//前置元素
// searchRequestBuilder.setHighlighterPostTags("</em>");//后置元素
// SearchResponse searchResponse = searchRequestBuilder.get();
// 这里用自己还是不行的 还要用内名对象来操作
highlightBuilder.fields().add(new HighlightBuilder.Field("name"));
highlightBuilder.fields().add(new HighlightBuilder.Field("description"));
searchSourceBuilder.query(boolQueryBuilder);
searchSourceBuilder.highlighter(highlightBuilder); // 将高亮放进去
searchRequest.source(searchSourceBuilder);
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
// 如果要写前端的话这里的展示数据就不要写了
SearchHits hits = searchResponse.getHits();
long totalHits = hits.getTotalHits();
System.out.println("总数据量: " + totalHits);
SearchHit[] searchHits = hits.getHits();
List<Course> list = new ArrayList<>();
for (SearchHit hit : searchHits) {
String id = hit.getId();
String json = hit.getSourceAsString();
// 里面的字段一一对应赋值
Course course = JSON.parseObject(json, Course.class);
// 这里是满足高亮的数据
Map<String, HighlightField> highlightFields = hit.getHighlightFields();
HighlightField nameField = highlightFields.get("name");
if (nameField != null){
StringBuffer nameBuf = new StringBuffer();
// 获取到原有内容中 每个高亮显示 集中位置fragment就是高亮片段 可能不止有一处高亮
Text[] fragments = nameField.fragments();
//
for (Text text : fragments) {
nameBuf.append(text.toString());
}
course.setName(nameBuf.toString());
}
HighlightField description = highlightFields.get("description");
if (description != null){
StringBuffer dSbf = new StringBuffer();
// text 类型的数据 文本类型要转化为String 在java中使用
Text[] text = description.fragments();
for (Text t : text) {
dSbf.append(t.toString());
}
course.setName(dSbf.toString());
}
course.setId(id);
list.add(course);
}
return list;
}
