1 依赖
4.0.0
spring-data-elasticsearch
org.springframework.boot
spring-boot-starter-parent
2.1.16.RELEASE
1.8
org.springframework.boot
spring-boot-starter-data-elasticsearch
com.alibaba
fastjson
1.2.76
org.projectlombok
lombok
true
org.springframework.boot
spring-boot-starter-test
test
2 配置文件
application.yml
server:
port: 20001
spring:
application:
name: elastic-search
data:
elasticsearch:
cluster-name: my-application
# 注意这里使用的是TransportClient 连接的是ES的TCP端口,而非ES的http端口
cluster-nodes: 127.0.0.1:9300
3 JavaBean
/**
* 索引库对应实体类
* 创建索引库信息使用注解:@Document
* indexName:索引库名
* type:类型
* shards:分片 默认5
* replicas:副本 默认1
* 指定mapping需要在field上添加@Id和@Field注解
* type:类型
* analyzer:分词器
* index:是否创建索引
*/
@Data
@AllArgsConstructor
@NoArgsConstructor
@Document(indexName = "goods", type = "_doc", shards = 3, replicas = 1)
public class Goods implements Serializable {
@Id
private Long id;
@Field(type = FieldType.Text,analyzer = "ik_max_word")
private String title; //标题
@Field(type = FieldType.Keyword)
private String category;// 分类
@Field(type = FieldType.Keyword)
private String brand; // 品牌
@Field(type = FieldType.Double)
private Double price; // 价格
@Field(type = FieldType.Keyword,index = false)
private String images; // 图片地址
}
4 使用ElasticsearchTemplate
操作索引库
对elasticsearch
的操作可以通过ElasticsearchTemplate
来进行
@RunWith(SpringRunner.class)
@SpringBootTest
public class ElasticSearchTest {
@Autowired
private ElasticsearchTemplate template;
@Autowired
private GoodsRepository goodsRepository;
/**
* 创建索引库
* 实体类的field上没加Id和Field注解时不会创建Mapping
*/
@Test
public void testCreateIndex(){
boolean result = template.createIndex(Goods.class);
System.out.print("创建索引库结果为" + result);
}
/**
* 新增映射
*/
@Test
public void testCreateMapping(){
boolean result = template.putMapping(Goods.class);
System.out.println("创建mapping结果为"+ result);
}
}
5 ElasticsearchRepository
ElasticsearchRepository
封装了基本的CRUD方法,可以通过继承ElasticsearchRepository
来使用
// ElasticsearchRepository T 为要操作的类型 ID为主键类型
@Repository
public interface GoodsRepository extends ElasticsearchRepository {
}
5.1 基本CRUD操作
/**
* 向索引库新增文档
*/
@Test
public void testAddDoc(){
Goods goods = new Goods(7L, "小米电视4A", " 电视",
"小米", 5699.00, "/13123.jpg");
goodsRepository.save(goods);
}
@Test
public void testBatchAddDoc(){
List list = new ArrayList<>();
list.add(new Goods(2L, "坚果手机R1", "手机", "锤子", 3699.00, "/13123.jpg"));
list.add(new Goods(3L, "华为META10", "手机", "华为", 4499.00, "/13123.jpg"));
list.add(new Goods(4L, "小米Mix2S", "手机", "小米", 4299.00, "/13123.jpg"));
list.add(new Goods(5L, "荣耀V10", "手机", "华为", 2799.00, "/13123.jpg"));
list.add(new Goods(6L, "小米手机7", "手机", "小米", 3299.00, "/13123.jpg"));
goodsRepository.saveAll(list);
System.out.println("批量新增文档成功");
}
/**
* 根据id查询文档
*/
@Test
public void testQueryById(){
Optional goodsOptional = goodsRepository.findById(1L);
System.out.println(goodsOptional.orElse(null));
}
/**
* 更新文档
*/
@Test
public void testUpdateDoc(){
Goods goods = new Goods(1L, "小米手机10Pro", " 手机",
"小米", 9999.00, "http://image.leyou.com/13123.jpg");
goodsRepository.save(goods);
System.out.println("更新文档成功");
}
/**
* 查询所有文档
*/
@Test
public void queryAllDoc(){
Iterable allGoods = goodsRepository.findAll();
allGoods.forEach(goods -> System.out.println(goods));
}
/**
* 根据文档id删除
*/
@Test
public void testDeleteDocById(){
goodsRepository.deleteById(6L);
System.out.println("根据id删除成功");
}
5.2 自定义查询
Keyword | Sample | Elasticsearch Query String |
---|---|---|
And |
findByNameAndPrice |
{"bool" : {"must" : [ {"field" : {"name" : "?"}}, {"field" : {"price" : "?"}} ]}} |
Or |
findByNameOrPrice |
{"bool" : {"should" : [ {"field" : {"name" : "?"}}, {"field" : {"price" : "?"}} ]}} |
Is |
findByName |
{"bool" : {"must" : {"field" : {"name" : "?"}}}} |
Not |
findByNameNot |
{"bool" : {"must_not" : {"field" : {"name" : "?"}}}} |
Between |
findByPriceBetween |
{"bool" : {"must" : {"range" : {"price" : {"from" : ?,"to" : ?,"include_lower" : true,"include_upper" : true}}}}} |
LessThanEqual |
findByPriceLessThan |
{"bool" : {"must" : {"range" : {"price" : {"from" : null,"to" : ?,"include_lower" : true,"include_upper" : true}}}}} |
GreaterThanEqual |
findByPriceGreaterThan |
{"bool" : {"must" : {"range" : {"price" : {"from" : ?,"to" : null,"include_lower" : true,"include_upper" : true}}}}} |
Before |
findByPriceBefore |
{"bool" : {"must" : {"range" : {"price" : {"from" : null,"to" : ?,"include_lower" : true,"include_upper" : true}}}}} |
After |
findByPriceAfter |
{"bool" : {"must" : {"range" : {"price" : {"from" : ?,"to" : null,"include_lower" : true,"include_upper" : true}}}}} |
Like |
findByNameLike |
{"bool" : {"must" : {"field" : {"name" : {"query" : "?*","analyze_wildcard" : true}}}}} |
StartingWith |
findByNameStartingWith |
{"bool" : {"must" : {"field" : {"name" : {"query" : "?*","analyze_wildcard" : true}}}}} |
EndingWith |
findByNameEndingWith |
{"bool" : {"must" : {"field" : {"name" : {"query" : "*?","analyze_wildcard" : true}}}}} |
Contains/Containing |
findByNameContaining |
{"bool" : {"must" : {"field" : {"name" : {"query" : "**?**","analyze_wildcard" : true}}}}} |
In |
findByNameIn(Collectionnames) |
{"bool" : {"must" : {"bool" : {"should" : [ {"field" : {"name" : "?"}}, {"field" : {"name" : "?"}} ]}}}} |
NotIn |
findByNameNotIn(Collectionnames) |
{"bool" : {"must_not" : {"bool" : {"should" : {"field" : {"name" : "?"}}}}}} |
Near |
findByStoreNear |
Not Supported Yet ! |
True |
findByAvailableTrue |
{"bool" : {"must" : {"field" : {"available" : true}}}} |
False |
findByAvailableFalse |
{"bool" : {"must" : {"field" : {"available" : false}}}} |
OrderBy |
findByAvailableTrueOrderByNameDesc |
{"sort" : [{ "name" : {"order" : "desc"} }],"bool" : {"must" : {"field" : {"available" : true}}}} |
repository修改
@Repository
public interface GoodsRepository extends ElasticsearchRepository {
List findByCategory(String category);
List findByBrand(String brand);
List findByPriceBetween(Double from,Double to);
List findByTitleAndCategory(String title, String category);
}
使用自定义查询
/**
* 自定义查询
*/
@Test
public void testConditionSearch(){
//List goodsList = goodsRepository.findByBrand("锤子");
//List goodsList = goodsRepository.findByPriceBetween(1000D, 4000D);
List goodsList = goodsRepository.findByTitleAndCategory("小米", "手机");
goodsList.forEach(goods -> System.out.println(goods));
}
/**
* 分页搜索
*/
@Test
public void testPageSearch(){
//构建分页排序对象
int page = 0;
int size = 5;
Sort sort = Sort.by(Sort.Direction.DESC, "price");
PageRequest pageRequest = PageRequest.of(0, 3, sort);
//构建查询对象
MatchAllQueryBuilder matchAllQueryBuilder = QueryBuilders.matchAllQuery();
//查询
Page goodsPage = goodsRepository.search(matchAllQueryBuilder, pageRequest);
List goodsList = goodsPage.getContent();
goodsList.forEach(goods -> System.out.println(goods));
}
6 原生查询
一些较复杂的查询使用repository查询较困难,此时可使用原生查询
6.1 高亮查询
高亮查询的原理,就是将关键字使用css标签将查询结果中的关键词包起来.具体操作时需要自定义结果处理器
/**
* goods的自定义结果处理器:用于接收处理高亮搜索结果
*/
public class GoodsSearchResultMapper implements SearchResultMapper {
@Override
public AggregatedPage mapResults(SearchResponse searchResponse, Class aClass, Pageable pageable) {
//获取返回数据所需总命中数
long totalHits = searchResponse.getHits().totalHits;
//获取返回数据所需最大评分
float maxScore = searchResponse.getHits().getMaxScore();
//获取返回数据所需聚合结果
Aggregations aggregations = searchResponse.getAggregations();
//获取返回数据必要参数
String scrollId = searchResponse.getScrollId();
//返回结果
List content = new ArrayList<>();
SearchHit[] hits = searchResponse.getHits().getHits();
for (SearchHit hit : hits) {
//获取源数据
String sourceAsString = hit.getSourceAsString();
//源数据转对象
T goods = JSON.parseObject(sourceAsString, aClass);
//获取高亮属性
Map highlightFields = hit.getHighlightFields();
HighlightField titleHighlightField = highlightFields.get("title");
Text[] fragments = titleHighlightField.getFragments();
if (fragments != null && fragments.length > 0){
StringBuilder highlightFieldValue = new StringBuilder();
for (Text fragment : fragments) {
highlightFieldValue.append(fragment.toString());
}
//高亮字段覆盖源字段值
Goods item = (Goods) goods;
item.setTitle(highlightFieldValue.toString());
}
content.add(goods);
}
return new AggregatedPageImpl<>(content,pageable,totalHits,aggregations,scrollId,maxScore);
}
}
使用原生高亮查询
/**
* 原生查询:高亮
*/
@Test
public void testHighlight(){
//构建查询对象
QueryBuilder queryBuilder = QueryBuilders.matchQuery("title","电视");
//构建高亮字段对象
HighlightBuilder.Field highlightField = new HighlightBuilder.Field("title")
.preTags("")
.postTags("");
//使用原生查询:传入条件查询对象和高亮对象
NativeSearchQuery nativeSearchQuery = new NativeSearchQueryBuilder()
.withQuery(queryBuilder)
.withHighlightFields(highlightField)
.build();
//自定义结果处理对象
GoodsSearchResultMapper goodsSearchResultMapper = new GoodsSearchResultMapper();
AggregatedPage goodsAggregatedPage = template.queryForPage(nativeSearchQuery, Goods.class, goodsSearchResultMapper);
List goodsList = goodsAggregatedPage.getContent();
goodsList.forEach(goods -> System.out.println(goods));
}
6.2 聚合查询
/**
* 原生查询:聚合
*/
@Test
public void testAggregation(){
//构建查询条件对象
MatchAllQueryBuilder queryBuilder = QueryBuilders.matchAllQuery();
//构建聚合分组--桶:按照brand字段聚合为桶
AbstractAggregationBuilder agg = AggregationBuilders.terms("brand_agg") //指定分组名称
.field("brand");//指定分组字段
//添加子聚合--度量:每个桶内求价格平均值
agg.subAggregation(AggregationBuilders.avg("price_avg").field("price"));
//使用原生查询
NativeSearchQuery nativeSearchQuery = new NativeSearchQueryBuilder()
.withQuery(queryBuilder)
.addAggregation(agg).build();
AggregatedPage goodsAggregatedPage = template.queryForPage(nativeSearchQuery, Goods.class);
Terms brandAgg = (Terms) goodsAggregatedPage.getAggregation("brand_agg");
List buckets = brandAgg.getBuckets();
for (Terms.Bucket bucket : buckets) {
String brandName = bucket.getKeyAsString();
long docCount = bucket.getDocCount();
Avg priceAvg = bucket.getAggregations().get("price_avg");
double priceAvgValue = priceAvg.getValue();
System.out.println("品牌为[" + brandName + "]的商品数量为" + docCount + ",平均价格为" + priceAvgValue);
}
}