本篇文章给大家分享的是有关Spring data中elasticsearch如何使用,小编觉得挺实用的,因此分享给大家学习,希望大家阅读完这篇文章后可以有所收获,话不多说,跟着小编一起来看看吧。
1.添加依赖
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
2.application.yml
spring:
application:
name: search-service
data:
elasticsearch:
cluster-name: elasticsearch
cluster-nodes: 192.168.25.129:9300
3.实体类
@Data
@Document(indexName = "goods", type = "_doc", shards = 1, replicas = 0)
public class Goods {
@Idprivate Long id;
@Field(type = FieldType.text, analyzer = "ik_max_word")
private String all;
@Field(type = FieldType.keyword, index = false)
private String subTitle;private Long brandId;private Long cid1;private Long cid2;private Long cid3;private Date createTime;private List<Long> price;
@Field(type = FieldType.keyword, index = false)
private String skus;private Map<String, Object> specs;
}
@Document 作用在类,标记实体类为文档对象,一般有两个属性
indexName:对应索引库名称
type:对应在索引库中的类型
shards:分片数量,默认5
replicas:副本数量,默认1
@Id 作用在成员变量,标记一个字段作为id主键
@Field 作用在成员变量,标记为文档的字段,并指定字段映射属性:
type:字段类型,取值是枚举:FieldType
index:是否索引,布尔类型,默认是true
store:是否存储,布尔类型,默认是false
analyzer:分词器名称
二.、索引操作
首先注入ElasticsearchTemplate
@Resource
private ElasticsearchTemplate elasticsearchTemplate;
● 创建索引
elasticsearchTemplate.createIndex(Goods.class);
● 配置映射
elasticsearchTemplate.putMapping(Goods.class);
● 删除索引
//根据类
elasticsearchTemplate.deleteIndex(Goods.class);
//根据索引名
elasticsearchTemplate.deleteIndex("goods");
三、文档操作
1.定义接口。也是SpringData风格
public interface ItemRepository extends ElasticsearchRepository<Item,Long> {
}
2.注入
@Autowired
private ItemRepository itemRepository;
● 新增文档
Item item = new Item(1L, "小米手机7", " 手机",
"小米", 3499.00, "http://image.leyou.com/13123.jpg");
itemRepository.save(item);
● 批量新增
List<Item> list = new ArrayList<>();
list.add(new Item(2L, "坚果手机R1", " 手机", "锤子", 3699.00, "http://image.leyou.com/123.jpg"));
list.add(new Item(3L, "华为META10", " 手机", "华为", 4499.00, "http://image.leyou.com/3.jpg"));
// 接收对象集合,实现批量新增
itemRepository.saveAll(list);
四、 基本搜索
● 基本查询。
例:
// 查询全部,并安装价格降序排序
Iterable<Item> items = this.itemRepository.findAll(Sort.by(Sort.Direction.DESC, "price"));
items.forEach(item-> System.out.println(item));
● 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(Collection<String>names) | {"bool" : {"must" : {"bool" : {"should" : [ {"field" : {"name" : "?"}}, {"field" : {"name" : "?"}} ]}}}} |
NotIn | findByNameNotIn(Collection<String>names) | {"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}}}} |
例:
public interface ItemRepository extends ElasticsearchRepository<Item,Long> {
/**
* 根据价格区间查询
* @param price1
* @param price2
* @return
*/
List<Item> findByPriceBetween(double price1, double price2);
}
五、高级查询
● 词条查询
MatchQueryBuilder queryBuilder = QueryBuilders.matchQuery("all", "小米");
// 执行查询
Iterable<Goods> goods = this.goodsRepository.search(queryBuilder);
● 自定义查询
// 构建查询条件
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 添加基本的分词查询
queryBuilder.withQuery(QueryBuilders.matchQuery("all", "小米"));
// 执行搜索,获取结果
Page<Goods> goods = this.goodsRepository.search(queryBuilder.build());
// 打印总条数
System.out.println(goods.getTotalElements());
// 打印总页数
System.out.println(goods.getTotalPages());
● 分页查询
// 构建查询条件
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 添加基本的分词查询
queryBuilder.withQuery(QueryBuilders.termQuery("all", "手机"));
// 初始化分页参数
int page = 0;
int size = 3;
// 设置分页参数
queryBuilder.withPageable(PageRequest.of(page, size));
// 执行搜索,获取结果
Page<Goods> goods = this.goodsRepository.search(queryBuilder.build());
// 打印总条数
System.out.println(goods.getTotalElements());
// 打印总页数
System.out.println(goods.getTotalPages());
// 每页大小
System.out.println(goods.getSize());
// 当前页
System.out.println(goods.getNumber());
● 排序
// 构建查询条件
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 添加基本的分词查询
queryBuilder.withQuery(QueryBuilders.termQuery("all", "手机"));
// 排序
queryBuilder.withSort(SortBuilders.fieldSort("price").order(SortOrder.DESC));
// 执行搜索,获取结果
Page<Goods> goods = this.goodsRepository.search(queryBuilder.build());
// 打印总条数
System.out.println(goods.getTotalElements());
● 聚合为桶
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 不查询任何结果
queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{""}, null));
// 1、添加一个新的聚合,聚合类型为terms,聚合名称为brands,聚合字段为brand
queryBuilder.addAggregation(AggregationBuilders.terms("brands").field("brandId"));
// 2、查询,需要把结果强转为AggregatedPage类型
AggregatedPage<Goods> aggPage = (AggregatedPage<Goods>) this.goodsRepository.search(queryBuilder.build());
// 3、解析
// 3.1、从结果中取出名为brands的那个聚合,
// 因为是利用String类型字段来进行的term聚合,所以结果要强转为StringTerm类型
LongTerms agg = (LongTerms) aggPage.getAggregation("brands");
// 3.2、获取桶
List<LongTerms.Bucket> buckets = agg.getBuckets();
// 3.3、遍历
for (LongTerms.Bucket bucket : buckets) {
// 3.4、获取桶中的key,即品牌名称
System.out.println(bucket.getKeyAsString());
// 3.5、获取桶中的文档数量
System.out.println(bucket.getDocCount());
}
● 嵌套聚合,求平均值
NativeSearchQueryBuilder queryBuilder = new NativeSearchQueryBuilder();
// 不查询任何结果
queryBuilder.withSourceFilter(new FetchSourceFilter(new String[]{""}, null));
// 1、添加一个新的聚合,聚合类型为terms,聚合名称为brands,聚合字段为brand
queryBuilder.addAggregation(AggregationBuilders.terms("brands").field("brandId")
.subAggregation(AggregationBuilders.avg("priceAvg").field("price"))); // 在品牌聚合桶内进行嵌套聚合,求平均值
// 2、查询,需要把结果强转为AggregatedPage类型
AggregatedPage<Goods> aggPage = (AggregatedPage<Goods>) this.goodsRepository.search(queryBuilder.build());
// 3、解析
// 3.1、从结果中取出名为brands的那个聚合,
// 因为是利用String类型字段来进行的term聚合,所以结果要强转为StringTerm类型
LongTerms agg = (LongTerms) aggPage.getAggregation("brands");
// 3.2、获取桶
List<LongTerms.Bucket> buckets = agg.getBuckets();
// 3.3、遍历
for (LongTerms.Bucket bucket : buckets) {
// 3.4、获取桶中的key,即品牌名称 3.5、获取桶中的文档数量
System.out.println(bucket.getKeyAsString() + ",共" + bucket.getDocCount() + "台");
// 3.6.获取子聚合结果:
InternalAvg avg = (InternalAvg) bucket.getAggregations().asMap().get("priceAvg");
System.out.println("平均售价:" + avg.getValue());
}
附:配置搜索结果不显示为null字段:
spring:
jackson:
default-property-inclusion: non_null # 配置json处理时忽略空值
以上就是Spring data中elasticsearch如何使用,小编相信有部分知识点可能是我们日常工作会见到或用到的。希望你能通过这篇文章学到更多知识。更多详情敬请关注亿速云行业资讯频道。
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