Spring data elasticsearch使用方法详解
作者:bofeng
这篇文章主要介绍了Spring data elasticsearch使用方法详解,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
这篇文章主要介绍了Spring data elasticsearch使用方法详解,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
一、准备
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
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持脚本之家。
