之前说过ElasticSearch一共支持4种Api，本篇文章主要讲解Springboot数据层集成ElasticSearch的Api简单使用。先看看下面这个Spring集成数据层框架图
可以看到Spring Data系列集成了非常多数据层框架，JDBC，Redis，ElasticSearch，Hadoop，Solr，MongoDB等，非常多啊，感觉spring是要一统天下啊，多的不说了，看看我们这个es怎么做
注意：我这里es的版本是5.6.2，由于es官方更新较快（现在已经7.15），相关api的使用，内部方法也在变，所以别的版本可能会有些变化
1.创建springboot项目，导入相关依赖首先parent父工程，我这里是2.0.5版本，对应里面的es版本刚好是5.x版本，如果不一样，需改变版本
org.springframework.boot spring-boot-starter-parent 2.0.5.RELEASE
2.创建好启动类（不做演示），以及yaml配置文件org.springframework.boot spring-boot-starter-data-elasticsearch org.springframework.boot spring-boot-starter-web org.springframework.boot spring-boot-starter-test org.projectlombok lombok com.alibaba fastjson 1.1.15
spring:
data:
elasticsearch:
cluster-name: elasticsearch
cluster-nodes: 127.0.0.1:9300
3.创建实体类，做es的文档对象
@Data
@AllArgsConstructor
@NoArgsConstructor
@document(indexName = "student",type = "infro")
public class Student {
@Id
private Long id;
@Field(type = FieldType.Text,analyzer = "ik_max_word",searchAnalyzer = "ik_max_word")
private String sname;
@Field(type = FieldType.Keyword)
private int sage;
@Field(type = FieldType.Text,analyzer = "ik_max_word",searchAnalyzer = "ik_max_word")
private String intro;
}
@document(indexName = “student”,type = “infro”)
indexName:指定索引名
type：指定类型名
@Id：代表文档id
@Field(type = FieldType.Text,analyzer = “ik_max_word”,searchAnalyzer = “ik_max_word”)
type：自定该字段的类型（Text和KeyWord都是String类型，Text代表分词，KeyWord代表不分词）
analyzer:指定存储时使用什么分词策略
searchAnalyzer:指定搜索时使用什么分词策略
4.创建索引测试类@RunWith(SpringRunner.class)
@SpringBootTest(classes = ESApp.class)
public class EsIndexTest {
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
@Test
public void testCreateIndex(){
// 创建索引
elasticsearchTemplate.createIndex(Student.class);
// 做文档映射
elasticsearchTemplate.putMapping(Student.class);
}
}
5.创建文档测试类
@RunWith(SpringRunner.class)
@SpringBootTest(classes = ESApp.class)
public class EsSimpleDocTest {
@Autowired
private EsRepository esRepository;
// 添加文档
@Test
public void testAddDoc(){
Student student = new Student(1L, "zhangsan", 18, "法外狂徒张三");
esRepository.save(student);
}
// 修改文档:和添加文档一样，只不过id必须相同
@Test
public void testUpdateDoc(){
Student student = new Student(1L, "lisi", 20, "法外狂徒李四");
esRepository.save(student);
}
// 删除文档数据
@Test
public void testDelDoc(){
esRepository.deleteById(1L);
}
// 查询数据
@Test
public void testSearchDoc(){
// 获取全部数据
Iterable students = esRepository.findAll();
students.forEach(student -> {
System.out.println(student);
});
System.out.println("=============");
// 根据id获取
Optional studentOptional = esRepository.findById(1L);
Student student = studentOptional.get();
System.out.println(student);
}
// 保存一堆数据
@Test
public void testAddMutilDoc(){
ArrayList students = new ArrayList<>();
students.add(new Student(1L,"zhangsan",18,"法外狂徒张三"));
students.add(new Student(2L,"lisi",20,"那真是绝了"));
students.add(new Student(3L,"王五",28,"法外狂徒张三"));
students.add(new Student(4L,"周勇",30,"不会吧"));
students.add(new Student(5L,"何总",25,"可恶"));
students.add(new Student(6L,"lisi",18,"秀儿"));
esRepository.saveAll(students);
}
}
6.文档高级搜索
@RunWith(SpringRunner.class)
@SpringBootTest(classes = ESApp.class)
public class EsMutilSearchDocTest {
@Autowired
private EsRepository esRepository;
// 高级查询
@Test
public void testMutilSearch(){
// 创建一个查询构造器
NativeSearchQueryBuilder builder = new NativeSearchQueryBuilder();
// 查询条件(组合查询)
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery();
// 必须满足sname匹配lisi字符
boolQueryBuilder.must(QueryBuilders.matchQuery("sname","lisi"));
// 过滤条件
boolQueryBuilder.filter(QueryBuilders.rangeQuery("sage").gte(18).lte(30));
builder.withQuery(boolQueryBuilder);
//按照年龄排序
builder.withSort(new FieldSortBuilder("sage").order(SortOrder.ASC));
// 分页
builder.withPageable(PageRequest.of(0,10));
// 通过构造器构建查询对象
NativeSearchQuery searchQuery = builder.build();
// 查询获取到page对象
Page studentPage = esRepository.search(searchQuery);
// 总条数
System.out.println(studentPage.getTotalElements());
// 总分页
System.out.println(studentPage.getTotalPages());
// 获取到真正需要的对象
List students = studentPage.getContent();
// 循环打印
students.forEach(student -> {
System.out.println(student);
});
}
}
7.文档高亮搜素
7.1SpringbootData中没有对高亮结果处理，所以要自己写结果处理器，并交给spring管理
@Component
public class HighlightResultMapper implements SearchResultMapper {
@Override
public AggregatedPage mapResults(SearchResponse response, Class aClass, Pageable pageable) {
// 记录总条数
long totalHits = response.getHits().getTotalHits();
// 记录列表(泛型) - 构建Aggregate使用
List list = Lists.newArrayList();
// 获取搜索结果(真正的的记录)
SearchHits hits = response.getHits();
for (SearchHit hit : hits) {
if(hits.getHits().length <= 0){
return null;
}
// 将原本的JSON对象转换成Map对象
Map map = hit.getSourceAsMap();
// 获取高亮的字段Map
Map highlightFields = hit.getHighlightFields();
for (Map.Entry highlightField : highlightFields.entrySet()) {
// 获取高亮的Key
String key = highlightField.getKey();
// 获取高亮的Value
HighlightField value = highlightField.getValue();
// 实际fragments[0]就是高亮的结果，无需遍历拼接
Text[] fragments = value.getFragments();
StringBuilder sb = new StringBuilder();
for (Text text : fragments) {
sb.append(text);
}
// 因为高亮的字段必然存在于Map中，就是key值
// 可能有一种情况，就是高亮的字段是嵌套Map，也就是说在Map里面还有Map的这种情况，这里没有考虑
map.put(key, sb.toString());
}
// 把Map转换成对象
T item = JSON.parseObject(JSONObject.toJSONString(map),aClass);
list.add(item);
}
// 返回的是带分页的结果
return new AggregatedPageImpl<>(list, pageable, totalHits);
}
}
7.2文档高亮测试
@RunWith(SpringRunner.class)
@SpringBootTest(classes = ESApp.class)
public class EsHighlightMutilSearchTest {
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
@Autowired
private HighlightResultMapper highlightResultMapper;
// 测试高亮
@Test
public void testHighlightSearch(){
// 构建查询构造器
NativeSearchQueryBuilder searchQueryBuilder = new NativeSearchQueryBuilder();
// 设置查询条件(全部查询)
searchQueryBuilder.withQuery(QueryBuilders.matchAllQuery());
// 分页、排序那些就不写了，直接写高亮
// 构建高亮查询(分别设置高亮字段以及其前缀后缀)
HighlightBuilder.Field highlightBuilder = new HighlightBuilder.Field("sname").preTags("").postTags("");
// 将高亮设置进去
searchQueryBuilder.withHighlightFields(highlightBuilder);
// 构建出具体条件
NativeSearchQuery searchQuery = searchQueryBuilder.build();
//开始查询(以高亮的方式查询)
AggregatedPage page = elasticsearchTemplate.queryForPage(searchQuery, Student.class, highlightResultMapper);
// 打印结果
System.out.println(page.getTotalElements());
System.out.println(page.getTotalPages());
List students = page.getContent();
students.forEach(student -> {
System.out.println(student);
});
}
}
8.聚合查询
8.1聚合查询也是一样，springboot没有处理器需要自己创建
其实跟高亮那个处理器一样，只不过在返回值时多加了一个聚合
@Component
public class AggregationResultMapper implements SearchResultMapper {
@Override
public AggregatedPage mapResults(SearchResponse response, Class aClass, Pageable pageable) {
// 记录总条数
long totalHits = response.getHits().getTotalHits();
// 记录列表(泛型) - 构建Aggregate使用
List list = Lists.newArrayList();
// 获取搜索结果(真正的的记录)
SearchHits hits = response.getHits();
for (SearchHit hit : hits) {
if(hits.getHits().length <= 0){
return null;
}
// 将原本的JSON对象转换成Map对象
Map map = hit.getSourceAsMap();
// 获取高亮的字段Map
Map highlightFields = hit.getHighlightFields();
for (Map.Entry highlightField : highlightFields.entrySet()) {
// 获取高亮的Key
String key = highlightField.getKey();
// 获取高亮的Value
HighlightField value = highlightField.getValue();
// 实际fragments[0]就是高亮的结果，无需遍历拼接
Text[] fragments = value.getFragments();
StringBuilder sb = new StringBuilder();
for (Text text : fragments) {
sb.append(text);
}
// 因为高亮的字段必然存在于Map中，就是key值
// 可能有一种情况，就是高亮的字段是嵌套Map，也就是说在Map里面还有Map的这种情况，这里没有考虑
map.put(key, sb.toString());
}
// 把Map转换成对象
T item = JSON.parseObject(JSONObject.toJSONString(map),aClass);
list.add(item);
}
// 返回的是带分页的结果
return new AggregatedPageImpl<>(list, pageable, totalHits,response.getAggregations());
}
}
8.2聚合查询测试
@RunWith(SpringRunner.class)
@SpringBootTest(classes = ESApp.class)
public class EsAggregationSearchTest {
@Autowired
private ElasticsearchTemplate elasticsearchTemplate;
@Autowired
private AggregationResultMapper aggregationResultMapper;
// 聚合查询
@Test
public void testAggregationSearch(){
NativeSearchQueryBuilder searchQueryBuilder = new NativeSearchQueryBuilder();
searchQueryBuilder.withQuery(QueryBuilders.matchAllQuery());
// 聚合查询
TermsAggregationBuilder termsAggregationBuilder = AggregationBuilders.terms("paixu").field("sage").order(Terms.Order.count(false));
// 添加聚合查询
searchQueryBuilder.addAggregation(termsAggregationBuilder);
NativeSearchQuery searchQuery = searchQueryBuilder.build();
// 开始查询
AggregatedPage page = elasticsearchTemplate.queryForPage(searchQuery, Student.class, aggregationResultMapper);
StringTerms terms = (StringTerms) page.getAggregation("paixu");
List buckets = terms.getBuckets();
//把机构名字聚合，搜集成字符串里集合
List sages = buckets.stream().map(bucket -> bucket.getKeyAsString()).collect(Collectors.toList());
System.out.println(sages);
}
}
