使用ElasticSearch完成百万级数据查询附近的人功能
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2022-04-05 23:45:53
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上一篇文章介绍了ElasticSearch使用Repository和ElasticSearchTemplate完成构建复杂查询条件，简单介绍了ElasticSearch使用地理位置的功能。
这一篇我们来看一下使用ElasticSearch完成大数据量查询附近的人功能，搜索N米范围的内的数据。
准备环境
本机测试使用了ElasticSearch最新版5.5.1，SpringBoot1.5.4，spring-data-ElasticSearch2.1.4.
新建Springboot项目，勾选ElasticSearch和web。
pom文件如下
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.tianyalei</groupId>
<artifactId>elasticsearch</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
<name>elasticsearch</name>
<description>Demo project for Spring Boot</description>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>1.5.4.RELEASE</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
<java.version>1.8</java.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.sun.jna</groupId>
<artifactId>jna</artifactId>
<version>3.0.9</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
package com.tianyalei.elasticsearch.model;
import org.springframework.data.annotation.Id;
import org.springframework.data.elasticsearch.annotations.Document;
import org.springframework.data.elasticsearch.annotations.GeoPointField;
import java.io.Serializable;
/**
* model类
*/
@Document(indexName="elastic_search_project",type="person",indexStoreType="fs",shards=5,replicas=1,refreshInterval="-1")
public class Person implements Serializable {
@Id
private int id;
private String name;
private String phone;
/**
* 地理位置经纬度
* lat纬度，lon经度 "40.715,-74.011"
* 如果用数组则相反[-73.983, 40.719]
*/
@GeoPointField
private String address;
public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String getPhone() {
return phone;
}
public void setPhone(String phone) {
this.phone = phone;
}
public String getAddress() {
return address;
}
public void setAddress(String address) {
this.address = address;
}
}
import com.tianyalei.elasticsearch.model.Person;
import org.springframework.data.elasticsearch.repository.ElasticsearchRepository;
public interface PersonRepository extends ElasticsearchRepository<Person, Integer> {
}
package com.tianyalei.elasticsearch.service;
import com.tianyalei.elasticsearch.model.Person;
import com.tianyalei.elasticsearch.repository.PersonRepository;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.elasticsearch.core.ElasticsearchTemplate;
import org.springframework.data.elasticsearch.core.query.IndexQuery;
import org.springframework.stereotype.Service;
import java.util.ArrayList;
import java.util.List;
@Service
public class PersonService {
@Autowired
PersonRepository personRepository;
@Autowired
ElasticsearchTemplate elasticsearchTemplate;
private static final String PERSON_INDEX_NAME = "elastic_search_project";
private static final String PERSON_INDEX_TYPE = "person";
public Person add(Person person) {
return personRepository.save(person);
}
public void bulkIndex(List<Person> personList) {
int counter = 0;
try {
if (!elasticsearchTemplate.indexExists(PERSON_INDEX_NAME)) {
elasticsearchTemplate.createIndex(PERSON_INDEX_TYPE);
}
List<IndexQuery> queries = new ArrayList<>();
for (Person person : personList) {
IndexQuery indexQuery = new IndexQuery();
indexQuery.setId(person.getId() + "");
indexQuery.setObject(person);
indexQuery.setIndexName(PERSON_INDEX_NAME);
indexQuery.setType(PERSON_INDEX_TYPE);
//上面的那几步也可以使用IndexQueryBuilder来构建
//IndexQuery index = new IndexQueryBuilder().withId(person.getId() + "").withObject(person).build();
queries.add(indexQuery);
if (counter % 500 == 0) {
elasticsearchTemplate.bulkIndex(queries);
queries.clear();
System.out.println("bulkIndex counter : " + counter);
}
counter++;
}
if (queries.size() > 0) {
elasticsearchTemplate.bulkIndex(queries);
}
System.out.println("bulkIndex completed.");
} catch (Exception e) {
System.out.println("IndexerService.bulkIndex e;" + e.getMessage());
throw e;
}
}
}
package com.tianyalei.elasticsearch.controller;
import com.tianyalei.elasticsearch.model.Person;
import com.tianyalei.elasticsearch.service.PersonService;
import org.elasticsearch.common.unit.DistanceUnit;
import org.elasticsearch.index.query.GeoDistanceQueryBuilder;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.search.sort.GeoDistanceSortBuilder;
import org.elasticsearch.search.sort.SortBuilders;
import org.elasticsearch.search.sort.SortOrder;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.domain.PageRequest;
import org.springframework.data.domain.Pageable;
import org.springframework.data.elasticsearch.core.ElasticsearchTemplate;
import org.springframework.data.elasticsearch.core.query.NativeSearchQueryBuilder;
import org.springframework.data.elasticsearch.core.query.SearchQuery;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;
import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
@RestController
public class PersonController {
@Autowired
PersonService personService;
@Autowired
ElasticsearchTemplate elasticsearchTemplate;
@GetMapping("/add")
public Object add() {
double lat = 39.929986;
double lon = 116.395645;
List<Person> personList = new ArrayList<>(900000);
for (int i = 100000; i < 1000000; i++) {
double max = 0.00001;
double min = 0.000001;
Random random = new Random();
double s = random.nextDouble() % (max - min + 1) + max;
DecimalFormat df = new DecimalFormat("######0.000000");
// System.out.println(s);
String lons = df.format(s + lon);
String lats = df.format(s + lat);
Double dlon = Double.valueOf(lons);
Double dlat = Double.valueOf(lats);
Person person = new Person();
person.setId(i);
person.setName("名字" + i);
person.setPhone("电话" + i);
person.setAddress(dlat + "," + dlon);
personList.add(person);
}
personService.bulkIndex(personList);
// SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(QueryBuilders.queryStringQuery("spring boot OR 书籍")).build();
// List<Article> articles = elas、ticsearchTemplate.queryForList(se、archQuery, Article.class);
// for (Article article : articles) {
// System.out.println(article.toString());
// }
return "添加数据";
}
/**
*
geo_distance: 查找距离某个中心点距离在一定范围内的位置
geo_bounding_box: 查找某个长方形区域内的位置
geo_distance_range: 查找距离某个中心的距离在min和max之间的位置
geo_polygon: 查找位于多边形内的地点。
sort可以用来排序
*/
@GetMapping("/query")
public Object query() {
double lat = 39.929986;
double lon = 116.395645;
Long nowTime = System.currentTimeMillis();
//查询某经纬度100米范围内
GeoDistanceQueryBuilder builder = QueryBuilders.geoDistanceQuery("address").point(lat, lon)
.distance(100, DistanceUnit.METERS);
GeoDistanceSortBuilder sortBuilder = SortBuilders.geoDistanceSort("address")
.point(lat, lon)
.unit(DistanceUnit.METERS)
.order(SortOrder.ASC);
Pageable pageable = new PageRequest(0, 50);
NativeSearchQueryBuilder builder1 = new NativeSearchQueryBuilder().withFilter(builder).withSort(sortBuilder).withPageable(pageable);
SearchQuery searchQuery = builder1.build();
//queryForList默认是分页，走的是queryForPage，默认10个
List<Person> personList = elasticsearchTemplate.queryForList(searchQuery, Person.class);
System.out.println("耗时：" + (System.currentTimeMillis() - nowTime));
return personList;
}
}
在查询方法中，我们构建了一个查询100米范围内、按照距离远近排序，分页每页50条的查询条件。如果不指明Pageable的话，ESTemplate的queryForList默认是10条，通过源码可以看到。
启动项目，先执行add，等待百万数据插入，大概几十秒。
然后执行查询，看一下结果。
第一次查询花费300多ms，再次查询后时间就大幅下降，到30ms左右，因为ES已经自动缓存到内存了。
可见，ES完成地理位置的查询还是非常快的。适用于查询附近的人、范围查询之类的功能。
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后记，在后来的使用中，Elasticsearch2.3版本时，按上面的写法出现了geo类型无法索引的情况，进入es的为String，而不是标注的geofiled。在此记录一下解决方法，将String类型修改为GeoPoint，且是org.springframework.data.elasticsearch.core.geo.GeoPoint包下的。然后需要在创建index时，显式调用一下mapping方法，才能正确的映射为geofield。
如下
if (!elasticsearchTemplate.indexExists("abc")) {
elasticsearchTemplate.createIndex("abc");
elasticsearchTemplate.putMapping(Person.class);
}参考：ES根据地理位置查询 http://blog.csdn.net/bingduanlbd/article/details/52253542
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