使用ElasticSearch完成百萬級資料查詢附近的人功能
阿新 • • 發佈:2019-01-28
上一篇文章介紹了ElasticSearch使用Repository和ElasticSearchTemplate完成構建複雜查詢條件,簡單介紹了ElasticSearch使用地理位置的功能。
這一篇我們來看一下使用ElasticSearch完成大資料量查詢附近的人功能,搜尋N米範圍的內的資料。
準備環境
本機測試使用了ElasticSearch最新版5.5.1,SpringBoot1.5.4,spring-data-ElasticSearch2.1.4.新建Springboot專案,勾選ElasticSearch和web。pom檔案如下新建model類Person<?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>
我用address欄位表示經緯度位置。注意,使用String[]和String分別來表示經緯度時是不同的,見註釋。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類 */ @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; /** * 地理位置經緯度 * lat緯度,lon經度 "40.715,-74.011" * 如果用陣列則相反[-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> {
}
看一下Service類,完成插入測試資料的功能,查詢的功能我放在Controller裡了,為了方便檢視,正常是應該放在Service裡注意看bulkIndex方法,這個是批量插入資料用的,bulk也是ES官方推薦使用的批量插入資料的方法。這裡是每逢500的整數倍就bulk插入一次。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); //上面的那幾步也可以使用IndexQueryBuilder來構建 //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("電話" + i);
person.setAddress(dlat + "," + dlon);
personList.add(person);
}
personService.bulkIndex(personList);
// SearchQuery searchQuery = new NativeSearchQueryBuilder().withQuery(QueryBuilders.queryStringQuery("spring boot OR 書籍")).build();
// List<Article> articles = elas、ticsearchTemplate.queryForList(se、archQuery, Article.class);
// for (Article article : articles) {
// System.out.println(article.toString());
// }
return "新增資料";
}
/**
*
geo_distance: 查詢距離某個中心點距離在一定範圍內的位置
geo_bounding_box: 查詢某個長方形區域內的位置
geo_distance_range: 查詢距離某個中心的距離在min和max之間的位置
geo_polygon: 查詢位於多邊形內的地點。
sort可以用來排序
*/
@GetMapping("/query")
public Object query() {
double lat = 39.929986;
double lon = 116.395645;
Long nowTime = System.currentTimeMillis();
//查詢某經緯度100米範圍內
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預設是分頁,走的是queryForPage,預設10個
List<Person> personList = elasticsearchTemplate.queryForList(searchQuery, Person.class);
System.out.println("耗時:" + (System.currentTimeMillis() - nowTime));
return personList;
}
}
看Controller類,在add方法中,我們插入90萬條測試資料,隨機產生不同的經緯度地址。在查詢方法中,我們構建了一個查詢100米範圍內、按照距離遠近排序,分頁每頁50條的查詢條件。如果不指明Pageable的話,ESTemplate的queryForList預設是10條,通過原始碼可以看到。啟動專案,先執行add,等待百萬資料插入,大概幾十秒。然後執行查詢,看一下結果。第一次查詢花費300多ms,再次查詢後時間就大幅下降,到30ms左右,因為ES已經自動快取到記憶體了。可見,ES完成地理位置的查詢還是非常快的。適用於查詢附近的人、範圍查詢之類的功能。-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------後記,在後來的使用中,Elasticsearch2.3版本時,按上面的寫法出現了geo型別無法索引的情況,進入es的為String,而不是標註的geofiled。在此記錄一下解決方法,將String型別修改為GeoPoint,且是org.springframework.data.elasticsearch.core.geo.GeoPoint包下的。然後需要在建立index時,顯式呼叫一下mapping方法,才能正確的對映為geofield。如下
if (!elasticsearchTemplate.indexExists("abc")) {
elasticsearchTemplate.createIndex("abc");
elasticsearchTemplate.putMapping(Person.class);
}
參考:ES根據地理位置查詢 http://blog.csdn.net/bingduanlbd/article/details/52253542