使用elasticsearch1.5.2实现查找附近的人

摘要: 计算两个坐标的距离小工具http://www.storyday.com/wp-content/uploads/2008/09/latlung_dis.html

pom.xml:

<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.heli</groupId>
<artifactId>ElasticSearch</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>

<name>ElasticSearch</name>
<url>http://maven.apache.org</url>

<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<es.version>1.5.2</es.version>
<lucene.maven.version>4.10.4</lucene.maven.version>
</properties>

<dependencies>
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch</artifactId>
<version>${es.version}</version>
</dependency>

<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>4.8.2</version>
<scope>test</scope>
</dependency>
</dependencies>
</project>

用户实体：

package com.heli.es;

public class User {

private long id;// id
private String name;// 姓名
private double lat;// 纬度
private double lon;// 经度
private double[] location;// hashcode

public User(long id, String name, double lat, double lon) {
super();
this.id = id;
this.name = name;
this.lat = lat;
this.lon = lon;
}
public long getId() {
return id;
}
public void setId(long id) {
this.id = id;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public double getLat() {
return lat;
}
public void setLat(double lat) {
this.lat = lat;
}
public double getLon() {
return lon;
}
public void setLon(double lon) {
this.lon = lon;
}
public double[] getLocation() {
return location;
}
public void setLocation(double[] location) {
this.location = location;
}
}

测试类：

package com.heli.es;

import static org.elasticsearch.common.xcontent.XContentFactory.jsonBuilder;
import static org.elasticsearch.index.query.FilterBuilders.geoDistanceRangeFilter;

import java.io.IOException;
import java.math.BigDecimal;
import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.Random;

import org.elasticsearch.action.admin.indices.mapping.put.PutMappingRequest;
import org.elasticsearch.action.admin.indices.mapping.put.PutMappingResponse;
import org.elasticsearch.action.bulk.BulkRequestBuilder;
import org.elasticsearch.action.bulk.BulkResponse;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.search.SearchRequestBuilder;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.Client;
import org.elasticsearch.client.Requests;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.geo.GeoDistance;
import org.elasticsearch.common.transport.InetSocketTransportAddress;
import org.elasticsearch.common.unit.DistanceUnit;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentFactory;
import org.elasticsearch.index.query.FilterBuilder;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.sort.GeoDistanceSortBuilder;
import org.elasticsearch.search.sort.SortBuilders;
import org.elasticsearch.search.sort.SortOrder;
/**
* 实现附近的人功能，最大限额1000人，1米到100米范围内的人
*/
public class ES4 {

// 创建索引
public static void createIndex(String indexName, String indexType) throws IOException {
Client esClient = new TransportClient().addTransportAddress(new InetSocketTransportAddress("127.0.0.1", 9300));
// 创建Mapping
XContentBuilder mapping = createMapping(indexType);
System.out.println("mapping:" + mapping.string());
// 创建一个空索引
esClient.admin().indices().prepareCreate(indexName).execute().actionGet();
PutMappingRequest putMapping = Requests.putMappingRequest(indexName).type(indexType).source(mapping);
PutMappingResponse response = esClient.admin().indices().putMapping(putMapping).actionGet();
if (!response.isAcknowledged()) {
System.out.println("Could not define mapping for type [" + indexName + "]/[" + indexType + "].");
} else {
System.out.println("Mapping definition for [" + indexName + "]/[" + indexType + "] succesfully created.");
}
}

// 创建mapping
public static XContentBuilder createMapping(String indexType) {
XContentBuilder mapping = null;
try {
mapping = jsonBuilder().startObject()
// 索引库名（类似数据库中的表）
.startObject(indexType).startObject("properties")
// ID
.startObject("id").field("type", "long").endObject()
// 姓名
.startObject("name").field("type", "string").endObject()
// 位置
.startObject("location").field("type", "geo_point").endObject()
.endObject().endObject().endObject();
} catch (IOException e) {
e.printStackTrace();
}
return mapping;
}

// 添加数据
public static Integer addIndexData100000(String indexName, String indexType) {
Client client = new TransportClient().addTransportAddress(new InetSocketTransportAddress("127.0.0.1", 9300));
List<String> cityList = new ArrayList<String>();

double lat = 39.929986;
double lon = 116.395645;
for (int i = 0; i < 100000; 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);

User city1 = new User(i, "郭德纲"+i, dlat, dlon);
cityList.add(obj2JsonUserData(city1));
}
// 创建索引库
List<IndexRequest> requests = new ArrayList<IndexRequest>();
for (int i = 0; i < cityList.size(); i++) {
IndexRequest request = client.prepareIndex(indexName, indexType).setSource(cityList.get(i)).request();
requests.add(request);
}

// 批量创建索引
BulkRequestBuilder bulkRequest = client.prepareBulk();
for (IndexRequest request : requests) {
bulkRequest.add(request);
}

BulkResponse bulkResponse = bulkRequest.execute().actionGet();
if (bulkResponse.hasFailures()) {
System.out.println("批量创建索引错误！");
}
return bulkRequest.numberOfActions();
}

public static String obj2JsonUserData(User user) {
String jsonData = null;
try {
// 使用XContentBuilder创建json数据
XContentBuilder jsonBuild = XContentFactory.jsonBuilder();
jsonBuild.startObject().field("id", user.getId()).field("name", user.getName()).startArray("location").value(user.getLat()).value(user.getLon()).endArray()
.endObject();
jsonData = jsonBuild.string();
System.out.println(jsonData);
} catch (IOException e) {
e.printStackTrace();
}
return jsonData;
}

// 获取附近的人
public static void testGetNearbyPeople(Client client, String index, String type, double lat, double lon) {
SearchRequestBuilder srb = client.prepareSearch(index).setTypes(type);
srb.setFrom(0).setSize(1000);//1000人
// lon, lat位于谦的坐标，查询距离于谦1米到1000米
FilterBuilder builder = geoDistanceRangeFilter("location").point(lon, lat).from("1m").to("100m").optimizeBbox("memory").geoDistance(GeoDistance.PLANE);
srb.setPostFilter(builder);
// 获取距离多少公里 这个才是获取点与点之间的距离的
GeoDistanceSortBuilder sort = SortBuilders.geoDistanceSort("location");
sort.unit(DistanceUnit.METERS);
sort.order(SortOrder.ASC);
sort.point(lon, lat);
srb.addSort(sort);

SearchResponse searchResponse = srb.execute().actionGet();

SearchHits hits = searchResponse.getHits();
SearchHit[] searchHists = hits.getHits();
// 搜索耗时
Float usetime = searchResponse.getTookInMillis() / 1000f;
System.out.println("于谦附近的人(" + hits.getTotalHits() + "个)，耗时("+usetime+"秒)：");
for (SearchHit hit : searchHists) {
String name = (String) hit.getSource().get("name");
List<Double> location = (List<Double>)hit.getSource().get("location");
// 获取距离值，并保留两位小数点
BigDecimal geoDis = new BigDecimal((Double) hit.getSortValues()[0]);
Map<String, Object> hitMap = hit.getSource();
// 在创建MAPPING的时候，属性名的不可为geoDistance。
hitMap.put("geoDistance", geoDis.setScale(0, BigDecimal.ROUND_HALF_DOWN));
System.out.println(name+"的坐标："+location + "他距离于谦" + hit.getSource().get("geoDistance") + DistanceUnit.METERS.toString());
}

}
public static void main(String[] args) throws IOException {
Client client = new TransportClient().addTransportAddress(new InetSocketTransportAddress("127.0.0.1", 9300));
String index = "es";
String type = "people";
//createIndex(index, type);
//addIndexData100000(index, type);

double lat = 39.929986;
double lon = 116.395645;
long start = System.currentTimeMillis();
//query("郭", index, type);
testGetNearbyPeople(client, index, type, lat, lon);
long end = System.currentTimeMillis();
System.out.println((end - start) + "毫秒");
//client.close();// 1.5.2用完不用关闭
}
}

查询结果：

于谦附近的人(69个)，耗时(0.016秒)：
郭德纲17413的坐标：[39.929999, 116.395658]他距离于谦2m
郭德纲79407的坐标：[39.930006, 116.395665]他距离于谦2m
郭德纲26009的坐标：[39.93003, 116.395689]他距离于谦5m
郭德纲90577的坐标：[39.930041, 116.3957]他距离于谦7m
郭德纲4479的坐标：[39.930049, 116.395708]他距离于谦8m
郭德纲59538的坐标：[39.930068, 116.395727]他距离于谦10m
郭德纲56225的坐标：[39.930072, 116.395731]他距离于谦10m
郭德纲78623的坐标：[39.930075, 116.395734]他距离于谦11m
郭德纲21402的坐标：[39.930092, 116.395751]他距离于谦13m
郭德纲98117的坐标：[39.930098, 116.395757]他距离于谦14m
郭德纲92957的坐标：[39.9301, 116.395759]他距离于谦14m
郭德纲75291的坐标：[39.930101, 116.39576]他距离于谦14m
郭德纲84154的坐标：[39.930121, 116.39578]他距离于谦16m
郭德纲73369的坐标：[39.93016, 116.395819]他距离于谦21m
郭德纲38979的坐标：[39.930174, 116.395833]他距离于谦23m
郭德纲78569的坐标：[39.930193, 116.395852]他距离于谦25m
郭德纲15100的坐标：[39.930207, 116.395866]他距离于谦27m
郭德纲3864的坐标：[39.930218, 116.395877]他距离于谦28m
郭德纲66276的坐标：[39.930237, 116.395896]他距离于谦30m
郭德纲90141的坐标：[39.930243, 116.395902]他距离于谦31m
郭德纲29377的坐标：[39.930249, 116.395908]他距离于谦32m
郭德纲54727的坐标：[39.930253, 116.395912]他距离于谦32m
郭德纲10456的坐标：[39.930292, 116.395951]他距离于谦37m
郭德纲48968的坐标：[39.930298, 116.395957]他距离于谦38m
郭德纲20625的坐标：[39.930305, 116.395964]他距离于谦39m
郭德纲58066的坐标：[39.930307, 116.395966]他距离于谦39m
郭德纲76596的坐标：[39.930308, 116.395967]他距离于谦39m
郭德纲73185的坐标：[39.930323, 116.395982]他距离于谦41m
郭德纲26093的坐标：[39.930331, 116.39599]他距离于谦42m
郭德纲76719的坐标：[39.930331, 116.39599]他距离于谦42m
郭德纲27200的坐标：[39.930337, 116.395996]他距离于谦43m
郭德纲48983的坐标：[39.930337, 116.395996]他距离于谦43m
郭德纲21808的坐标：[39.930356, 116.396015]他距离于谦45m
郭德纲70386的坐标：[39.930356, 116.396015]他距离于谦45m
郭德纲56140的坐标：[39.93036, 116.396019]他距离于谦45m
郭德纲19567的坐标：[39.930365, 116.396024]他距离于谦46m
郭德纲9499的坐标：[39.930366, 116.396025]他距离于谦46m
郭德纲11682的坐标：[39.930381, 116.39604]他距离于谦48m
郭德纲19372的坐标：[39.930382, 116.396041]他距离于谦48m
郭德纲12508的坐标：[39.930383, 116.396042]他距离于谦48m
郭德纲56554的坐标：[39.930385, 116.396044]他距离于谦48m
郭德纲79324的坐标：[39.930389, 116.396048]他距离于谦49m
郭德纲30910的坐标：[39.930394, 116.396053]他距离于谦50m
郭德纲45095的坐标：[39.930412, 116.396071]他距离于谦52m
郭德纲73533的坐标：[39.930422, 116.396081]他距离于谦53m
郭德纲46509的坐标：[39.930422, 116.396081]他距离于谦53m
郭德纲81262的坐标：[39.93044, 116.396099]他距离于谦55m
郭德纲30077的坐标：[39.930448, 116.396107]他距离于谦56m
郭德纲61049的坐标：[39.930456, 116.396115]他距离于谦57m
郭德纲16607的坐标：[39.930458, 116.396117]他距离于谦57m
郭德纲50464的坐标：[39.930467, 116.396126]他距离于谦58m
郭德纲7272的坐标：[39.930468, 116.396127]他距离于谦59m
郭德纲82133的坐标：[39.93047, 116.396129]他距离于谦59m
郭德纲46350的坐标：[39.930472, 116.396131]他距离于谦59m
郭德纲40185的坐标：[39.930502, 116.396161]他距离于谦63m
郭德纲28020的坐标：[39.930515, 116.396174]他距离于谦64m
郭德纲75873的坐标：[39.93052, 116.396179]他距离于谦65m
郭德纲83959的坐标：[39.930527, 116.396186]他距离于谦66m
郭德纲5175的坐标：[39.930529, 116.396188]他距离于谦66m
郭德纲15511的坐标：[39.930531, 116.39619]他距离于谦66m
郭德纲61721的坐标：[39.930535, 116.396194]他距离于谦67m
郭德纲54860的坐标：[39.930549, 116.396208]他距离于谦68m
郭德纲38391的坐标：[39.93055, 116.396209]他距离于谦69m
郭德纲5603的坐标：[39.930555, 116.396214]他距离于谦69m
郭德纲70588的坐标：[39.930579, 116.396238]他距离于谦72m
郭德纲12256的坐标：[39.930583, 116.396242]他距离于谦73m
郭德纲93219的坐标：[39.930598, 116.396257]他距离于谦74m
郭德纲80353的坐标：[39.930607, 116.396266]他距离于谦75m
郭德纲19737的坐标：[39.930617, 116.396276]他距离于谦77m
82毫秒

注：server 和client版本使用的是1.5.2，如果server版本用elasticsearch-rtf-master，sort的时候总是报：

Exception in thread "main" org.elasticsearch.action.search.SearchPhaseExecutionException: Failed to execute phase [query], all shards failed; shardFailures {[alee59cPQNuzRP4go6-5vw][testes][4]: SearchParseException[[testes][4]: from[-1],size[-1]: Parse Failure [Failed to parse source [{"post_filter":{"geo_distance_range":{"location":"wx4g0th9p0gk","from":"1km","to":"2000km","include_lower":true,"include_upper":true,"distance_type":"arc","optimize_bbox":"memory"}},"sort":[{"_geo_distance":{"location":[{"lat":39.929986,"lon":116.395645}],"unit":"km","distance_type":"arc"}}]}]]]; nested: ElasticsearchParseException[Numeric value expected]; }{[alee59cPQNuzRP4go6-5vw][testes][0]: SearchParseException[[testes][0]: from[-1],size[-1]: Parse Failure [Failed to parse source [{"post_filter":{"geo_distance_range":{"location":"wx4g0th9p0gk","from":"1km","to":"2000km","include_lower":true,"include_upper":true,"distance_type":"arc","optimize_bbox":"memory"}},"sort":[{"_geo_distance":{"location":[{"lat":39.929986,"lon":116.395645}],"unit":"km","distance_type":"arc"}}]}]]]; nested: ElasticsearchParseException[Numeric value expected]; }{[alee59cPQNuzRP4go6-5vw][testes][1]: SearchParseException[[testes][1]: from[-1],size[-1]: Parse Failure [Failed to parse source [{"post_filter":{"geo_distance_range":{"location":"wx4g0th9p0gk","from":"1km","to":"2000km","include_lower":true,"include_upper":true,"distance_type":"arc","optimize_bbox":"memory"}},"sort":[{"_geo_distance":{"location":[{"lat":39.929986,"lon":116.395645}],"unit":"km","distance_type":"arc"}}]}]]]; nested: ElasticsearchParseException[Numeric value expected]; }{[alee59cPQNuzRP4go6-5vw][testes][2]: SearchParseException[[testes][2]: from[-1],size[-1]: Parse Failure [Failed to parse source [{"post_filter":{"geo_distance_range":{"location":"wx4g0th9p0gk","from":"1km","to":"2000km","include_lower":true,"include_upper":true,"distance_type":"arc","optimize_bbox":"memory"}},"sort":[{"_geo_distance":{"location":[{"lat":39.929986,"lon":116.395645}],"unit":"km","distance_type":"arc"}}]}]]]; nested: ElasticsearchParseException[Numeric value expected]; }{[alee59cPQNuzRP4go6-5vw][testes][3]: SearchParseException[[testes][3]: from[-1],size[-1]: Parse Failure [Failed to parse source [{"post_filter":{"geo_distance_range":{"location":"wx4g0th9p0gk","from":"1km","to":"2000km","include_lower":true,"include_upper":true,"distance_type":"arc","optimize_bbox":"memory"}},"sort":[{"_geo_distance":{"location":[{"lat":39.929986,"lon":116.395645}],"unit":"km","distance_type":"arc"}}]}]]]; nested: ElasticsearchParseException[Numeric value expected]; }

换成1.5.2结果就好了，还有

.point(lon, lat)

必须经度在前，纬度在后，不然查询为空，跟一朋友聊说这个可能是个bug
另外查询速度太慢，应该哪个地方配置的问题，经过试验，原来创建client消耗了1秒左右，10万个基数查询82毫秒，非常快