filebeat+kafka+Flink+ElasticSearch+springboot+高德地图热力图项目

原文地址 https://www.jianshu.com/p/c148bf91c3ac

2019.05.26

由于近期在研究ELK和最新的实时计算框架Flink，所以把以前热力图项目flume+kafka+SparkStreaming+mysql+ssm+高德地图热力图项目换组件重构一下。效果不会变好，可能更麻烦，性能更低，纯属应用一下最近研究的新组件和新计算框架。

项目环境：

filebeat 6.2.0
kafka 0.8.2
Flink 1.6.1
ElasticSearch 6.4.0
springboot 2.1.5
scala 2.11

项目顺序：

1.python写个脚本模拟下数据。正常情况的真实数据是，我们每个人的手机会不停发送你的经纬度，比如你坐火车到别的省份会收到一条短信，例如：山东省济南市欢迎您。就是这个道理。

import random
import time

phone = [
    "13869555210",
    "18542360152",
    "15422556663",
    "18852487210",
    "13993584664",
    "18754366522",
    "15222436542",
    "13369568452",
    "13893556666",
    "15366698558"
]

location = [
    "123.449169, 41.740567",
    "123.450169, 41.740705",
    "123.451169, 41.741405",
    "123.452169, 41.741805",
    "123.453654, 41.742405",
    "123.454654, 41.742805",
    "123.455654, 41.743405",
    "123.458654, 41.743705"
]


def sample_phone():
    return random.sample(phone, 1)[0]


def sample_location():
    return random.sample(location, 1)[0]


def generator_log(count=10):
    time_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
    f = open("/var/log/lyh.log", "a+")
    while count >= 1:
        query_log = "{phone}\t{location}\t{date}".format(phone=sample_phone(), location=sample_location(),
                                                         date=time_str)
        f.write(query_log + "\n")
        #   print query_log
        count = count - 1


if __name__ == '__main__':
    while True:
        generator_log(100)
        time.sleep(5)

把代码上传到linux环境运行，脚本功能向/var/log/lyh.log文件内 每隔5秒随即生成100条数据。内容就是电话号码+经纬度+时间，后期用Flink实时处理时候需要拿到经纬度信息。

2.用filebeat组件抓取/var/log/lyh.log文件中不停增加的数据，然后输出到kafka中

filebeat是ELK日志收集系统体系里抓取日志的插件，我们这里为了应用一下用他来抓取我们上面Python脚本生成的数据。
修改filebeat.yml配置文件，配置监控抓取信息的文件，和输出的位置

filebeat.prospectors:
- type: log      #抓取信息后以log格式json字符串输出
  paths:
    - /var/log/lyh.log    #监控抓取数据的文件

filebeat.config.modules:
  path: ${path.config}/modules.d/*.yml
  reload.enabled: false
#如果不适用logstash对日志进行过滤，也可以直接输出到es
#output.elasticsearch:
#  hosts: ["172.24.112.17:9200"]
#  #输出到kafka
output.kafka:
  hosts: ["hadoop1:9092", "hadoop2:9092", "hadoop3:9092"]
  topic: 'log'

注意:filebeat和kafka的版本一定要兼容否者报错，具体哪个版本之间互相兼容参考官方文档https://www.elastic.co/guide/en/beats/filebeat/6.4/kafka-output.html
启动filebeat命令

sudo -u elk ./filebeat -e -c filebeat.yml -d "publish"

3.编写Flink代码。从kafka消费数据，清洗数据拿到自己要的数据，存入到ElasticSearch中

pom依赖：

    
      junit
      junit
      4.11
      test
    
    
      org.scala-lang
      scala-library
      2.11.8
    

    
      org.apache.flink
      flink-core
      1.6.1
    

    
      org.apache.flink
      flink-clients_2.11
      1.6.1
    

    
      org.apache.flink
      flink-scala_2.11
      1.6.1
    

    
      org.apache.flink
      flink-streaming-scala_2.11
      1.6.1
    
    
    
      org.apache.flink
      flink-connector-kafka-0.8_2.11
      1.6.1
    
    
    
      log4j
      log4j
      1.2.17
    
    
      com.alibaba
      fastjson
      1.2.36
    

    
      org.apache.flink
      flink-connector-elasticsearch6_2.11
      1.6.1
    

  

Flink代码：

import java.text.SimpleDateFormat
import java.util.{Date, Properties}

import com.alibaba.fastjson.JSON
import org.apache.flink.streaming.connectors.kafka._
import org.apache.flink.streaming.util.serialization.SimpleStringSchema
import org.apache.flink.streaming.api.scala._
import org.apache.flink.api.common.functions.RuntimeContext
import org.apache.flink.streaming.connectors.elasticsearch.ElasticsearchSinkFunction
import org.apache.flink.streaming.connectors.elasticsearch.RequestIndexer
import org.apache.flink.streaming.connectors.elasticsearch6.ElasticsearchSink
import org.apache.http.HttpHost
import org.elasticsearch.action.index.IndexRequest
import org.elasticsearch.client.Requests


object Flink_kafka {
  def main(args: Array[String]): Unit = {
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    // 非常关键，一定要设置启动检查点！！
    env.enableCheckpointing(5000)

    //配置kafka信息
    val props = new Properties()
    props.setProperty("bootstrap.servers", "192.168.199.128:9092,192.168.199.131:9092,192.168.199.132:9092")
    props.setProperty("zookeeper.connect", "192.168.199.128:2181,192.168.199.131:2181,192.168.199.132:2181")
    props.setProperty("group.id", "test")
    //读取数据,第一个参数是kafka的topic，也就是上面filebeat配置文件里面设定的topic叫log
    val consumer = new FlinkKafkaConsumer08[String]("log", new SimpleStringSchema(), props)
    //设置只读取最新数据
    consumer.setStartFromLatest()
    //添加kafka为数据源
    //18542360152   116.410588, 39.880172   2019-05-24 23:43:38
    val stream = env.addSource(consumer).map(
      x=>{
        JSON.parseObject(x)
      }
    ).map(x=>{
      x.getString("message")
    }).map(x=>{
      val jingwei=x.split("\\t")(1)
      val wei=jingwei.split(",")(0).trim
      val jing=jingwei.split(",")(1).trim
      //调一下时间格式，es里面存储时间默认是UTC格式日期，+0800是设置成北京时区
      val sdf=new SimpleDateFormat("yyyy-MM-dd\'T\'HH:mm:ss.SSS+0800")
      val time=sdf.format(new Date())
      val resultStr=wei+","+jing+","+time
      resultStr
    })

    stream.print() //数据清洗以后是这种样子 123.450169,41.740705,2019-05-26T19:03:59.281+0800
    //把清洗好的数据存入es中，数据入库
    val httpHosts = new java.util.ArrayList[HttpHost]
    httpHosts.add(new HttpHost("192.168.199.128", 9200, "http"))//es的client通过http请求连接到es进行增删改查操作

    val esSinkBuilder = new ElasticsearchSink.Builder[String](
      httpHosts,
      new ElasticsearchSinkFunction[String]{    //参数element就是上面清洗好的数据格式
        def createIndexRequest(element: String):IndexRequest={
          val json = new java.util.HashMap[String, String]
          json.put("wei", element.split(",")(0))
          json.put("jing", element.split(",")(1))
          json.put("time", element.split(",")(2))

          return Requests.indexRequest()
            .index("location-index")
              .`type`("location")
            .source(json)
        }

        override def process(element: String, runtimeContext: RuntimeContext, requestIndexer: RequestIndexer): Unit = {
          requestIndexer.add(createIndexRequest(element))
        }
      }
    )

    //批量请求的配置；这将指示接收器在每个元素之后发出请求，否则将对它们进行缓冲。
    esSinkBuilder.setBulkFlushMaxActions(1)

    stream.addSink(esSinkBuilder.build())

    env.execute("Kafka_Flink")
  }
}

注意：ES存储时间时候的格式和时区问题
elasticsearch原生支持date类型，json格式通过字符来表示date类型。
所以在用json提交日期至elasticsearch的时候，es会隐式转换，把es认为是date类型的字符串直接转为date类型。

date类型是包含时区信息的，如果我们没有在json代表日期的字符串中显式指定时区，对es来说没什么问题，
但是如果通过kibana显示es里的数据时，就会出现问题，数据的时间会晚8个小时。

kibana在通过浏览器展示的时候，会通过js获取当前客户端机器所在的时区，也就是东八区，所以kibana会把从es得到的日期数据减去8小时。
最佳实践方案就是：往es提交日期数据时，直接提交带有时区信息的日期字符串，
如：“2016-07-15T12:58:17.136+0800”。 这个是世界协调时间（UTC）格式-es默认支持的格式
java格式化：

String FULL_FORMAT="yyyy-MM-dd\'T\'HH:mm:ss.SSS+0800";
Date now=new Date();
new SimpleDateFormat(FULL_FORMAT).format(now)

4.目前数据已经入库，用springboot创建一个web项目，从es里查出数据，在前台高德热力图组件里动态展示

整个web项目的pom依赖：

        
            org.springframework.boot
            spring-boot-starter-web
        

        
            org.springframework.boot
            spring-boot-starter-tomcat
            provided
        
        
            org.springframework.boot
            spring-boot-starter-test
            test
        
        
        
            javax.servlet
            jstl
        

        
        
            org.apache.tomcat.embed
            tomcat-embed-jasper
            
        

        
            org.elasticsearch.client
            elasticsearch-rest-high-level-client
            6.4.3
        

        
            org.apache.logging.log4j
            log4j-core
            2.11.1
        
        
            com.alibaba
            fastjson
            1.2.36
        
    

4.1我们要从es中查出距离当前时间20秒以内的所有数据，并且按经纬度聚合统计数量。
es的查询语句：

 

QQ截图20190526193643.png

 

使用聚合查询之前要先设置一下mapping，把jing和wei的属性fielddata设置成true，默认是false。不改成true进行聚会查询会报错。
上面语句是先查出距离当前时间20秒内的所有数据，然后根据jing和wei数据进行聚合也就是sql里的group by，聚会以后统计总数。意思就是当前经纬度内的总人数，数越大代表该区域人越多。
web代码里面我们要把上述查询语句通过es的api换成java代码实现。

先创建一个Location实体类，来存放查询出来的数据，总数，经度，纬度。

public class Location {
    private Integer count;
    private double wei;
    private double jing;

    public Integer getCount() {
        return count;
    }

    public void setCount(Integer count) {
        this.count = count;
    }

    public double getWei() {
        return wei;
    }

    public void setWei(double wei) {
        this.wei = wei;
    }

    public double getJing() {
        return jing;
    }

    public void setJing(double jing) {
        this.jing = jing;
    }
}

写一个es的工具类，创建和es连接的client，一些基本增删改查方法，以及上面查询语句的java代码实现

import com.test.flink_web_show.controller.Location;
import org.apache.http.HttpHost;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.script.ScriptType;
import org.elasticsearch.script.mustache.SearchTemplateRequest;
import org.elasticsearch.script.mustache.SearchTemplateResponse;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.aggregations.Aggregation;
import org.elasticsearch.search.aggregations.Aggregations;
import org.elasticsearch.search.aggregations.bucket.terms.Terms;

import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;

public class RestClientUtils {

    private RestHighLevelClient client = null;

    public RestClientUtils() {
        if (client == null){
            synchronized (RestHighLevelClient.class){
                if (client == null){
                    client = getClient();
                }
            }
        }
    }

    private RestHighLevelClient getClient(){
        RestHighLevelClient client = new RestHighLevelClient(
                RestClient.builder(
                        new HttpHost("192.168.199.128", 9200, "http"),
                        new HttpHost("192.168.199.128", 9201, "http")));

        return client;
    }

    public void closeClient(){
        try {
            if (client != null){
                client.close();
            }
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
    
    /*------------------------------------------------ search Api 多条件查询 start ----------------------------------------------*/
    /**
     * 查询模板
     * @throws Exception
     */
    public List searchTemplate(String indexName, String JsonStr, Map scriptParams) throws Exception{
        //Inline Templates
        SearchTemplateRequest request = new SearchTemplateRequest();
        request.setRequest(new SearchRequest(indexName));
        request.setScriptType(ScriptType.INLINE);
        request.setScript(JsonStr);

        request.setScriptParams(scriptParams);

        //Synchronous Execution
        SearchTemplateResponse response = client.searchTemplate(request, RequestOptions.DEFAULT);

        //SearchTemplate Response
        SearchResponse searchResponse = response.getResponse();
        //Retrieving SearchHits 获取结果数据
        SearchHits hits = searchResponse.getHits();
        long totalHits = hits.getTotalHits();
        float maxScore = hits.getMaxScore();
        System.out.println("totalHits: " + totalHits);
        System.out.println("maxScore: " + maxScore);
        System.out.println("------------------------------------------");
        SearchHit[] searchHits = hits.getHits();
        /*for (SearchHit hit : searchHits) {
            // do something with the SearchHit
            String index = hit.getIndex();
            String type = hit.getType();
            String id = hit.getId();
            float score = hit.getScore();

            String sourceAsString = hit.getSourceAsString();
            System.out.println("index: " + index);
            System.out.println("type: " + type);
            System.out.println("id: " + id);
            System.out.println("score: " + score);
            System.out.println(sourceAsString);
            System.out.println("------------------------------------------");
        }*/
        //得到aggregations下内容
        ArrayList locations = new ArrayList<>();
        Aggregations aggregations = searchResponse.getAggregations();
        if(aggregations!=null){
            Map aggregationMap = aggregations.getAsMap();
            Terms companyAggregation = (Terms) aggregationMap.get("group_by_jing");
            List buckets = companyAggregation.getBuckets();
            for(Terms.Bucket bk:buckets){
                Location location = new Location();
                Object key = bk.getKey();
                long docCount = bk.getDocCount();
                System.out.println("key: "+key.toString());
                System.out.println("doc_count: "+docCount);
                String jingdu = key.toString().split("#split#")[0];
                String substring_jing = jingdu.substring(1, jingdu.length() - 1);
                location.setJing(Double.parseDouble(substring_jing));
                String weidu = key.toString().split("#split#")[1];
                String substring_wei = weidu.substring(1, weidu.length() - 1);
                location.setWei(Double.parseDouble(substring_wei));
                location.setCount((int)docCount);

                locations.add(location);
            }
        }
        return locations;
    }
}

es的java api比较复杂具体参考我的另一篇简书ElasticSearch java API

Controller代码：

import com.alibaba.fastjson.JSON;
import com.test.flink_web_show.es_utils.RestClientUtils;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.servlet.ModelAndView;

import javax.servlet.http.HttpServletResponse;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

@Controller
public class HomeController {

    @RequestMapping("/")
    public ModelAndView home()
    {
        ModelAndView modelAndView = new ModelAndView();

        modelAndView.setViewName("index");
        return modelAndView;
    }
    @RequestMapping("/get_map")
    public void getMap(HttpServletResponse response) throws Exception{
        RestClientUtils restClientUtils = new RestClientUtils();
        String searchJSON="{\n" +
                "  \"query\": {\n" +
                "    \"bool\": {\n" +
                "      \"filter\": {\n" +
                "        \"range\": {\n" +
                "          \"{{time}}\": {\n" +
                "            \"{{gte}}\": \"{{value1}}\", \n" +
                "            \"{{lt}}\": \"{{now}}\"\n" +
                "          }\n" +
                "        }\n" +
                "      }\n" +
                "    }\n" +
                "  },\n" +
                "  \"aggs\": {\n" +
                "    \"{{group_by_jing}}\": {\n" +
                "      \"terms\": {\n" +
                "        \"script\": \"{{doc['jing'].values +'#split#'+ doc['wei'].values}}\"\n" +
                "      }\n" +
                "    }\n" +
                "  }\n" +
                "}";
        Map map = new HashMap<>();
        map.put("time","time");
        map.put("gte","gte");
        map.put("value1","now-20s");
        map.put("lt","lt");
        map.put("now","now");
        map.put("group_by_jing","group_by_jing");
        map.put("doc['jing'].values +'#split#'+ doc['wei'].values","doc['jing'].values +'#split#'+ doc['wei'].values");

        List locations = restClientUtils.searchTemplate("location-index", searchJSON, map);
        restClientUtils.closeClient();
        String json = JSON.toJSONString(locations);
        response.getWriter().print(json);
    }
}

前台jsp代码：

<%--
  Created by IntelliJ IDEA.
  User: ttc
  Date: 2018/7/6
  Time: 14:06
  To change this template use File | Settings | File Templates.
--%>
<%@ page contentType="text/html;charset=UTF-8" language="java" %>



    
    
    

上述为全部代码部分
按顺序启动项目全部流程
启动zookeeper

zkServer.sh start

启动kafka

bin/kafka-server-start.sh config/server.properties

启动es

sudo -u elk bin/elasticsearch

启动filebeat

sudo -u elk ./filebeat -e -c filebeat.yml -d "publish"

启动Python脚本生成模拟数据

python phoneData_every5second.py

启动Flink项目，实时接收并处理数据存入到es
启动web项目完成动态地图展示

 

QQ截图20190526201432.png

不会截取gif动图，数据模拟也不是很好，图中的热力图圆圈颜色会根据模拟数据一直不停变化。

作者：__元昊__
链接：https://www.jianshu.com/p/c148bf91c3ac
来源：简书
简书著作权归作者所有，任何形式的转载都请联系作者获得授权并注明出处。