Storm 集群的搭建及其Java编程进行简单统计计算

一、Storm集群构建

编写storm 与 zookeeper的yml文件

 

storm yml文件的编写

具体如下:

version: '2'

services:

  zookeeper1:

    image: registry.aliyuncs.com/denverdino/zookeeper:3.4.8

    container_name: zk1.cloud

    environment:

      - SERVER_ID=1

      - ADDITIONAL_ZOOKEEPER_1=server.1=0.0.0.0:2888:3888

      - ADDITIONAL_ZOOKEEPER_2=server.2=zk2.cloud:2888:3888

      - ADDITIONAL_ZOOKEEPER_3=server.3=zk3.cloud:2888:3888

  zookeeper2:

    image: registry.aliyuncs.com/denverdino/zookeeper:3.4.8

    container_name: zk2.cloud

    environment:

      - SERVER_ID=2

      - ADDITIONAL_ZOOKEEPER_1=server.1=zk1.cloud:2888:3888

      - ADDITIONAL_ZOOKEEPER_2=server.2=0.0.0.0:2888:3888

      - ADDITIONAL_ZOOKEEPER_3=server.3=zk3.cloud:2888:3888

  zookeeper3:

    image: registry.aliyuncs.com/denverdino/zookeeper:3.4.8

    container_name: zk3.cloud

    environment:

      - SERVER_ID=3

      - ADDITIONAL_ZOOKEEPER_1=server.1=zk1.cloud:2888:3888

      - ADDITIONAL_ZOOKEEPER_2=server.2=zk2.cloud:2888:3888

      - ADDITIONAL_ZOOKEEPER_3=server.3=0.0.0.0:2888:3888

  ui:

    image: registry.aliyuncs.com/denverdino/baqend-storm:1.0.0

    command: ui -c nimbus.host=nimbus

    environment:

      - STORM_ZOOKEEPER_SERVERS=zk1.cloud,zk2.cloud,zk3.cloud

    restart: always

    container_name: ui

    ports:

      - 8080:8080

    depends_on:

      - nimbus

  nimbus:

    image: registry.aliyuncs.com/denverdino/baqend-storm:1.0.0

    command: nimbus -c nimbus.host=nimbus

    restart: always

    environment:

      - STORM_ZOOKEEPER_SERVERS=zk1.cloud,zk2.cloud,zk3.cloud

    container_name: nimbus

    ports:

      - 6627:6627

  supervisor:

    image: registry.aliyuncs.com/denverdino/baqend-storm:1.0.0

    command: supervisor -c nimbus.host=nimbus -c supervisor.slots.ports=[6700,6701,6702,6703]

    restart: always

    environment:

      - affinity:role!=supervisor

      - STORM_ZOOKEEPER_SERVERS=zk1.cloud,zk2.cloud,zk3.cloud

    depends_on:

      - nimbus

networks:

  default:

    external:

      name: zk-net

 

 

拉取Storm搭建需要的镜像,这里我选择镜像版本为 zookeeper:3.4.8  storm:1.0.0

键入命令:

docker pull zookeeper:3.4.8  docker pull storm:1.0.0

 

storm镜像 获取

使用docker-compose 构建集群

在power shell中执行以下命令:

 

docker-compose -f storm.yml up -d

 

                                                                              docker-compose 构建集群

在浏览器中打开localhost:8080 可以看到storm集群的详细情况

 

storm UI 展示

二、Storm统计任务

统计股票交易情况交易量和交易总金额   (数据文件存储在csv文件中)

编写DataSourceSpout类

 

DataSourceSpout类

编写bolt类

 

 

 

编写topology类

 

 

需要注意的是 Storm Java API 下有本地模型和远端模式

在本地模式下的调试不依赖于集群环境,可以进行简单的调试

如果需要使用生产模式,则需要将

1、 编写和自身业务相关的spout和bolt类,并将其打包成一个jar包

 

2、将上述的jar包放到客户端代码能读到的任何位置,

 

3、使用如下方式定义一个拓扑(Topology)

 

 

演示结果:

本地模式下的调试:

 

正在执行:

 

根据24小时

 

 

根据股票种类

 

 

生产模式:

 

向集群提交topology

                                                       

 

 

 

三、核心计算bolt的代码

1.统计不同类型的股票交易量和交易总金额:

package bolt;

 

import java.io.IOException;

import java.util.HashMap;

import java.util.Map;

import java.util.Set;

 

import org.apache.storm.task.OutputCollector;

import org.apache.storm.task.TopologyContext;

import org.apache.storm.topology.OutputFieldsDeclarer;

import org.apache.storm.topology.base.BaseRichBolt;

import org.apache.storm.tuple.Tuple;

import org.apache.storm.tuple.Values;

 

@SuppressWarnings("serial")

public class TypeCountBolt extends BaseRichBolt {

 

    OutputCollector collector;

 

    Map<String,Integer> map = new HashMap<String, Integer>();

 

    Map<String,Float> map2 = new HashMap<String, Float>();

 

 

    public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) {

        this.collector = collector;

 

    }

 

    public void execute(Tuple input) {

        String line = input.getStringByField("line");

        String[] data = line.split(",");

        Integer count = map.get(data[2]);

        Float total_amount = map2.get(data[2]);

        if(count==null){

            count = 0;

        }

        if(total_amount==null){

            total_amount = 0.0f;

        }

        count++;

        total_amount+=Float.parseFloat(data[3]) * Integer.parseInt(data[4]);

        map.put(data[2],count);

        map2.put(data[2],total_amount);

 

        System.out.println("~~~~~~~~~~~~~~~~~~~~~~~");

        Set<Map.Entry<String,Integer>> entrySet = map.entrySet();

        for(Map.Entry<String,Integer> entry :entrySet){

            System.out.println("交易量:");

            System.out.println(entry);

        }

        System.out.println();

        Set<Map.Entry<String,Float>> entrySet2 = map2.entrySet();

        for(Map.Entry<String,Float> entry :entrySet2){

            System.out.println("交易总金额:");

            System.out.println(entry);

        }

    }

 

 

    public void declareOutputFields(OutputFieldsDeclarer declarer) {

    }

 

}

 

 

2. 统计不同每个小时的交易量和交易总金额

package bolt;

 

import org.apache.storm.task.OutputCollector;

import org.apache.storm.task.TopologyContext;

import org.apache.storm.topology.OutputFieldsDeclarer;

import org.apache.storm.topology.base.BaseRichBolt;

import org.apache.storm.tuple.Tuple;

 

import java.text.ParseException;

import java.text.SimpleDateFormat;

import java.util.Date;

import java.util.HashMap;

import java.util.Map;

import java.util.Set;

 

public  class TimeCountBolt extends BaseRichBolt {

    OutputCollector collector;

 

    Map<Integer,Integer> map = new HashMap<Integer, Integer>();

 

    Map<Integer,Float> map2 = new HashMap<Integer, Float>();

 

 

    public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) {

        this.collector = collector;

 

    }

 

    public void execute(Tuple input) {

        String line = input.getStringByField("line");

        String[] data = line.split(",");

 

        Date date = new Date();

        SimpleDateFormat dateFormat= new SimpleDateFormat("yyyy-MM-dd hh:mm:ss");

        try {

            date = dateFormat.parse(data[0]);

        } catch (ParseException e) {

            e.printStackTrace();

        }

 

        Integer count = map.get(date.getHours());

        Float total_amount = map2.get(date.getHours());

        if(count==null){

            count = 0;

        }

        if(total_amount==null){

            total_amount = 0.0f;

        }

        count++;

        total_amount+=Float.parseFloat(data[3]) * Integer.parseInt(data[4]);

        map.put(date.getHours(),count);

        map2.put(date.getHours(),total_amount);

 

        System.out.println("~~~~~~~~~~~~~~~~~~~~~~~");

        Set<Map.Entry<Integer,Integer>> entrySet = map.entrySet();

        for(Map.Entry<Integer,Integer> entry :entrySet){

            System.out.println("交易量:");

            System.out.println(entry);

        }

        System.out.println();

        Set<Map.Entry<Integer,Float>> entrySet2 = map2.entrySet();

        for(Map.Entry<Integer,Float> entry :entrySet2){

            System.out.println("交易总金额:");

            System.out.println(entry);

        }

    }

 

 

    public void declareOutputFields(OutputFieldsDeclarer declarer) {

    }

}

 

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