一、需求：统计网站访问量（实时统计）
技术选型：特点（数据量大、做计算、实时） 实时流式计算框架：storm 1)spout 数据源，接入数据源 本地文件 2)splitbolt 业务逻辑处理 切分数据 拿到网址 3)bolt 累加次数求和
1、PvCountSpout类
package com.demo.pvcount;
import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.Map;
import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.IRichSpout;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Values;
public class PvCountSpout implements IRichSpout{
private SpoutOutputCollector collector;
private BufferedReader br;
private String line;
@Override
public void nextTuple() {
//发送读取的数据的每一行
try {
while((line = br.readLine())!= null) {
//发送数据到splitbolt
collector.emit(new Values(line));
//设置延迟
Thread.sleep(500);
}
} catch (IOException e) {
e.printStackTrace();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
@Override
public void open(Map arg0, TopologyContext arg1, SpoutOutputCollector collector) {
this.collector = collector;
//读取文件
try {
br = new BufferedReader(new InputStreamReader(new FileInputStream("e:/weblog.log")));
} catch (FileNotFoundException e) {
e.printStackTrace();
}
}
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
//声明
declarer.declare(new Fields("logs"));
}
//处理tuple成功 回调的方法
@Override
public void ack(Object arg0) {
}
//如果spout在失效的模式中 调用此方法来激活
@Override
public void activate() {
}
//在spout程序关闭前执行 不能保证一定被执行 kill -9 是不执行 storm kill 是不执行
@Override
public void close() {
}
//在spout失效期间，nextTuple不会被调用
@Override
public void deactivate() {
}
//处理tuple失败回调的方法
@Override
public void fail(Object arg0) {
}
//配置
@Override
public Map<String, Object> getComponentConfiguration() {
return null;
}
}
2、PvCountSplitBolt类
package com.demo.pvcount;
import java.util.Map;
import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.IRichBolt;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;
public class PvCountSplitBolt implements IRichBolt{
private OutputCollector collector;
//一个bolt即将关闭时调用 不能保证一定被调用 资源清理
@Override
public void cleanup() {
}
private int pvnum = 0;
//业务逻辑 分布式 集群 并发度 线程 （接收tuple然后进行处理）
@Override
public void execute(Tuple input) {
//1.获取数据
String line = input.getStringByField("logs");
//2.切分数据
String[] fields = line.split("\t");
String session_id = fields[1];
//3.局部累加
if (session_id != null) {
//累加
pvnum++;
//输出
collector.emit(new Values(Thread.currentThread().getId(),pvnum));
}
}
//初始化调用
@Override
public void prepare(Map arg0, TopologyContext arg1, OutputCollector collector) {
this.collector = collector;
}
//声明
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
//声明输出
declarer.declare(new Fields("threadid","pvnum"));
}
//配置
@Override
public Map<String, Object> getComponentConfiguration() {
return null;
}
}
3、PvCountSumBolt类
package com.demo.pvcount;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.IRichBolt;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.tuple.Tuple;
public class PvCountSumBolt implements IRichBolt{
private HashMap<Long, Integer> hashMap = new HashMap<>();
@Override
public void cleanup() {
}
//全局累加求和 业务逻辑
@Override
public void execute(Tuple input) {
//1.获取数据
Long threadid = input.getLongByField("threadid");
Integer pvnum = input.getIntegerByField("pvnum");
//2.创建集合 存储(threadid,pvnum) 15 20
hashMap.put(threadid, pvnum);
//3.累加求和(拿到集合中所有value值)
Iterator<Integer> iterator = hashMap.values().iterator();
//4.清空之前的数据
int sumnum = 0;
while (iterator.hasNext()) {
sumnum += iterator.next();
}
System.err.println(Thread.currentThread().getName() + "总访问量为->" + sumnum);
}
@Override
public void prepare(Map arg0, TopologyContext arg1, OutputCollector arg2) {
}
@Override
public void declareOutputFields(OutputFieldsDeclarer arg0) {
}
@Override
public Map<String, Object> getComponentConfiguration() {
return null;
}
}
4、PvCountDriver类
package com.demo.pvcount;
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.tuple.Fields;
public class PvCountDriver {
public static void main(String[] args) {
// 1.hadoop->Job storm->topology 创建拓扑
TopologyBuilder builder = new TopologyBuilder();
// 2.指定设置
builder.setSpout("PvCountSpout", new PvCountSpout(), 1);
builder.setBolt("PvCountSplitBolt", new PvCountSplitBolt(), 6).setNumTasks(4)
.fieldsGrouping("PvCountSpout", new Fields("logs"));
builder.setBolt("PvCountSumBolt", new PvCountSumBolt(), 1).fieldsGrouping("PvCountSplitBolt", new Fields("pvnum"));
// 3.创建配置信息
Config conf = new Config();
conf.setNumWorkers(2);
// 4.提交任务
LocalCluster localCluster = new LocalCluster();
localCluster.submitTopology("pvcounttopology", conf, builder.createTopology());
}
}
5、PvCountDriver_Shuffle类
package com.demo.pvcount;
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.topology.TopologyBuilder;
public class PvCountDriver_Shuffle {
public static void main(String[] args) {
// 1.hadoop->Job storm->topology 创建拓扑
TopologyBuilder builder = new TopologyBuilder();
// 2.指定设置
builder.setSpout("PvCountSpout", new PvCountSpout(), 1);
builder.setBolt("PvCountSplitBolt", new PvCountSplitBolt(), 6).setNumTasks(4)
.shuffleGrouping("PvCountSpout");
builder.setBolt("PvCountSumBolt", new PvCountSumBolt(), 2).shuffleGrouping("PvCountSplitBolt");
// 3.创建配置信息
Config conf = new Config();
conf.setNumWorkers(2);
// 4.提交任务
LocalCluster localCluster = new LocalCluster();
localCluster.submitTopology("pvcounttopology", conf, builder.createTopology());
}
}
6、weblog.log文件
storm.apache.org EEH6Y21245GHI899OFG4V9U567 2018-08-07 10:40:49 storm.apache.org VVVYH6Y4V4SFXZWWEQRQWEQ 2018-08-07 08:40:50 storm.apache.org BBYH61456DEL89RG5VV9UYU7 2018-08-07 10:40:49 storm.apache.org EEH6Y21245GHI899OFG4V9U567 2018-08-07 09:40:49 storm.apache.org CCYH6Y4V4SCVXTG6DPB4VH9U123 2018-08-07 10:40:49 storm.apache.org CCYH6Y4V4SCVXTG6DPB4VH9U123 2018-08-07 12:40:49 storm.apache.org VVVYH6Y4V4SFXZWWEQRQWEQ 2018-08-07 08:40:52 storm.apache.org CCYH6Y4V4SCVXTG6DPB4VH9U123 2018-08-07 08:40:50 storm.apache.org VVVYH6Y4V4SFXZWWEQRQWEQ 2018-08-07 09:40:49......... storm.apache.org EEH6Y21245GHI899OFG4V9U567 2018-08-07 08:40:53 storm.apache.org BBYH61456DEL89RG5VV9UYU7 2018-08-07 12:40:49 storm.apache.org EEH6Y21245GHI899OFG4V9U567 2018-08-07 08:40:51 storm.apache.org EEH6Y21245GHI899OFG4V9U567 2018-08-07 10:40:49 storm.apache.org HUNTERH6YCGFJYERTT834R52FDXV9U34 2018-08-07 08:40:53 storm.apache.org BBYH61456DEL89RG5VV9UYU7 2018-08-07 08:40:50 storm.apache.org EEH6Y21245GHI899OFG4V9U567 2018-08-07 08:40:53 storm.apache.org VVVYH6Y4V4SFXZWWEQRQWEQ 2018-08-07 10:40:49
7、运行（4）中的main方法，控制台显示如下图：
此时在weblog.log文件中增加几条数据，则总访问量相应增加几条。
至此，简单实现了网站访问量实时统计。
原文地址：https://www.cnblogs.com/areyouready/p/10188300.html
时间： 2024-08-28 11:58:40