1 package com.it.baizhan.scalacode.Streaming
2
3 import java.text.SimpleDateFormat
4 import java.util.{Date, Properties}
5
6 import org.apache.kafka.clients.producer.{KafkaProducer, ProducerRecord}
7
8 import scala.util.Random
9
10 /**
11 * 向 kafka 中生产数据
12 */
13 object ProduceDataToKafka {
14 def main(args: Array[String]): Unit = {
15 val props = new Properties()
16 props.put("bootstrap.servers", "mynode1:9092,mynode2:9092,mynode3:9092")
17 props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer")
18 props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer")
19
20 val producer = new KafkaProducer[String,String](props)
21 var counter = 0
22 var keyFlag = 0
23 while(true){
24 counter +=1
25 keyFlag +=1
26 val content: String = userlogs()
27 // producer.send(new ProducerRecord[String, String]("streamingtopic", content))
28 producer.send(new ProducerRecord[String, String]("mytopic", s"key-$keyFlag", content))
29 if(0 == counter%100){
30 counter = 0
31 Thread.sleep(5000)
32 }
33 }
34 producer.close()
35 }
36
37 def userlogs()={
38 val userLogBuffer = new StringBuffer("")
39 val timestamp = new Date().getTime();
40 var userID = 0L
41 var pageID = 0L
42
43 //随机生成的用户ID
44 userID = Random.nextInt(2000)
45
46 //随机生成的页面ID
47 pageID = Random.nextInt(2000);
48
49 //随机生成Channel
50 val channelNames = Array[String]("Spark","Scala","Kafka","Flink","Hadoop","Storm","Hive","Impala","HBase","ML")
51 val channel = channelNames(Random.nextInt(10))
52
53 val actionNames = Array[String]("View", "Register")
54 //随机生成action行为
55 val action = actionNames(Random.nextInt(2))
56
57 val dateToday = new SimpleDateFormat("yyyy-MM-dd").format(new Date())
58 userLogBuffer.append(dateToday)
59 .append("\t")
60 .append(timestamp)
61 .append("\t")
62 .append(userID)
63 .append("\t")
64 .append(pageID)
65 .append("\t")
66 .append(channel)
67 .append("\t")
68 .append(action)
69 System.out.println(userLogBuffer.toString())
70 userLogBuffer.toString()
71 }
72
73 }
