查看“Flink点击流和销售额计算”的源代码

==编写flink程序==
===flinkclass===

实现flink数据处理

(1)在flinkclass里面创建一个'''object对象'''

[[文件:flinkclass1.png]]

Flink实时处理编程过程

 <nowiki>package flinkclass
import java.util.Properties

import mysqlsink.SaleSQLSink
import objectclass.StringAndDouble
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.api.windowing.time.Time
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
import org.apache.flink.api.common.serialization.SimpleStringSchema
object SaleVolumn {
  def main(args: Array[String]): Unit = {
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    //配置Kafka参数
    val pro = new Properties()
    pro.setProperty("bootstrap.servers","192.168.128.130:9092")
    pro.setProperty("group.id","test")
    //创建数据源
    val stream  = env.addSource(new FlinkKafkaConsumer[String]("shop",new SimpleStringSchema(),pro))
    //数据处理过程
    val data = stream.map(x=>x.split(",")).filter(x=>x.nonEmpty && x.length==11)
      .map{x=>if(x(7).contains("buy")) (x(x.length-1),(x(5).toDouble,1.0)) else (x(x.length-1),(0.0,1.0))}.keyBy(0).timeWindow(Time.minutes(1)).reduce((x,y)=>(x._1,(x._2._1+y._2._1,x._2._2+y._2._2)))
    //保存每日销售额到MYSQL表
    data.map(x=>new StringAndDouble(x._1,x._2._1)).addSink(new SaleSQLSink("salevolume"))
    //保存每日点击流到mysql表
    data.map(x=>new StringAndDouble(x._1,x._2._2)).addSink(new SaleSQLSink("visitcount_everyday"))
    env.execute()
  }
}</nowiki>

flink中的时间窗口：https://blog.csdn.net/zg_hover/article/details/87592060

==运行flink程序==
===关闭flink===
[root@master local]# cd /usr/local/flink-1.10.1/bin

[root@master bin]# stop-cluster.sh

 <nowiki>Stopping taskexecutor daemon (pid: 7986) on host slave1.centos.com.
Stopping taskexecutor daemon (pid: 5760) on host slave2.centos.com.
Stopping taskexecutor daemon (pid: 3219) on host slave3.centos.com.
Stopping standalonesession daemon (pid: 11586) on host master.centos.com.</nowiki>

===关闭kafka===
①在所有节点查看kafka的状态,如果运行则kill掉

[[文件:Killkafka.png]]

 jps

 kill -9 3507

===关闭zookeeper===

===启动zookeeper===

必须先启动zookeeper 再启动kafka,不然启动无效,启动kafka里面的zookeeper

nohup bin/zookeeper-server-start.sh config/zookeeper.properties >log/zookeeper/zookeeper.log 2>1 & 

===启动kafka===

③在所有节点启动zookeeper后在master,slave1,slave2上启动kafka

 /usr/local/kafka/bin/kafka-server-start.sh /usr/local/kafka/config/server.propertiec >/tmp/klog &

④Jps查看进程

[[文件:jincheng.png]]

===创建kafka主题===
查看主题是否创建没有则创建shop主题

[root@master kafka_2.11-2.3.1]# bin/kafka-topics.sh --list --zookeeper 192.168.128.130:2181 
  
 <nowiki>__consumer_offsets
shop
test</nowiki>

[root@master kafka_2.11-2.3.1]#bin/kafka-topics.sh  --zookeeper 192.168.128.130:2181  --delete  --topic shop

[root@master kafka_2.11-2.3.1]# bin/kafka-topics.sh -create --zookeeper 192.168.128.130:2181 -replication-factor 1 --partitions 1 --topic shop 

[root@master kafka_2.11-2.3.1]#  bin/kafka-topics.sh --list --zookeeper 192.168.128.130:2181 

 <nowiki>__consumer_offsets
shop
test</nowiki>

===启动flink集群===

⑤在master启动flink集群

 /usr/local/flink/start-cluster.sh

===启动flume采集===
在IDEA中启动flume采集方案时,把之间采集的数据删除掉, 检查模拟采集是否启动

 crontab -e

查看采集的数据：

[root@master bin]# rm -rf /opt/flinkproject/

[root@master bin]# mkdir /opt/flinkproject

[root@master bin]# ls /opt/flinkproject/

 2020-07-25-20-05-01.log

启动之前写好的flume采集方案

/usr/local/flume/bin/flume-ng agent -c /usr/local/flume/conf/ -f /usr/local/flume/conf/spool-memory-kafka.conf -n client -Dflume.root.logger=INFO,console 

===运行flink客户端程序-SaleVolumn===

终于到了IDEA中本地运行项目SaleVolumn,无报错后,进入mysql中查看最开始定义的两个表,mysql表里面就有每日的访问流量和每日的销售额了

[[文件:bd20-6-16.png|600px]]

[[文件:mysqlsale1.png]]

[[文件:Msyqlsale1-1.png]]

==将flink程序打包==
刚才我们是将flink在客户端（PC机）上运行的，

我们还可以将flink程序 放到集群中去运行，这就需要将flink打包。