本文内容可查看目录
本文内容包含单节点(单agent)和多节点(多agent,采集远程日志)说明
一、环境
linux系统:Centos7
Jdk:1.7
Flume:1.7.0
二、安装
linux中jdk、mysql的安装不多赘述
flume1.7的安装:进入官网:http://flume.apache.org/
然后找到1.7版本下载放到centos系统解压即可
三、准备数据库表
注,本文flume的event是execSource来源。即通过执行linux命令获得执行结果作为flume的数据源。通过自定义MysqlSink作为flume的sink。
创建sql语句:
CREATE TABLE `flume_test` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(255) DEFAULT NULL,
`age` int(11) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
四、MysqlSink编写
4.1.maven创建项目(打包方式为jar)
pom.xml文件:
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>yichao.mym</groupId>
<artifactId>flumeDemo</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
<dependencies>
<dependency>
<groupId>org.apache.flume</groupId>
<artifactId>flume-ng-core</artifactId>
<version>1.7.0</version>
</dependency>
<dependency>
<groupId>org.apache.flume</groupId>
<artifactId>flume-ng-configuration</artifactId>
<version>1.7.0</version>
</dependency>
<!-- https://mvnrepository.com/artifact/mysql/mysql-connector-java -->
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.15</version>
</dependency>
</dependencies>
</project>
4.2 准备java Bean
与数据库表对应的javabean,方便处理event的body(event的body就是execSource的命令读取的内容)
package yichao.mym.base.bean;
public class Person {
private String name;
private Integer age;
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public Integer getAge() {
return age;
}
public void setAge(Integer age) {
this.age = age;
}
}
4.3 自定义的sink编写
说明都在代码中
package yichao.mym.base.bean;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.SQLException;
import java.util.List;
import org.apache.flume.Channel;
import org.apache.flume.Context;
import org.apache.flume.Event;
import org.apache.flume.EventDeliveryException;
import org.apache.flume.Transaction;
import org.apache.flume.conf.Configurable;
import org.apache.flume.sink.AbstractSink;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.google.common.base.Preconditions;
import com.google.common.base.Throwables;
import com.google.common.collect.Lists;
public class MysqlSink extends AbstractSink implements Configurable {
private Logger LOG = LoggerFactory.getLogger(MysqlSink.class);
private String hostname;
private String port;
private String databaseName;
private String tableName;
private String user;
private String password;
private PreparedStatement preparedStatement;
private Connection conn;
private int batchSize; //每次提交的批次大小
public MysqlSink() {
LOG.info("MySqlSink start...");
}
/**实现Configurable接口中的方法:可获取配置文件中的属性*/
public void configure(Context context) {
hostname = context.getString("hostname");
Preconditions.checkNotNull(hostname, "hostname must be set!!");
port = context.getString("port");
Preconditions.checkNotNull(port, "port must be set!!");
databaseName = context.getString("databaseName");
Preconditions.checkNotNull(databaseName, "databaseName must be set!!");
tableName = context.getString("tableName");
Preconditions.checkNotNull(tableName, "tableName must be set!!");
user = context.getString("user");
Preconditions.checkNotNull(user, "user must be set!!");
password = context.getString("password");
Preconditions.checkNotNull(password, "password must be set!!");
batchSize = context.getInteger("batchSize", 100); //设置了batchSize的默认值
Preconditions.checkNotNull(batchSize > 0, "batchSize must be a positive number!!");
}
/**
* 服务启动时执行的代码,这里做准备工作
*/
@Override
public void start() {
super.start();
try {
//调用Class.forName()方法加载驱动程序
Class.forName("com.mysql.jdbc.Driver");
} catch (ClassNotFoundException e) {
e.printStackTrace();
}
String url = "jdbc:mysql://" + hostname + ":" + port + "/" + databaseName;
//调用DriverManager对象的getConnection()方法,获得一个Connection对象
try {
conn = DriverManager.getConnection(url, user, password);
conn.setAutoCommit(false);
//创建一个Statement对象
preparedStatement = conn.prepareStatement("insert into " + tableName +
" (name,age) values (?,?)");
} catch (SQLException e) {
e.printStackTrace();
System.exit(1);
}
}
/**
* 服务关闭时执行
*/
@Override
public void stop() {
super.stop();
if (preparedStatement != null) {
try {
preparedStatement.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
if (conn != null) {
try {
conn.close();
} catch (SQLException e) {
e.printStackTrace();
}
}
}
/**
* 执行的事情:<br/>
(1)持续不断的从channel中获取event放到batchSize大小的数组中<br/>
(2)event可以获取到则进行event处理,否则返回Status.BACKOFF标识没有数据提交<br/>
(3)batchSize中有内容则进行jdbc提交<br/>
*/
public Status process() throws EventDeliveryException {
Status result = Status.READY;
Channel channel = getChannel();
Transaction transaction = channel.getTransaction();
Event event;
String content;
List<Person> persons = Lists.newArrayList();
transaction.begin();
try {
/*event处理*/
for (int i = 0; i < batchSize; i++) {
event = channel.take();
if (event != null) {//对事件进行处理
//event 的 body 为 "exec tail-event-$i , $i"
content = new String(event.getBody());
Person person=new Person();
if (content.contains(",")) {
//存储 event 的 content
person.setName(content.substring(0, content.indexOf(",")));
//存储 event 的 create +1 是要减去那个 ","
person.setAge(Integer.parseInt(content.substring(content.indexOf(",")+1).trim()));
}else{
person.setName(content);
}
persons.add(person);
} else {
result = Status.BACKOFF;
break;
}
}
/*jdbc提交*/
if (persons.size() > 0) {
preparedStatement.clearBatch();
for (Person temp : persons) {
preparedStatement.setString(1, temp.getName());
preparedStatement.setInt(2, temp.getAge());
preparedStatement.addBatch();
}
preparedStatement.executeBatch();
conn.commit();
}
transaction.commit();
} catch (Exception e) {
try {
transaction.rollback();
} catch (Exception e2) {
LOG.error("Exception in rollback. Rollback might not have been.successful.", e2);
}
LOG.error("Failed to commit transaction.Transaction rolled back.", e);
Throwables.propagate(e);
} finally {
transaction.close();
}
return result;
}
}
编写好后打包成jar,发送到
flume安装目录下的lib文件夹中。同时
把mysql的驱动包mysql-connector-java一起放过去
4.4 conf配置:编写mysqlSink.conf(单agent的测试)
在flume的conf 文件夹下新建配置文件 mysqlSink.conf 内容如下:
agent1.sources=source1
agent1.channels=channel1
agent1.sinks=mysqlSink
# describe/configure source1
# type:exec is through linux command like 'tail -F' to collect logData
agent1.sources.source1.type=exec
agent1.sources.source1.command=tail -F /usr/local/tomcat/logs/ac.log
agent1.sources.source1.channels=channel1
# use a channel which buffers events in memory
# type:memory or file is to temporary to save buffer data which is sink using
agent1.channels.channel1.type=memory
agent1.channels.channel1.capacity=5000
agent1.channels.channel1.transactionCapacity=1000
# describe sink. there are using mysqlSink that is a jar
agent1.sinks.mysqlSink.type=yichao.mym.base.bean.MysqlSink
agent1.sinks.mysqlSink.hostname=localhost
agent1.sinks.mysqlSink.port=3306
agent1.sinks.mysqlSink.databaseName=firstflume
agent1.sinks.mysqlSink.tableName=flume_test
agent1.sinks.mysqlSink.user=root
agent1.sinks.mysqlSink.password=123456
agent1.sinks.mysqlSink.channel=channel1
agent1.sinks.mysqlSink.batchSize=5
说明:
(1)localhost 为mysql 数据库所在的服务器IP;
(2)/usr/local/tomcat/logs/ac.log;
(3)yichao.mym.base.bean.MysqlSink是自定义sink的mysqlsink的全称;
重点:capacity(channel大小) > transactionCapacity(大小是每次flume的事务大小) > batchSize(sink会一次从channel中取多少个event去发送)。
这些数值应根据实时性要求、并发量、占用系统资源等方面权衡设计,但必须遵循以上标准。flume官方却没有这样的说明,一旦没有遵循,执行过程中就会报错!
五、准备测试
启动flume:在flume安装目录下的bin目录中:
./flume-ng agent -c ../conf -f ../conf/mysqlSink.conf -n agent1 -Dflume.root.logger=INFO,console
启动服务后,可以模拟log文件的动态增长,新开终端,通过shell命令:
for i in {1..100};do echo "exec tail-name-$i,$i" >> /usr/local/tomcat/logs/ac.log;sleep 1;done;
此时可以快速刷新数据库的数据表,可以看到数据正在动态增长:
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六、多节点多agent
1.说明架构方式
两台可互相通信的linux机器:
201机器:安装好jdk1.7,mysql,flume1.7
202机器:安装好jdk1.7,flume1.7
结构:
不过本案例中,agent1、agent2、agent3都是execSource源,即直接读取磁盘上的log文件,而不是log4j直接作为agent的source。
那么对于本案例,202机器就作为其中一个agent收集者(agent1、agent2、agent3),把从本机上收集的log内容发送到远程的201机器。他们之间就是使用avro作为传输协议。
所以本案例202机器的:
source:exec (tail -F /usr/local/tomcat/logs/ac.log)
channel:memory
sink:avro
本案例201机器的:
source:avro
channel:memory
sink:自定义的mysqlSink
注:表、自定义的sink的jar、javaBean都和之前的一致
2.两个agent的配置文件conf
202机器的flume配置文件:tail-avro.conf
agent1.sources=source1
agent1.channels=channel1
agent1.sinks=mysqlSink
# describe/configure source1
# type:exec is through linux command like 'tail -F' to collect logData
agent1.sources.source1.type=exec
agent1.sources.source1.command=tail -F /usr/local/tomcat/logs/ac.log
agent1.sources.source1.channels=channel1
# use a channel which buffers events in memory
# type:memory or file is to temporary to save buffer data which is sink using
agent1.channels.channel1.type=memory
agent1.channels.channel1.capacity=5000
agent1.channels.channel1.transactionCapacity=1000
agent1.sinks.mysqlSink.type=avro
agent1.sinks.mysqlSink.channel=channel1
agent1.sinks.mysqlSink.hostname=192.168.216.201
agent1.sinks.mysqlSink.port=4545
agent1.sinks.mysqlSink.batch-size=5
201机器的flume配置文件:avro-mysql.conf
agent1.sources=source1
agent1.channels=channel1
agent1.sinks=mysqlSink
# describe/configure source1
# type:avro is through net-protocal-transport to collect logData
agent1.sources.source1.type = avro
agent1.sources.source1.channels = channel1
agent1.sources.source1.bind = 192.168.216.201
agent1.sources.source1.port = 4545
# use a channel which buffers events in memory
# type:memory or file is to temporary to save buffer data which is sink using
agent1.channels.channel1.type=memory
agent1.channels.channel1.capacity=5000
agent1.channels.channel1.transactionCapacity=1000
# describe sink. there are using mysqlSink that is a jar
agent1.sinks.mysqlSink.type=yichao.mym.base.bean.MysqlSink
agent1.sinks.mysqlSink.hostname=localhost
agent1.sinks.mysqlSink.port=3306
agent1.sinks.mysqlSink.databaseName=firstflume
agent1.sinks.mysqlSink.tableName=flume_test
agent1.sinks.mysqlSink.user=root
agent1.sinks.mysqlSink.password=123456
agent1.sinks.mysqlSink.channel=channel1
agent1.sinks.mysqlSink.batchSize=5
分别配置好并且启动服务。(可先启动机器201,因为机器202需要连接机器201)
3.启动测试
机器 201 的flume启动命令:在flume目录下的bin目录中执行
./flume-ng agent -c ../conf -f ../conf/avro-mysql.conf -n agent1 -Dflume.root.logger=INFO,console
机器 202 的flume启动命令:在flume目录下的bin目录中执行
./flume-ng agent -c ../conf -f ../conf/tail-avro.conf -n agent1 -Dflume.root.logger=INFO,console
启动完之后在机器202上进行模拟log文件数据动态生成:
for i in {1..150};do echo "exec tail-name-$i,$i" >> /usr/local/tomcat/logs/ac.log;sleep 1;done;
此时可以查看机器201上的数据库表的数据是否有动态添加:
至此多节点agent的测试完成!