Flume基础（十二）：自定义 Source MySQLSource

自定义 Source 说明

Source 是负责接收数据到 Flume Agent 的组件。Source 组件可以处理各种类型、各种格式的日志数据，包括 avro、thrift、exec、jms、spooling directory、netcat、sequence generator、

syslog、http、legacy。官方提供的 source 类型已经很多，但是有时候并不能满足实际开发当中的需求，此时我们就需要根据实际需求自定义某些 Source。

如：实时监控 MySQL，从 MySQL 中获取数据传输到 HDFS 或者其他存储框架，所以此时需要我们自己实现 MySQLSource。

 

官方也提供了自定义 source 的接口：

 

官网说明：https://flume.apache.org/FlumeDeveloperGuide.html#source根据官方说明自定义MySource 需要继承 AbstractSource 类并实现 Configurable 和 PollableSource 接口。

 

自定义 MySQLSource 组成

自定义 MySQLSource 步骤

根据官方说明自定义 MySqlSource 需要继承 AbstractSource 类并实现 Configurable 和PollableSource 接口。

实现相应方法：

getBackOffSleepIncrement()//暂不用

getMaxBackOffSleepInterval()//暂不用

configure(Context context)//初始化 context

process()//获取数据（从 MySql 获取数据，业务处理比较复杂，所以我们定义一个专门

的类——SQLSourceHelper 来处理跟 MySql 的交互），封装成 Event 并写入 Channel，这个方法被循环调用stop()//关闭相关的资源 

代码实现

1 导入 Pom 依赖

<dependencies>
 <dependency>
 <groupId>org.apache.flume</groupId>
 <artifactId>flume-ng-core</artifactId>
 <version>1.7.0</version>
 </dependency>
 <dependency>
 <groupId>mysql</groupId>
 <artifactId>mysql-connector-java</artifactId>
 <version>5.1.27</version>
 </dependency>
</dependencies>

2 添加配置信息

在 ClassPath 下添加 jdbc.properties 和 log4j. properties

jdbc.properties:

dbDriver=com.mysql.jdbc.Driver
dbUrl=jdbc:mysql://hadoop102:3306/mysqlsource?useUnicode=true&
characterEncoding=utf-8
dbUser=root
dbPassword=000000

log4j. properties: 

#--------console-----------
log4j.rootLogger=info,myconsole,myfile
log4j.appender.myconsole=org.apache.log4j.ConsoleAppender
log4j.appender.myconsole.layout=org.apache.log4j.SimpleLayout
#log4j.appender.myconsole.layout.ConversionPattern =%d [%t] %-5p 
[%c] - %m%n
#log4j.rootLogger=error,myfile
log4j.appender.myfile=org.apache.log4j.DailyRollingFileAppende
r
log4j.appender.myfile.File=/tmp/flume.log
log4j.appender.myfile.layout=org.apache.log4j.PatternLayout
log4j.appender.myfile.layout.ConversionPattern =%d [%t] %-5p [%c] 
- %m%n

3 SQLSourceHelper 

 

 

 

3）代码分析 

4）代码实现： 

package com.atguigu.source;
import org.apache.flume.Context;
import org.apache.flume.conf.ConfigurationException;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.IOException;
import java.sql.*;
import java.text.ParseException;
import java.util.ArrayList;
import java.util.List;
import java.util.Properties;
public class SQLSourceHelper {
     private static final Logger LOG = 
LoggerFactory.getLogger(SQLSourceHelper.class);
     private int runQueryDelay, //两次查询的时间间隔
         startFrom, //开始 id
         currentIndex, //当前 id

 recordSixe = 0, //每次查询返回结果的条数
 maxRow; //每次查询的最大条数
 private String table, //要操作的表
 columnsToSelect, //用户传入的查询的列
 customQuery, //用户传入的查询语句
 query, //构建的查询语句
 defaultCharsetResultSet;//编码集
 //上下文，用来获取配置文件
 private Context context;
 //为定义的变量赋值（默认值），可在 flume 任务的配置文件中修改
 private static final int DEFAULT_QUERY_DELAY = 10000;
 private static final int DEFAULT_START_VALUE = 0;
 private static final int DEFAULT_MAX_ROWS = 2000;
 private static final String DEFAULT_COLUMNS_SELECT = "*";
 private static final String DEFAULT_CHARSET_RESULTSET = 
"UTF-8";
 private static Connection conn = null;
 private static PreparedStatement ps = null;
 private static String connectionURL, connectionUserName, 
connectionPassword;
 //加载静态资源
static {
 Properties p = new Properties();
 try {
 
p.load(SQLSourceHelper.class.getClassLoader().getResourceAsStr
eam("jdbc.properties"));
 connectionURL = p.getProperty("dbUrl");
 connectionUserName = p.getProperty("dbUser");
 connectionPassword = p.getProperty("dbPassword");
 Class.forName(p.getProperty("dbDriver"));
 } catch (IOException | ClassNotFoundException e) {
 LOG.error(e.toString());
 }
 }
 //获取 JDBC 连接
 private static Connection InitConnection(String url, String 
user, String pw) {
 try {
 Connection conn = DriverManager.getConnection(url, 
user, pw);
 if (conn == null)
 throw new SQLException();
 return conn;
 } catch (SQLException e) {
 e.printStackTrace();
 }
 return null;
 }
 //构造方法
SQLSourceHelper(Context context) throws ParseException {
 //初始化上下文
 this.context = context;
 //有默认值参数：获取 flume 任务配置文件中的参数，读不到的采用默认值
 this.columnsToSelect = 
context.getString("columns.to.select", DEFAULT_COLUMNS_SELECT);
 this.runQueryDelay = context.getInteger("run.query.delay", 
DEFAULT_QUERY_DELAY);
 this.startFrom = context.getInteger("start.from", 
DEFAULT_START_VALUE);
 this.defaultCharsetResultSet = 
context.getString("default.charset.resultset", 
DEFAULT_CHARSET_RESULTSET);
 //无默认值参数：获取 flume 任务配置文件中的参数
 this.table = context.getString("table");
 this.customQuery = context.getString("custom.query");
 connectionURL = context.getString("connection.url");
 connectionUserName = 
context.getString("connection.user");
 connectionPassword = 
context.getString("connection.password");
 conn = InitConnection(connectionURL, connectionUserName, 
connectionPassword);
 //校验相应的配置信息，如果没有默认值的参数也没赋值，抛出异常
 checkMandatoryProperties();
 //获取当前的 id
 currentIndex = getStatusDBIndex(startFrom);
 //构建查询语句
 query = buildQuery();
 }
 //校验相应的配置信息（表，查询语句以及数据库连接的参数）
private void checkMandatoryProperties() {
 if (table == null) {
 throw new ConfigurationException("property table not 
set");
 }
 if (connectionURL == null) {
 throw new ConfigurationException("connection.url 
property not set");
 }
 if (connectionUserName == null) {
 throw new ConfigurationException("connection.user 
property not set");
 }
 if (connectionPassword == null) {
 throw new ConfigurationException("connection.password 
property not set");
 }
 }
 //构建 sql 语句
private String buildQuery() {
 String sql = "";
 //获取当前 id
 currentIndex = getStatusDBIndex(startFrom);
 LOG.info(currentIndex + "");
 if (customQuery == null) {
 sql = "SELECT " + columnsToSelect + " FROM " + table;
 } else {
 sql = customQuery;
 }
 StringBuilder execSql = new StringBuilder(sql);
 //以 id 作为 offset
 if (!sql.contains("where")) {
 execSql.append(" where ");
 
execSql.append("id").append(">").append(currentIndex);
 return execSql.toString();
 } else {
 int length = execSql.toString().length();
 return execSql.toString().substring(0, length -
String.valueOf(currentIndex).length()) + currentIndex;
 }
 }
 //执行查询
List<List<Object>> executeQuery() {
 try {
 //每次执行查询时都要重新生成 sql，因为 id 不同
 customQuery = buildQuery();
 //存放结果的集合
 List<List<Object>> results = new ArrayList<>();
 if (ps == null) {
 //
 ps = conn.prepareStatement(customQuery);
 }
 ResultSet result = ps.executeQuery(customQuery);
 while (result.next()) {
 //存放一条数据的集合（多个列）
 List<Object> row = new ArrayList<>();
 //将返回结果放入集合
 for (int i = 1; i <= 
result.getMetaData().getColumnCount(); i++) {
 row.add(result.getObject(i));
 }
 results.add(row);
 }
 LOG.info("execSql:" + customQuery + "\nresultSize:" + 
results.size());
 return results;
 } catch (SQLException e) {
 LOG.error(e.toString());
 // 重新连接
 conn = InitConnection(connectionURL, 
connectionUserName, connectionPassword);
 }
 return null;
 }
 //将结果集转化为字符串，每一条数据是一个 list 集合，将每一个小的 list
集合转化为字符串
List<String> getAllRows(List<List<Object>> queryResult) {
 List<String> allRows = new ArrayList<>();
 if (queryResult == null || queryResult.isEmpty())
 return allRows;
 StringBuilder row = new StringBuilder();
 for (List<Object> rawRow : queryResult) {
 Object value = null;
 for (Object aRawRow : rawRow) {
 value = aRawRow;
 if (value == null) {
 row.append(",");
 } else {
 row.append(aRawRow.toString()).append(",");
 }
 }
 allRows.add(row.toString());
 row = new StringBuilder();
 }
 return allRows;
 }
 //更新 offset 元数据状态，每次返回结果集后调用。必须记录每次查询的
offset 值，为程序中断续跑数据时使用，以 id 为 offset
 void updateOffset2DB(int size) {
 //以 source_tab 做为 KEY，如果不存在则插入，存在则更新（每个源表对
应一条记录）
 String sql = "insert into 
flume_meta(source_tab,currentIndex) VALUES('"
 + this.table
 + "','" + (recordSixe += size)
 + "') on DUPLICATE key update 
source_tab=values(source_tab),currentIndex=values(currentIndex
)";
 LOG.info("updateStatus Sql:" + sql);
 execSql(sql);
 }
 //执行 sql 语句
private void execSql(String sql) {
 try {
 ps = conn.prepareStatement(sql);
 LOG.info("exec::" + sql);
 ps.execute();
 } catch (SQLException e) {
 e.printStackTrace();
 }
 }
 //获取当前 id 的 offset
private Integer getStatusDBIndex(int startFrom) {
 //从 flume_meta 表中查询出当前的 id 是多少
 String dbIndex = queryOne("select currentIndex from 
flume_meta where source_tab='" + table + "'");
 if (dbIndex != null) {
 return Integer.parseInt(dbIndex);
 }
 //如果没有数据，则说明是第一次查询或者数据表中还没有存入数据，返回
最初传入的值
 return startFrom;
 }
 //查询一条数据的执行语句(当前 id)
private String queryOne(String sql) {
 ResultSet result = null;
 try {
 ps = conn.prepareStatement(sql);
 result = ps.executeQuery();
 while (result.next()) {
 return result.getString(1);
 }
 } catch (SQLException e) {
 e.printStackTrace();
 }
 return null;
 }
 //关闭相关资源
void close() {
 try {
 ps.close();
 conn.close();
 } catch (SQLException e) {
 e.printStackTrace();
 }
 }
 int getCurrentIndex() {
 return currentIndex;
 }
 void setCurrentIndex(int newValue) {
 currentIndex = newValue;
 }
 int getRunQueryDelay() {
 return runQueryDelay;
 }
 String getQuery() {
 return query;
 }
 String getConnectionURL() {
 return connectionURL;
 }
 private boolean isCustomQuerySet() {
 return (customQuery != null);
 }
 Context getContext() {
 return context;
 }
 public String getConnectionUserName() {
 return connectionUserName;
 }
 public String getConnectionPassword() {
 return connectionPassword;
 }
 String getDefaultCharsetResultSet() {
 return defaultCharsetResultSet;
 } }

View Code

4 MySQLSource

代码实现： 

package com.atguigu.source;
import org.apache.flume.Context;
import org.apache.flume.Event;
import org.apache.flume.EventDeliveryException;
import org.apache.flume.PollableSource;
import org.apache.flume.conf.Configurable;
import org.apache.flume.event.SimpleEvent;
import org.apache.flume.source.AbstractSource;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.text.ParseException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
public class SQLSource extends AbstractSource implements 
Configurable, PollableSource {
 //打印日志
private static final Logger LOG = 
LoggerFactory.getLogger(SQLSource.class);
 //定义 sqlHelper
 private SQLSourceHelper sqlSourceHelper;
 @Override
 public long getBackOffSleepIncrement() {
 return 0;
 }
 @Override
 public long getMaxBackOffSleepInterval() {
 return 0;
 }
 @Override
public void configure(Context context) {
 try {
 //初始化
 sqlSourceHelper = new SQLSourceHelper(context);
 } catch (ParseException e) {
 e.printStackTrace();
 }
 }
 @Override
public Status process() throws EventDeliveryException {
 try {
 //查询数据表
 List<List<Object>> result = 
sqlSourceHelper.executeQuery();
 //存放 event 的集合
 List<Event> events = new ArrayList<>();
 //存放 event 头集合
 HashMap<String, String> header = new HashMap<>();
 //如果有返回数据，则将数据封装为 event
 if (!result.isEmpty()) {
 List<String> allRows = 
sqlSourceHelper.getAllRows(result);
 Event event = null;
 for (String row : allRows) {
 event = new SimpleEvent();
 event.setBody(row.getBytes());
 event.setHeaders(header);
 events.add(event);
 }
 //将 event 写入 channel
 
this.getChannelProcessor().processEventBatch(events);
 //更新数据表中的 offset 信息
 sqlSourceHelper.updateOffset2DB(result.size());
 }
 //等待时长
 Thread.sleep(sqlSourceHelper.getRunQueryDelay());
 return Status.READY;
 } catch (InterruptedException e) {
 LOG.error("Error procesing row", e);
 return Status.BACKOFF;
 }
 }
 @Override
public synchronized void stop() {
 LOG.info("Stopping sql source {} ...", getName());
 try {
 //关闭资源
 sqlSourceHelper.close();
 } finally {
 super.stop();
 }
 } }

View Code

5 测试

5.1 Jar 包准备

1) 将 MySql 驱动包放入 Flume 的 lib 目录下

[atguigu@hadoop102 flume]$ cp \
/opt/sorfware/mysql-libs/mysql-connector-java-5.1.27/mysql-con
nector-java-5.1.27-bin.jar \
/opt/module/flume/lib/

2) 打包项目并将 Jar 包放入 Flume 的 lib 目录下

5.2 配置文件准备

1）创建配置文件并打开

[atguigu@hadoop102 job]$ touch mysql.conf
[atguigu@hadoop102 job]$ vim mysql.conf

2）添加如下内容

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# Describe/configure the source
a1.sources.r1.type = com.atguigu.source.SQLSource 
a1.sources.r1.connection.url = 
jdbc:mysql://192.168.9.102:3306/mysqlsource
a1.sources.r1.connection.user = root 
a1.sources.r1.connection.password = 000000 
a1.sources.r1.table = student 
a1.sources.r1.columns.to.select = * 
#a1.sources.r1.incremental.column.name = id
#a1.sources.r1.incremental.value = 0 
a1.sources.r1.run.query.delay=5000
# Describe the sink
a1.sinks.k1.type = logger
# Describe the channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

5.3 MySql 表准备

1) 创建 MySqlSource 数据库

CREATE DATABASE mysqlsource；

2) 在 MySqlSource 数据库下创建数据表 Student 和元数据表 Flume_meta

CREATE TABLE `student` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(255) NOT NULL,
PRIMARY KEY (`id`)
);
CREATE TABLE `flume_meta` (
`source_tab` varchar(255) NOT NULL,
`currentIndex` varchar(255) NOT NULL,
PRIMARY KEY (`source_tab`)
);

3) 向数据表中添加数据

1 zhangsan
2 lisi
3 wangwu
4 zhaoliu

.5.4 测试并查看结果

1) 任务执行

[atguigu@hadoop102 flume]$ bin/flume-ng agent --conf conf/ --name 
a1 \
--conf-file job/mysql.conf -Dflume.root.logger=INFO,console

2) 结果展示，如图 6-2 所示：