Flume配置4——自定义MYSQLSource

自定义MySQLSource说明

• 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
• Source 的目的是从外部客户端接收数据并将其存储到配置的 Channels 中
• 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

虚拟机未安装MySQL先安装

1.mysql8(推荐)

2.mysql5

实现

1.新建项目Flume-MySQLSource

2.添加依赖

<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>

3.添加配置信息，不是spring项目，所以没有使用yml配置

• jdbc.properties

dbDriver=com.mysql.jdbc.Driver
dbUrl=jdbc:mysql://hadoop100:3306/mysource?useUnicode=true&characterEncoding=utf-8
dbUser=root
dbPassword=aaaa #linux中的数据库

• 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.DailyRollingFileAppender
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

4.SQLSourceHelper

• 说明
  
  
• 代码分析
  
• 代码实现

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;

/** * @program: Flume-MySQLSource * @description: * @author: 作者 * @create: 2022-06-25 18:50 */
public class SQLSourceHelper {
    
    private static final Logger LOG = LoggerFactory.getLogger(SQLSourceHelper.class);

    private int runQueryDelay;//两次查询的时间间隔
    private int startFrom;//开始id
    private int currentIndex;//当前id
    private int recordSixe = 0;//每次查询返回结果的条数
    private int maxRow;//每次查询的最大条数

    private String table;//要操作的表
    private String columnsToSelect;//用户传入的查询的列
    private String customQuery;//用户传入的查询语句
    private String query;//构建的查询语句
    private String 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().getResourceAsStream("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;
    }
}

5.SQLSource

package com.yc;

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;

/** * @program: Flume-MySQLSource * @description: * @author: 作者 * @create: 2022-06-25 18:57 */
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 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();
        }
    }

    @Override
    public long getBackOffSleepIncrement() {
    
        return 0;
    }

    @Override
    public long getMaxBackOffSleepInterval() {
    
        return 0;
    }
}

6.两个jar放入flume的lib目录下

• 项目jar
  
  
• mysql
  

7./jobs/t9下编写配置文件

• vim mysql-flume-logger.conf

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = com.yc.SQLSource
a1.sources.r1.connection.url = jdbc:mysql://192.168.10.100:3306/mysource
a1.sources.r1.connection.user = root
a1.sources.r1.connection.password = aaaa
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

8.建库，建表

• 建库

CREATE DATABASE mysource;

• 建表

use mysource;
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`)
);

• 插4条数据

 insert into student(name) values ('zhaoliu');

9.启动

bin/flume-ng agent --conf conf --conf-file jobs/t9/mysql-flume-logger.conf --name a1 -Dflume.root.logger==INFO,console

10.类似于如图结果输出则成功