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Flume知识扩展之自定义MySQLSource

大数据小同学 2020-06-12
162

常见正则表达式语法

元字符描述
^匹配输入字符串的开始位置。如果设置了RegExp对象的Multiline属性,^也匹配“\n”或“\r”之后的位置。
$匹配输入字符串的结束位置。如果设置了RegExp对象的Multiline属性,$也匹配“\n”或“\r”之前的位置
*匹配前面的子表达式任意次。例如,zo*能匹配“z”,“zo”以及“zoo”。*等价于{0,}。
+匹配前面的子表达式一次或多次(大于等于1次)。例如,“zo+”能匹配“zo”以及“zoo”,但不能匹配“z”。+等价于{1,}。
[a-z]字符范围。匹配指定范围内的任意字符。例如,“[a-z]”可以匹配“a”到“z”范围内的任意小写字母字符。
注意:只有连字符在字符组内部时,并且出现在两个字符之间时,才能表示字符的范围; 如果出字符组的开头,则只能表示连字符本身.

自定义MySQLSource

自定义Source说明

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

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
PollableSource:从source中提取数据,将其发送到channel。
Configurable:实现了Configurable的任何类都含有一个context,使用context获取配置信息。

代码实现

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>

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.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

SQLSourceHelper

  1. 属性说明:

属性说明(括号中为默认值)
runQueryDelay查询时间间隔(10000)
batchSize缓存大小(100)
startFrom查询语句开始id(0)
currentIndex查询语句当前id,每次查询之前需要查元数据表
recordSixe查询返回条数
table监控的表名
columnsToSelect查询字段(*)
customQuery用户传入的查询语句
query查询语句
defaultCharsetResultSet编码格式(UTF-8)
  1. 方法说明:

方法说明
SQLSourceHelper(Context context)构造方法,初始化属性及获取JDBC连接
InitConnection(String url, String user, String pw)获取JDBC连接
checkMandatoryProperties()校验相关属性是否设置(实际开发中可增加内容)
buildQuery()根据实际情况构建sql语句,返回值String
executeQuery()执行sql语句的查询操作,返回值List<List>
getAllRows(List<List> queryResult)将查询结果转换为String,方便后续操作
updateOffset2DB(int size)根据每次查询结果将offset写入元数据表
execSql(String sql)具体执行sql语句方法
getStatusDBIndex(int startFrom)获取元数据表中的offset
queryOne(String sql)获取元数据表中的offset实际sql语句执行方法
close()关闭资源

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;

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().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;
}
}

MySQLSource

代码实现:

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();
}
}
}

测试

jar包准备

  1. 将mysql驱动包放入flume的lib目录下

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

  1. 打包项目并将jar包放入flume的lib目录下

配置文件准备

  1. 创建配置文件并打开

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

  1. 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.liujh.source.SQLSource
a1.sources.r1.connection.url = jdbc:mysql://192.168.1.102:3306/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

mysql表准备

  1. 创建mysqlsource数据库

CREATE DATABASE mysqlsource;

  1. 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`)
);

  1. 向数据表中添加数据

1 zhangsan
2 lisi
3 wangwu
4 zhaoliu

测试并查看结果

  1. 任务执行

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

  1. 结果展示,如图所示:


简书:https://www.jianshu.com/u/0278602aea1d
CSDN:https://blog.csdn.net/u012387141


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