Flume高级之自定义MySQLSource
1 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
3 自定义MySQLSource组成
2 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
4 代码实现
4.1 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>
4.2 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.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
4.3 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) |
2)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<Object>> |
getAllRows(List<List<Object>> 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
|
3)代码分析
4)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; } }
4.4 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(); } } } 5 测试
5.1 Jar包准备
1) 将MySql驱动包放入Flume的lib目录下
[FLY@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/
2) 打包项目并将Jar包放入Flume的lib目录下
5.5.2 配置文件准备
1)创建配置文件并打开
[FLY@hadoop102 job]$ touch mysql.conf [FLY@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.FLY.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
5.5.3 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
5.5.4 测试并查看结果
1) 任务执行
[FLY@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6-2所示: