背景
最近项目中使用Flink消费kafka消息,并将消费的消息存储到mysql中,看似一个很简单的需求,在网上也有很多flink消费kafka的例子,但看了一圈也没看到能解决重复消费的问题的文章,于是在flink官网中搜索此类场景的处理方式,发现官网也没有实现flink到mysql的Exactly-Once例子,但是官网却有类似的例子来解决端到端的仅一次消费问题。这个现成的例子就是FlinkKafkaProducer011这个类,它保证了通过FlinkKafkaProducer011发送到kafka的消息是Exactly-Once的,主要的实现方式就是继承了TwoPhaseCommitSinkFunction这个类,关于TwoPhaseCommitSinkFunction这个类的作用可以先看上一篇文章:https://blog.51cto.com/simplelife/2401411。
实现思想
这里简单说下这个类的作用就是实现这个类的方法:beginTransaction、preCommit、commit、abort,达到事件(preCommit)预提交的逻辑(当事件进行自己的逻辑处理后进行预提交,如果预提交成功之后才进行真正的(commit)提交,如果预提交失败则调用abort方法进行事件的回滚操作),结合flink的checkpoint机制,来保存topic中partition的offset。
达到的效果我举个例子来说明下:比如checkpoint每10s进行一次,此时用FlinkKafkaConsumer011实时消费kafka中的消息,消费并处理完消息后,进行一次预提交数据库的操作,如果预提交没有问题,10s后进行真正的插入数据库操作,如果插入成功,进行一次checkpoint,flink会自动记录消费的offset,可以将checkpoint保存的数据放到hdfs中,如果预提交出错,比如在5s的时候出错了,此时Flink程序就会进入不断的重启中,重启的策略可以在配置中设置,当然下一次的checkpoint也不会做了,checkpoint记录的还是上一次成功消费的offset,本次消费的数据因为在checkpoint期间,消费成功,但是预提交过程中失败了,注意此时数据并没有真正的执行插入操作,因为预提交(preCommit)失败,提交(commit)过程也不会发生了。等你将异常数据处理完成之后,再重新启动这个Flink程序,它会自动从上一次成功的checkpoint中继续消费数据,以此来达到Kafka到Mysql的Exactly-Once。
具体实现代码三个类
- StreamDemoKafka2Mysql.java
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import org.apache.flink.runtime.state.filesystem.FsStateBackend;
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import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode;
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import org.apache.flink.streaming.api.CheckpointingMode;
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import org.apache.flink.streaming.api.datastream.DataStreamSource;
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import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
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import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011;
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import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase;
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import org.apache.flink.streaming.util.serialization.JSONKeyValueDeserializationSchema;
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import org.apache.kafka.clients.consumer.ConsumerConfig;
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import java.util.Properties;
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/**
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* Created with IntelliJ IDEA.
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* User: zzy
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* Date: 2019/5/28
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* Time: 8:40 PM
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* To change this template use File | Settings | File Templates.
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*
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* 消费kafka消息,sink(自定义)到mysql中,保证kafka to mysql 的Exactly-Once
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*/
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public class StreamDemoKafka2Mysql {
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private static final String topic_ExactlyOnce = "mysql-exactly-Once-4";
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public static void main(String[] args) throws Exception {
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StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
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//设置并行度,为了方便测试,查看消息的顺序,这里设置为1,可以更改为多并行度
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env.setParallelism(1);
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//checkpoint的设置
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//每隔10s进行启动一个检查点【设置checkpoint的周期】
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env.enableCheckpointing(10000);
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//设置模式为:exactly_one,仅一次语义
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env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
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//确保检查点之间有1s的时间间隔【checkpoint最小间隔】
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env.getCheckpointConfig().setMinPauseBetweenCheckpoints(1000);
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//检查点必须在10s之内完成,或者被丢弃【checkpoint超时时间】
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env.getCheckpointConfig().setCheckpointTimeout(10000);
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//同一时间只允许进行一次检查点
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env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
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//表示一旦Flink程序被cancel后,会保留checkpoint数据,以便根据实际需要恢复到指定的checkpoint
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//env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
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//设置statebackend,将检查点保存在hdfs上面,默认保存在内存中。这里先保存到本地
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// env.setStateBackend(new FsStateBackend("file:///Users/temp/cp/"));
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//设置kafka消费参数
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Properties props = new Properties();
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props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "zzy:9092");
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props.put(ConsumerConfig.GROUP_ID_CONFIG, "flink-consumer-group2");
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//kafka分区自动发现周期
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props.put(FlinkKafkaConsumerBase.KEY_PARTITION_DISCOVERY_INTERVAL_MILLIS, "3000");
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/*SimpleStringSchema可以获取到kafka消息,JSONKeyValueDeserializationSchema可以获取都消息的key,value,metadata:topic,partition,offset等信息*/
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FlinkKafkaConsumer011<ObjectNode> kafkaConsumer011 = new FlinkKafkaConsumer011<>(topic_ExactlyOnce, new JSONKeyValueDeserializationSchema(true), props);
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//加入kafka数据源
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DataStreamSource<ObjectNode> streamSource = env.addSource(kafkaConsumer011);
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// System.out.println("streamSource:" + streamSource.print());
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streamSource.print();
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//数据传输到下游
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streamSource.addSink(new MySqlTwoPhaseCommitSink()).name("MySqlTwoPhaseCommitSink");
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//触发执行
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env.execute(StreamDemoKafka2Mysql.class.getName());
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}
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}
2.MySqlTwoPhaseCommitSink.java
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import org.apache.flink.api.common.ExecutionConfig;
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import org.apache.flink.api.common.typeutils.TypeSerializer;
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import org.apache.flink.api.common.typeutils.base.VoidSerializer;
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import org.apache.flink.api.java.typeutils.runtime.kryo.KryoSerializer;
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import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode;
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import org.apache.flink.streaming.api.functions.sink.SinkFunction;
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import org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import java.sql.Connection;
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import java.sql.PreparedStatement;
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import java.sql.Timestamp;
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import java.text.SimpleDateFormat;
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import java.util.Date;
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/**
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* Created with IntelliJ IDEA.
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* User: zzy
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* Date: 2019/5/28
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* Time: 8:47 PM
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* To change this template use File | Settings | File Templates.
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*
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* 自定义kafka to mysql,继承TwoPhaseCommitSinkFunction,实现两阶段提交
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*/
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public class MySqlTwoPhaseCommitSink extends TwoPhaseCommitSinkFunction<ObjectNode,Connection,Void> {
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private static final Logger log = LoggerFactory.getLogger(MySqlTwoPhaseCommitSink.class);
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public MySqlTwoPhaseCommitSink(){
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super(new KryoSerializer<>(Connection.class,new ExecutionConfig()), VoidSerializer.INSTANCE);
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}
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/**
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* 执行数据库入库操作 task初始化的时候调用
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* @param connection
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* @param objectNode
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* @param context
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* @throws Exception
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*/
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protected void invoke(Connection connection, ObjectNode objectNode, Context context) throws Exception {
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log.info("start invoke...");
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String date = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date());
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log.info("===>date:" + date + " " + objectNode);
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log.info("===>date:{} --{}",date,objectNode);
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String value = objectNode.get("value").toString();
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log.info("objectNode-value:" + value);
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JSONObject valueJson = JSONObject.parseObject(value);
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String value_str = (String) valueJson.get("value");
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String sql = "insert into `mysqlExactlyOnce_test` (`value`,`insert_time`) values (?,?)";
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PreparedStatement ps = connection.prepareStatement(sql);
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ps.setString(1,value_str);
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Timestamp value_time = new Timestamp(System.currentTimeMillis());
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ps.setTimestamp(2,value_time);
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log.info("要插入的数据:{}--{}",value_str,value_time);
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//执行insert语句
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ps.execute();
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//手动制造异常
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if(Integer.parseInt(value_str) == 15) {
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System.out.println(1 / 0);
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}
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}
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/**
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* 获取连接,开启手动提交事物(getConnection方法中)
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* @return
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* @throws Exception
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*/
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protected Connection beginTransaction() throws Exception {
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log.info("start beginTransaction.......");
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String url = "jdbc:mysql://localhost:3306/test?useUnicode=true&characterEncoding=UTF-8&zeroDateTimeBehavior=convertToNull&useSSL=false&autoReconnect=true";
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Connection connection = DBConnectUtil.getConnection(url, "root", "123456");
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return connection;
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}
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/**
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*预提交,这里预提交的逻辑在invoke方法中
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* @param connection
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* @throws Exception
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*/
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protected void preCommit(Connection connection) throws Exception {
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log.info("start preCommit...");
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}
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/**
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* 如果invoke方法执行正常,则提交事务
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* @param connection
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*/
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protected void commit(Connection connection) {
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log.info("start commit...");
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DBConnectUtil.commit(connection);
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}
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/**
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* 如果invoke执行异常则回滚事物,下一次的checkpoint操作也不会执行
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* @param connection
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*/
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protected void abort(Connection connection) {
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log.info("start abort rollback...");
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DBConnectUtil.rollback(connection);
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}
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}
3.DBConnectUtil.java
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import java.sql.DriverManager;
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import java.sql.SQLException;
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import java.sql.Connection;
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/**
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* Created with IntelliJ IDEA.
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* User: zzy
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* Date: 2019/5/28
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* Time: 8:58 PM
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* To change this template use File | Settings | File Templates.
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*/
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public class DBConnectUtil {
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private static final Logger log = LoggerFactory.getLogger(DBConnectUtil.class);
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/**
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* 获取连接
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*
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* @param url
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* @param user
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* @param password
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* @return
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* @throws SQLException
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*/
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public static Connection getConnection(String url, String user, String password) throws SQLException {
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Connection conn = null;
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try {
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Class.forName("com.mysql.jdbc.Driver");
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} catch (ClassNotFoundException e) {
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log.error("获取mysql.jdbc.Driver失败");
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e.printStackTrace();
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}
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try {
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conn = DriverManager.getConnection(url, user, password);
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log.info("获取连接:{} 成功...",conn);
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}catch (Exception e){
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log.error("获取连接失败,url:" + url + ",user:" + user);
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}
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//设置手动提交
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conn.setAutoCommit(false);
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return conn;
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}
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/**
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* 提交事物
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*/
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public static void commit(Connection conn) {
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if (conn != null) {
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try {
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conn.commit();
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} catch (SQLException e) {
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log.error("提交事物失败,Connection:" + conn);
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e.printStackTrace();
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} finally {
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close(conn);
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}
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}
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}
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/**
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* 事物回滚
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*
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* @param conn
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*/
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public static void rollback(Connection conn) {
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if (conn != null) {
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try {
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conn.rollback();
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} catch (SQLException e) {
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log.error("事物回滚失败,Connection:" + conn);
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e.printStackTrace();
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} finally {
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close(conn);
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}
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}
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}
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/**
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* 关闭连接
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*
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* @param conn
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*/
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public static void close(Connection conn) {
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if (conn != null) {
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try {
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conn.close();
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} catch (SQLException e) {
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log.error("关闭连接失败,Connection:" + conn);
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e.printStackTrace();
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}
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}
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}
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}
4.代码测试
为了方便发送消息,我用一个定时任务每秒发送一个数字,1~20,往kafka写日志的程序
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public class KafkaUtils {
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// private static final String broker_list = "localhost:9092";
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private static final String broker_list = "zzy:9092";
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//flink 读取kafka写入mysql exactly-once 的topic
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private static final String topic_ExactlyOnce = "mysql-exactly-Once-4";
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public static void writeToKafka2() throws InterruptedException {
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Properties props = new Properties();
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props.put("bootstrap.servers", broker_list);
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props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
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props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
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// KafkaProducer producer = new KafkaProducer<String, String>(props);//老版本producer已废弃
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Producer<String, String> producer = new org.apache.kafka.clients.producer.KafkaProducer<>(props);
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try {
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for (int i = 1; i <= 20; i++) {
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MysqlExactlyOncePOJO mysqlExactlyOnce = new MysqlExactlyOncePOJO(String.valueOf(i));
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ProducerRecord record = new ProducerRecord<String, String>(topic_ExactlyOnce, null, null, JSON.toJSONString(mysqlExactlyOnce));
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producer.send(record);
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System.out.println("发送数据: " + JSON.toJSONString(mysqlExactlyOnce));
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Thread.sleep(1000);
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}
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}catch (Exception e){
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}
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producer.flush();
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}
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public static void main(String[] args) throws InterruptedException {
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writeToKafka2();
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}
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}
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public class MysqlExactlyOncePOJO {
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private String value;
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}
在发送到数字15之前,应该是做过一次checkpoint了,并且快要到第二次checkpoint的时间,第一次checkpoint的消费数据成功将插入数据库中,在消费到数字15的时候,手动造一个异常,此时数据库中应该只有第一次checkpoint后commit的数据,第二次checkpoint的数据并不会插入到数据库中(因为预提交已经失败,不会进行真正的提交),我实验的日志信息:
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19/06/01 14:52:07 INFO TypeExtractor: Class class org.apache.flink.streaming.connectors.kafka.internals.KafkaTopicPartition cannot be used as a POJO type because not all fields are valid POJO fields, and must be processed as GenericType. Please read the Flink documentation on "Data Types & Serialization" for details of the effect on performance.
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19/06/01 14:52:07 INFO FlinkKafkaConsumerBase: Setting restore state in the FlinkKafkaConsumer: {KafkaTopicPartition{topic='mysql-exactly-Once-4', partition=0}=10}
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19/06/01 14:52:07 INFO ConsumerConfig: ConsumerConfig values:
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auto.commit.interval.ms = 5000
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auto.offset.reset = latest
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bootstrap.servers = [zzy:9092]
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check.crcs = true
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client.id =
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connections.max.idle.ms = 540000
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enable.auto.commit = true
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exclude.internal.topics = true
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fetch.max.bytes = 52428800
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fetch.max.wait.ms = 500
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fetch.min.bytes = 1
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group.id = flink-consumer-group2
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heartbeat.interval.ms = 3000
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interceptor.classes = null
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internal.leave.group.on.close = true
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isolation.level = read_uncommitted
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key.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
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max.partition.fetch.bytes = 1048576
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max.poll.interval.ms = 300000
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max.poll.records = 500
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metadata.max.age.ms = 300000
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metric.reporters = []
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metrics.num.samples = 2
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metrics.recording.level = INFO
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metrics.sample.window.ms = 30000
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partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
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receive.buffer.bytes = 65536
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reconnect.backoff.max.ms = 1000
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reconnect.backoff.ms = 50
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request.timeout.ms = 305000
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retry.backoff.ms = 100
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sasl.jaas.config = null
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sasl.kerberos.kinit.cmd = /usr/bin/kinit
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sasl.kerberos.min.time.before.relogin = 60000
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sasl.kerberos.service.name = null
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sasl.kerberos.ticket.renew.jitter = 0.05
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sasl.kerberos.ticket.renew.window.factor = 0.8
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sasl.mechanism = GSSAPI
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security.protocol = PLAINTEXT
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send.buffer.bytes = 131072
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session.timeout.ms = 10000
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ssl.cipher.suites = null
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ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
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ssl.endpoint.identification.algorithm = null
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ssl.key.password = null
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ssl.keymanager.algorithm = SunX509
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ssl.keystore.location = null
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ssl.keystore.password = null
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ssl.keystore.type = JKS
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ssl.protocol = TLS
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ssl.provider = null
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ssl.secure.random.implementation = null
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ssl.trustmanager.algorithm = PKIX
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ssl.truststore.location = null
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ssl.truststore.password = null
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ssl.truststore.type = JKS
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value.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
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19/06/01 14:52:07 WARN ConsumerConfig: The configuration 'flink.partition-discovery.interval-millis' was supplied but isn't a known config.
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19/06/01 14:52:07 INFO AppInfoParser: Kafka version : 0.11.0.0
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19/06/01 14:52:07 INFO AppInfoParser: Kafka commitId : cb8625948210849f
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19/06/01 14:52:07 INFO FlinkKafkaConsumerBase: Consumer subtask 0 will start reading 1 partitions with offsets in restored state: {KafkaTopicPartition{topic='mysql-exactly-Once-4', partition=0}=10}
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19/06/01 14:52:07 INFO ConsumerConfig: ConsumerConfig values:
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auto.commit.interval.ms = 5000
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auto.offset.reset = latest
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bootstrap.servers = [zzy:9092]
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check.crcs = true
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client.id =
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connections.max.idle.ms = 540000
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enable.auto.commit = false
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exclude.internal.topics = true
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fetch.max.bytes = 52428800
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fetch.max.wait.ms = 500
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fetch.min.bytes = 1
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group.id = flink-consumer-group2
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heartbeat.interval.ms = 3000
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interceptor.classes = null
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internal.leave.group.on.close = true
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isolation.level = read_uncommitted
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key.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
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max.partition.fetch.bytes = 1048576
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max.poll.interval.ms = 300000
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max.poll.records = 500
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metadata.max.age.ms = 300000
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metric.reporters = []
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metrics.num.samples = 2
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metrics.recording.level = INFO
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metrics.sample.window.ms = 30000
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partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
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receive.buffer.bytes = 65536
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reconnect.backoff.max.ms = 1000
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reconnect.backoff.ms = 50
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request.timeout.ms = 305000
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retry.backoff.ms = 100
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sasl.jaas.config = null
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sasl.kerberos.kinit.cmd = /usr/bin/kinit
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sasl.kerberos.min.time.before.relogin = 60000
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sasl.kerberos.service.name = null
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sasl.kerberos.ticket.renew.jitter = 0.05
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sasl.kerberos.ticket.renew.window.factor = 0.8
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sasl.mechanism = GSSAPI
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security.protocol = PLAINTEXT
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send.buffer.bytes = 131072
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session.timeout.ms = 10000
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ssl.cipher.suites = null
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ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
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ssl.endpoint.identification.algorithm = null
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ssl.key.password = null
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ssl.keymanager.algorithm = SunX509
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ssl.keystore.location = null
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ssl.keystore.password = null
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ssl.keystore.type = JKS
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ssl.protocol = TLS
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ssl.provider = null
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ssl.secure.random.implementation = null
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ssl.trustmanager.algorithm = PKIX
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ssl.truststore.location = null
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ssl.truststore.password = null
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ssl.truststore.type = JKS
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value.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
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19/06/01 14:52:07 WARN ConsumerConfig: The configuration 'flink.partition-discovery.interval-millis' was supplied but isn't a known config.
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19/06/01 14:52:07 INFO AppInfoParser: Kafka version : 0.11.0.0
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19/06/01 14:52:07 INFO AppInfoParser: Kafka commitId : cb8625948210849f
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{"value":{"value":"12"},"metadata":{"offset":11,"topic":"mysql-exactly-Once-4","partition":0}}
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19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: start invoke...
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19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 {"value":{"value":"12"},"metadata":{"offset":11,"topic":"mysql-exactly-Once-4","partition":0}}
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19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 --{"value":{"value":"12"},"metadata":{"offset":11,"topic":"mysql-exactly-Once-4","partition":0}}
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19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: objectNode-value:{"value":"12"}
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19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: 要插入的数据:12--2019-06-01 14:52:07.616
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19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: start invoke...
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 {"value":{"value":"13"},"metadata":{"offset":12,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 --{"value":{"value":"13"},"metadata":{"offset":12,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: objectNode-value:{"value":"13"}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: 要插入的数据:13--2019-06-01 14:52:07.617
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: start invoke...
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 {"value":{"value":"14"},"metadata":{"offset":13,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 --{"value":{"value":"14"},"metadata":{"offset":13,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: objectNode-value:{"value":"14"}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: 要插入的数据:14--2019-06-01 14:52:07.618
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: start invoke...
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 {"value":{"value":"15"},"metadata":{"offset":14,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: ===>date:2019-06-01 14:52:07 --{"value":{"value":"15"},"metadata":{"offset":14,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: objectNode-value:{"value":"15"}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: 要插入的数据:15--2019-06-01 14:52:07.619
-
{"value":{"value":"13"},"metadata":{"offset":12,"topic":"mysql-exactly-Once-4","partition":0}}
-
{"value":{"value":"14"},"metadata":{"offset":13,"topic":"mysql-exactly-Once-4","partition":0}}
-
{"value":{"value":"15"},"metadata":{"offset":14,"topic":"mysql-exactly-Once-4","partition":0}}
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: start abort rollback...
-
19/06/01 14:52:07 INFO Task: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (c284f48cd0b113da4f68fd835e643903) switched from RUNNING to FAILED.
-
java.lang.ArithmeticException: / by zero
-
at com.zzy.bigdata.flink.streaming.MySqlTwoPhaseCommitSink.invoke(MySqlTwoPhaseCommitSink.java:68)
-
at com.zzy.bigdata.flink.streaming.MySqlTwoPhaseCommitSink.invoke(MySqlTwoPhaseCommitSink.java:30)
-
at org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.invoke(TwoPhaseCommitSinkFunction.java:230)
-
at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:56)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:579)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:554)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:534)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:649)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:602)
-
at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718)
-
at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696)
-
at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104)
-
at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111)
-
at org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398)
-
at org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:89)
-
at org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:154)
-
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.runWithPartitionDiscovery(FlinkKafkaConsumerBase.java:675)
-
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:667)
-
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:94)
-
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:58)
-
at org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:99)
-
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:300)
-
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:704)
-
at java.lang.Thread.run(Thread.java:748)
-
19/06/01 14:52:07 INFO Task: Freeing task resources for Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (c284f48cd0b113da4f68fd835e643903).
-
19/06/01 14:52:07 INFO Task: Ensuring all FileSystem streams are closed for task Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (c284f48cd0b113da4f68fd835e643903) [FAILED]
-
19/06/01 14:52:07 INFO TaskExecutor: Un-registering task and sending final execution state FAILED to JobManager for task Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) c284f48cd0b113da4f68fd835e643903.
-
19/06/01 14:52:07 INFO ExecutionGraph: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (c284f48cd0b113da4f68fd835e643903) switched from RUNNING to FAILED.
-
java.lang.ArithmeticException: / by zero
-
at com.zzy.bigdata.flink.streaming.MySqlTwoPhaseCommitSink.invoke(MySqlTwoPhaseCommitSink.java:68)
-
at com.zzy.bigdata.flink.streaming.MySqlTwoPhaseCommitSink.invoke(MySqlTwoPhaseCommitSink.java:30)
-
at org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.invoke(TwoPhaseCommitSinkFunction.java:230)
-
at org.apache.flink.streaming.api.operators.StreamSink.processElement(StreamSink.java:56)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.pushToOperator(OperatorChain.java:579)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:554)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$CopyingChainingOutput.collect(OperatorChain.java:534)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:649)
-
at org.apache.flink.streaming.runtime.tasks.OperatorChain$BroadcastingOutputCollector.collect(OperatorChain.java:602)
-
at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:718)
-
at org.apache.flink.streaming.api.operators.AbstractStreamOperator$CountingOutput.collect(AbstractStreamOperator.java:696)
-
at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collect(StreamSourceContexts.java:104)
-
at org.apache.flink.streaming.api.operators.StreamSourceContexts$NonTimestampContext.collectWithTimestamp(StreamSourceContexts.java:111)
-
at org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher.emitRecordWithTimestamp(AbstractFetcher.java:398)
-
at org.apache.flink.streaming.connectors.kafka.internal.Kafka010Fetcher.emitRecord(Kafka010Fetcher.java:89)
-
at org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:154)
-
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.runWithPartitionDiscovery(FlinkKafkaConsumerBase.java:675)
-
at org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:667)
-
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:94)
-
at org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:58)
-
at org.apache.flink.streaming.runtime.tasks.SourceStreamTask.run(SourceStreamTask.java:99)
-
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:300)
-
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:704)
-
at java.lang.Thread.run(Thread.java:748)
-
19/06/01 14:52:07 INFO ExecutionGraph: Job com.zzy.bigdata.flink.streaming.StreamDemoKafka2Mysql (a7188181ec45ab397d21bb1f928c7b89) switched from state RUNNING to FAILING.
-
...
-
19/06/01 14:52:07 INFO TaskExecutor: Discarding the results produced by task execution c284f48cd0b113da4f68fd835e643903.
-
19/06/01 14:52:07 INFO ExecutionGraph: Try to restart or fail the job com.zzy.bigdata.flink.streaming.StreamDemoKafka2Mysql (a7188181ec45ab397d21bb1f928c7b89) if no longer possible.
-
19/06/01 14:52:07 INFO ExecutionGraph: Job com.zzy.bigdata.flink.streaming.StreamDemoKafka2Mysql (a7188181ec45ab397d21bb1f928c7b89) switched from state FAILING to RESTARTING.
-
19/06/01 14:52:07 INFO ExecutionGraph: Restarting the job com.zzy.bigdata.flink.streaming.StreamDemoKafka2Mysql (a7188181ec45ab397d21bb1f928c7b89).
-
19/06/01 14:52:07 INFO ExecutionGraph: Job com.zzy.bigdata.flink.streaming.StreamDemoKafka2Mysql (a7188181ec45ab397d21bb1f928c7b89) switched from state RESTARTING to CREATED.
-
19/06/01 14:52:07 INFO CheckpointCoordinator: Restoring job a7188181ec45ab397d21bb1f928c7b89 from latest valid checkpoint: Checkpoint 3 @ 1559371921807 for a7188181ec45ab397d21bb1f928c7b89.
-
19/06/01 14:52:07 INFO CheckpointCoordinator: No master state to restore
-
19/06/01 14:52:07 INFO ExecutionGraph: Job com.zzy.bigdata.flink.streaming.StreamDemoKafka2Mysql (a7188181ec45ab397d21bb1f928c7b89) switched from state CREATED to RUNNING.
-
19/06/01 14:52:07 INFO ExecutionGraph: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) switched from CREATED to SCHEDULED.
-
19/06/01 14:52:07 INFO ExecutionGraph: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) switched from SCHEDULED to DEPLOYING.
-
19/06/01 14:52:07 INFO ExecutionGraph: Deploying Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (attempt #33) to localhost
-
19/06/01 14:52:07 INFO TaskExecutor: Received task Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1).
-
19/06/01 14:52:07 INFO Task: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) switched from CREATED to DEPLOYING.
-
19/06/01 14:52:07 INFO Task: Creating FileSystem stream leak safety net for task Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) [DEPLOYING]
-
19/06/01 14:52:07 INFO Task: Loading JAR files for task Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) [DEPLOYING].
-
19/06/01 14:52:07 INFO Task: Registering task at network: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) [DEPLOYING].
-
19/06/01 14:52:07 INFO Task: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) switched from DEPLOYING to RUNNING.
-
19/06/01 14:52:07 INFO ExecutionGraph: Source: Custom Source -> (Sink: Print to Std. Out, Sink: MySqlTwoPhaseCommitSink) (1/1) (b406c6534c19b26ab0ae3b6056f926cc) switched from DEPLOYING to RUNNING.
-
19/06/01 14:52:07 INFO StreamTask: No state backend has been configured, using default (Memory / JobManager) MemoryStateBackend (data in heap memory / checkpoints to JobManager) (checkpoints: 'null', savepoints: 'null', asynchronous: TRUE, maxStateSize: 5242880)
-
19/06/01 14:52:07 INFO TwoPhaseCommitSinkFunction: MySqlTwoPhaseCommitSink 0/1 - restoring state
-
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: start commit...
-
19/06/01 14:52:07 ERROR DBConnectUtil: 提交事物失败,Connection:com.mysql.jdbc.JDBC4Connection@69ae3a8c
-
java.sql.SQLException: Unexpected exception encountered during query.
-
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:965)
-
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:898)
-
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:887)
-
at com.mysql.jdbc.SQLError.createSQLException(SQLError.java:861)
-
at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2523)
-
at com.mysql.jdbc.ConnectionImpl.commit(ConnectionImpl.java:1547)
-
at com.zzy.bigdata.flink.streaming.DBConnectUtil.commit(DBConnectUtil.java:56)
-
at com.zzy.bigdata.flink.streaming.MySqlTwoPhaseCommitSink.commit(MySqlTwoPhaseCommitSink.java:103)
-
at com.zzy.bigdata.flink.streaming.MySqlTwoPhaseCommitSink.commit(MySqlTwoPhaseCommitSink.java:30)
-
at org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.recoverAndCommit(TwoPhaseCommitSinkFunction.java:200)
-
at org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.recoverAndCommitInternal(TwoPhaseCommitSinkFunction.java:395)
-
at org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.initializeState(TwoPhaseCommitSinkFunction.java:353)
-
at org.apache.flink.streaming.util.functions.StreamingFunctionUtils.tryRestoreFunction(StreamingFunctionUtils.java:178)
-
at org.apache.flink.streaming.util.functions.StreamingFunctionUtils.restoreFunctionState(StreamingFunctionUtils.java:160)
-
at org.apache.flink.streaming.api.operators.AbstractUdfStreamOperator.initializeState(AbstractUdfStreamOperator.java:96)
-
at org.apache.flink.streaming.api.operators.AbstractStreamOperator.initializeState(AbstractStreamOperator.java:278)
-
at org.apache.flink.streaming.runtime.tasks.StreamTask.initializeState(StreamTask.java:738)
-
at org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:289)
-
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:704)
-
at java.lang.Thread.run(Thread.java:748)
通过日志发现成功入库的日志是1-11,消费到数字15的时候,提交失败,日志最后一行发生了回滚,关闭了连接,然后进行conmit的时候也失败了,消费的数据12-15不会插入到数据库中,此时checkpoint也不会做了,checkpoint保存的还是上一次成功消费后的offset数据。
数据库表:mysqlExactlyOnce_test
-
CREATE TABLE `mysqlExactlyOnce_test` (
-
`id` bigint(20) NOT NULL AUTO_INCREMENT,
-
`value` varchar(255) DEFAULT NULL,
-
`insert_time` datetime DEFAULT NULL,
-
PRIMARY KEY (`id`)
-
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
表中的数据