Flink实现Kafka到Mysql的Exactly-Once

Flink实现Kafka到Mysql的Exactly-Once


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

  1. StreamDemoKafka2Mysql.java
import org.apache.flink.runtime.state.filesystem.FsStateBackend;
import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode;
import org.apache.flink.streaming.api.CheckpointingMode;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase;
import org.apache.flink.streaming.util.serialization.JSONKeyValueDeserializationSchema;
import org.apache.kafka.clients.consumer.ConsumerConfig;

import java.util.Properties;

/**
 * Created with IntelliJ IDEA.
 * User: zzy
 * Date: 2019/5/28
 * Time: 8:40 PM
 * To change this template use File | Settings | File Templates.
 *
 * 消费kafka消息,sink(自定义)到mysql中,保证kafka to mysql 的Exactly-Once
 */

@SuppressWarnings("all")
public class StreamDemoKafka2Mysql {
    private static final String topic_ExactlyOnce = "mysql-exactly-Once-4";

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        //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
        env.setParallelism(1);
        //checkpoint的设置
        //每隔10s进行启动一个检查点【设置checkpoint的周期】
        env.enableCheckpointing(10000);
        //设置模式为:exactly_one,仅一次语义
        env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);
        //确保检查点之间有1s的时间间隔【checkpoint最小间隔】
        env.getCheckpointConfig().setMinPauseBetweenCheckpoints(1000);
        //检查点必须在10s之内完成,或者被丢弃【checkpoint超时时间】
        env.getCheckpointConfig().setCheckpointTimeout(10000);
        //同一时间只允许进行一次检查点
        env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);
        //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
        //env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
        //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
//        env.setStateBackend(new FsStateBackend("file:///Users/temp/cp/"));

        //设置kafka消费参数
        Properties props = new Properties();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "zzy:9092");
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "flink-consumer-group2");
        //kafka分区自动发现周期
        props.put(FlinkKafkaConsumerBase.KEY_PARTITION_DISCOVERY_INTERVAL_MILLIS, "3000");

        /*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*/
        FlinkKafkaConsumer011 kafkaConsumer011 = new FlinkKafkaConsumer011<>(topic_ExactlyOnce, new JSONKeyValueDeserializationSchema(true), props);

        //加入kafka数据源
        DataStreamSource streamSource = env.addSource(kafkaConsumer011);
//        System.out.println("streamSource:" + streamSource.print());
        streamSource.print();
        //数据传输到下游
        streamSource.addSink(new MySqlTwoPhaseCommitSink()).name("MySqlTwoPhaseCommitSink");
        //触发执行
        env.execute(StreamDemoKafka2Mysql.class.getName());
    }
}

  1. MySqlTwoPhaseCommitSink.java
import org.apache.flink.api.common.ExecutionConfig;
import org.apache.flink.api.common.typeutils.TypeSerializer;
import org.apache.flink.api.common.typeutils.base.VoidSerializer;
import org.apache.flink.api.java.typeutils.runtime.kryo.KryoSerializer;
import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode;
import org.apache.flink.streaming.api.functions.sink.SinkFunction;
import org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.sql.Connection;
import java.sql.PreparedStatement;
import java.sql.Timestamp;
import java.text.SimpleDateFormat;
import java.util.Date;

/**
 * Created with IntelliJ IDEA.
 * User: zzy
 * Date: 2019/5/28
 * Time: 8:47 PM
 * To change this template use File | Settings | File Templates.
 *
 * 自定义kafka to mysql,继承TwoPhaseCommitSinkFunction,实现两阶段提交
 */
public class MySqlTwoPhaseCommitSink extends TwoPhaseCommitSinkFunction {

    private static final Logger log = LoggerFactory.getLogger(MySqlTwoPhaseCommitSink.class);

    public MySqlTwoPhaseCommitSink(){
        super(new KryoSerializer<>(Connection.class,new ExecutionConfig()), VoidSerializer.INSTANCE);
    }

    /**
     * 执行数据库入库操作  task初始化的时候调用
     * @param connection
     * @param objectNode
     * @param context
     * @throws Exception
     */
    @Override
    protected void invoke(Connection connection, ObjectNode objectNode, Context context) throws Exception {
        log.info("start invoke...");
        String date = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date());
        log.info("===>date:" + date + " " + objectNode);
        log.info("===>date:{} --{}",date,objectNode);
        String value = objectNode.get("value").toString();
        log.info("objectNode-value:" + value);
        JSONObject valueJson = JSONObject.parseObject(value);
        String value_str = (String) valueJson.get("value");
        String sql = "insert into `mysqlExactlyOnce_test` (`value`,`insert_time`) values (?,?)";
        PreparedStatement ps = connection.prepareStatement(sql);
        ps.setString(1,value_str);
        Timestamp value_time = new Timestamp(System.currentTimeMillis());
        ps.setTimestamp(2,value_time);
        log.info("要插入的数据:{}--{}",value_str,value_time);
        //执行insert语句
        ps.execute();
        //手动制造异常
        if(Integer.parseInt(value_str) == 15) {
            System.out.println(1 / 0);
        }
    }

    /**
     * 获取连接,开启手动提交事物(getConnection方法中)
     * @return
     * @throws Exception
     */
    @Override
    protected Connection beginTransaction() throws Exception {
        log.info("start beginTransaction.......");
        String url = "jdbc:mysql://localhost:3306/test?useUnicode=true&characterEncoding=UTF-8&zeroDateTimeBehavior=convertToNull&useSSL=false&autoReconnect=true";
        Connection connection = DBConnectUtil.getConnection(url, "root", "123456");
        return connection;
    }

    /**
     *预提交,这里预提交的逻辑在invoke方法中
     * @param connection
     * @throws Exception
     */
    @Override
    protected void preCommit(Connection connection) throws Exception {
        log.info("start preCommit...");
    }

    /**
     * 如果invoke方法执行正常,则提交事务
     * @param connection
     */
    @Override
    protected void commit(Connection connection) {
        log.info("start commit...");
        DBConnectUtil.commit(connection);
    }

    /**
     * 如果invoke执行异常则回滚事物,下一次的checkpoint操作也不会执行
     * @param connection
     */
    @Override
    protected void abort(Connection connection) {
        log.info("start abort rollback...");
        DBConnectUtil.rollback(connection);
    }
}

  1. DBConnectUtil.java
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.sql.DriverManager;
import java.sql.SQLException;
import java.sql.Connection;

/**
 * Created with IntelliJ IDEA.
 * User: zzy
 * Date: 2019/5/28
 * Time: 8:58 PM
 * To change this template use File | Settings | File Templates.
 */
public class DBConnectUtil {

    private static final Logger log = LoggerFactory.getLogger(DBConnectUtil.class);

    /**
     * 获取连接
     *
     * @param url
     * @param user
     * @param password
     * @return
     * @throws SQLException
     */
    public static Connection getConnection(String url, String user, String password) throws SQLException {
        Connection conn = null;
        try {
            Class.forName("com.mysql.jdbc.Driver");
        } catch (ClassNotFoundException e) {
            log.error("获取mysql.jdbc.Driver失败");
            e.printStackTrace();
        }
        try {
            conn = DriverManager.getConnection(url, user, password);
            log.info("获取连接:{} 成功...",conn);
        }catch (Exception e){
            log.error("获取连接失败,url:" + url + ",user:" + user);
        }

        //设置手动提交
        conn.setAutoCommit(false);
        return conn;
    }

    /**
     * 提交事物
     */
    public static void commit(Connection conn) {
        if (conn != null) {
            try {
                conn.commit();
            } catch (SQLException e) {
                log.error("提交事物失败,Connection:" + conn);
                e.printStackTrace();
            } finally {
                close(conn);
            }
        }
    }

    /**
     * 事物回滚
     *
     * @param conn
     */
    public static void rollback(Connection conn) {
        if (conn != null) {
            try {
                conn.rollback();
            } catch (SQLException e) {
                log.error("事物回滚失败,Connection:" + conn);
                e.printStackTrace();
            } finally {
                close(conn);
            }
        }
    }

    /**
     * 关闭连接
     *
     * @param conn
     */
    public static void close(Connection conn) {
        if (conn != null) {
            try {
                conn.close();
            } catch (SQLException e) {
                log.error("关闭连接失败,Connection:" + conn);
                e.printStackTrace();
            }
        }
    }
}
  1. 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
public class KafkaUtils {
//    private static final String broker_list = "localhost:9092";
    private static final String broker_list = "zzy:9092";
    //flink 读取kafka写入mysql exactly-once 的topic
    private static final String topic_ExactlyOnce = "mysql-exactly-Once-4";

    public static void writeToKafka2() throws InterruptedException {
        Properties props = new Properties();
        props.put("bootstrap.servers", broker_list);
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
//        KafkaProducer producer = new KafkaProducer(props);//老版本producer已废弃
        Producer producer = new org.apache.kafka.clients.producer.KafkaProducer<>(props);

        try {
            for (int i = 1; i <= 20; i++) {
                MysqlExactlyOncePOJO mysqlExactlyOnce = new MysqlExactlyOncePOJO(String.valueOf(i));
                ProducerRecord record = new ProducerRecord(topic_ExactlyOnce, null, null, JSON.toJSONString(mysqlExactlyOnce));
                producer.send(record);
                System.out.println("发送数据: " + JSON.toJSONString(mysqlExactlyOnce));
                Thread.sleep(1000);
            }
        }catch (Exception e){

        }

        producer.flush();
    }

    public static void main(String[] args) throws InterruptedException {
        writeToKafka2();
    }
}


@Data
@NoArgsConstructor
@AllArgsConstructor
public class MysqlExactlyOncePOJO {
    private String value;
}

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:

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.
19/06/01 14:52:07 INFO FlinkKafkaConsumerBase: Setting restore state in the FlinkKafkaConsumer: {KafkaTopicPartition{topic='mysql-exactly-Once-4', partition=0}=10}
19/06/01 14:52:07 INFO ConsumerConfig: ConsumerConfig values: 
    auto.commit.interval.ms = 5000
    auto.offset.reset = latest
    bootstrap.servers = [zzy:9092]
    check.crcs = true
    client.id = 
    connections.max.idle.ms = 540000
    enable.auto.commit = true
    exclude.internal.topics = true
    fetch.max.bytes = 52428800
    fetch.max.wait.ms = 500
    fetch.min.bytes = 1
    group.id = flink-consumer-group2
    heartbeat.interval.ms = 3000
    interceptor.classes = null
    internal.leave.group.on.close = true
    isolation.level = read_uncommitted
    key.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
    max.partition.fetch.bytes = 1048576
    max.poll.interval.ms = 300000
    max.poll.records = 500
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
    receive.buffer.bytes = 65536
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 305000
    retry.backoff.ms = 100
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.mechanism = GSSAPI
    security.protocol = PLAINTEXT
    send.buffer.bytes = 131072
    session.timeout.ms = 10000
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = null
    ssl.key.password = null
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = null
    ssl.keystore.password = null
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = null
    ssl.truststore.password = null
    ssl.truststore.type = JKS
    value.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer

19/06/01 14:52:07 WARN ConsumerConfig: The configuration 'flink.partition-discovery.interval-millis' was supplied but isn't a known config.
19/06/01 14:52:07 INFO AppInfoParser: Kafka version : 0.11.0.0
19/06/01 14:52:07 INFO AppInfoParser: Kafka commitId : cb8625948210849f
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}
19/06/01 14:52:07 INFO ConsumerConfig: ConsumerConfig values: 
    auto.commit.interval.ms = 5000
    auto.offset.reset = latest
    bootstrap.servers = [zzy:9092]
    check.crcs = true
    client.id = 
    connections.max.idle.ms = 540000
    enable.auto.commit = false
    exclude.internal.topics = true
    fetch.max.bytes = 52428800
    fetch.max.wait.ms = 500
    fetch.min.bytes = 1
    group.id = flink-consumer-group2
    heartbeat.interval.ms = 3000
    interceptor.classes = null
    internal.leave.group.on.close = true
    isolation.level = read_uncommitted
    key.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer
    max.partition.fetch.bytes = 1048576
    max.poll.interval.ms = 300000
    max.poll.records = 500
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
    receive.buffer.bytes = 65536
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 305000
    retry.backoff.ms = 100
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.mechanism = GSSAPI
    security.protocol = PLAINTEXT
    send.buffer.bytes = 131072
    session.timeout.ms = 10000
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = null
    ssl.key.password = null
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = null
    ssl.keystore.password = null
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = null
    ssl.truststore.password = null
    ssl.truststore.type = JKS
    value.deserializer = class org.apache.kafka.common.serialization.ByteArrayDeserializer

19/06/01 14:52:07 WARN ConsumerConfig: The configuration 'flink.partition-discovery.interval-millis' was supplied but isn't a known config.
19/06/01 14:52:07 INFO AppInfoParser: Kafka version : 0.11.0.0
19/06/01 14:52:07 INFO AppInfoParser: Kafka commitId : cb8625948210849f
{"value":{"value":"12"},"metadata":{"offset":11,"topic":"mysql-exactly-Once-4","partition":0}}
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":"12"},"metadata":{"offset":11,"topic":"mysql-exactly-Once-4","partition":0}}
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}}
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: objectNode-value:{"value":"12"}
19/06/01 14:52:07 INFO MySqlTwoPhaseCommitSink: 要插入的数据:12--2019-06-01 14:52:07.616
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


Flink实现Kafka到Mysql的Exactly-Once_第1张图片

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