解决Flink消费Kafka信息，结果存储在Mysql的重复消费问题
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FlinkK..
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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
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<ObjectNode> kafkaConsumer011 = new FlinkKafkaConsumer011<>(topic_ExactlyOnce, new JSONKeyValueDeserializationSchema(true), props);
//加入kafka数据源
DataStreamSource<ObjectNode> 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());
}
}2.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<ObjectNode,Connection,Void> {
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);
}
}3.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();
}
}
}
}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
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<String, String>(props);//老版本producer已废弃
Producer<String, String> 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<String, String>(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
Kafka开源项目指南提供详尽教程，助开发者掌握其架构、配置和使用，实现高效数据流管理和实时处理。它高性能、可扩展，适合日志收集和实时数据处理，通过持久化保障数据安全，是企业大数据生态系统的核心。
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