Flink初试——对接Kafka

2021-01-06 15:14:11 浏览数 (1)

本篇文章我们用 Flink Kafka Connector对接Kafka,实现一个简单的报警业务。我们暂时不去谈论理论,先上手实现这个简单的需求。

flink-connector-kafka是 flink 内置的Kafka连接器,包含了从topic读取数据的Flink Kafka Consumer 和 向topic写入数据的flink kafka producer,除了基本功能外还提供了基于 checkpoint 机制提供了完美的容错能力。

本文基于flink 1.10.1 和 flink-connector-kafka-0.10_2.11版本,pom如下:

代码语言:javascript复制
<dependency>            <groupId>org.apache.flink</groupId>            <artifactId>flink-connector-kafka-0.10_2.11</artifactId>            <version>1.10.0</versio></dependency>

以企业常见的预警业务为例,本文要实现的业务逻辑很简单,当设备上报的油桶余量不足10%时,便生成一个报警,这里我们将报警写入MySQL,以供web业务端展示报警报表。

首先我们用网络数据调试器向网关模拟发送数据,网关会将数据解析后写入kafka

代码语言:javascript复制
kafka-console-consumer --bootstrap-server cdh1.macro.com:9092,cdh2.macro.com:9092,cdh3.macro.com:9092 --from-beginning --topic fill
{"addTime":1593147840000,"currentAmount":0.3,"devId":"XT365-000170","devStatus":"1","ifOffline":"1","ip":"127.0.0.1","leftTankAmount":5,"realTotalAmount":2377.39,"registerTime":1606658457000,"settingAmount":0.3,"tankCapacity":1000,"totalAmount":2017.9315}{"addTime":1593147840000,"currentAmount":0.3,"devId":"XT365-000170","devStatus":"1","ifOffline":"1","ip":"127.0.0.1","leftTankAmount":5,"realTotalAmount":2377.69,"registerTime":1606658458000,"settingAmount":0.3,"tankCapacity":1000,"totalAmount":2017.9315}^C20/11/29 23:26:55 INFO internals.ConsumerCoordinator: [Consumer clientId=consumer-console-consumer-82199-1, groupId=console-consumer-82199] Revoke previously assigned partitions fill-020/11/29 23:26:55 INFO internals.AbstractCoordinator: [Consumer clientId=consumer-console-consumer-82199-1, groupId=console-consumer-82199] Member consumer-console-consumer-82199-1-aa5fc2e6-1f06-4714-9d89-fe080a9400e2 sending LeaveGroup request to coordinator cdh2.macro.com:9092 (id: 2147483598 rack: null) due to the consumer is being closedProcessed a total of 1200 messages

可以看到我们已经向kafka生产了1200条数据了

接下来我们写一段代码来消费kafka数据,并将报警结果写入MySQL

代码语言:javascript复制
import com.alibaba.fastjson.JSONObject;import com.iiot.bean.InSufficient;import com.iiot.commCommon.Fill;import com.iiot.jdbc.MySQLSinks;import org.apache.flink.api.common.functions.MapFunction;import org.apache.flink.api.common.serialization.SimpleStringSchema;import org.apache.flink.streaming.api.datastream.DataStream;import org.apache.flink.streaming.api.datastream.DataStreamSource;import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;import org.apache.flink.streaming.api.windowing.windows.TimeWindow;import org.apache.flink.streaming.api.windowing.time.Time;import java.util.List;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010;import org.apache.flink.util.Collector;import org.apache.flink.shaded.guava18.com.google.common.collect.Lists;import org.apache.flink.streaming.api.functions.windowing.AllWindowFunction;
import java.util.Properties;
public class InSufficientOilAlarms {    public static void main(String[] args) throws Exception{        //构建流执行环境        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        //kafka        Properties prop = new Properties();        prop.put("bootstrap.servers", "cdh1.macro.com:9092,cdh2.macro.com:9092,cdh3.macro.com:9092");//        prop.put("zookeeper.connect", "localhost:2181");        prop.put("group.id", "fill6");        prop.put("key.serializer", "org.apache.kafka.common.serialization.StringDeserializer");        prop.put("value.serializer", "org.apache.kafka.common.serialization.StringDeserializer");        prop.put("auto.offset.reset", "earliest");
        DataStreamSource<String> stream = env                .addSource(new FlinkKafkaConsumer010<String>(                        "fill",                        new SimpleStringSchema(), prop)).                //单线程打印,控制台不乱序,不影响结果                setParallelism(1);
        //从kafka里读取数据,转换成Person对象        DataStream<Fill> dataStream = stream.map(value ->                JSONObject.parseObject(value, Fill.class)        );
        SingleOutputStreamOperator<InSufficient> result = dataStream.map(new MapFunction<Fill, InSufficient>() {                           @Override                           public InSufficient map(Fill fill) throws Exception {                               InSufficient inSufficient = new InSufficient();                               Float leftTankAmount = fill.getLeftTankAmount();                               Float tankCapacity = fill.getTankCapacity();                               String devCode = fill.getDevId();                               long timeBegin = fill.getAddTime().getTime();                               System.out.println("devCode:-------------------------------------------------"   devCode);                               String alarmType = "";                               if ((leftTankAmount / tankCapacity) < 0.1 ) {                                   alarmType = "inSufficientOil";                                   inSufficient.setDev_code(devCode);                                   inSufficient.setCreateTime(System.currentTimeMillis());                                   inSufficient.setTimeBegin(timeBegin);                                   inSufficient.setAlarmType(alarmType);                                   inSufficient.setRemainAmount(leftTankAmount);                               }                               return inSufficient;                           }                       }
        );

        //收集5秒钟的总数        result.timeWindowAll(Time.seconds(5L)).                apply(new AllWindowFunction<InSufficient, List<InSufficient>, TimeWindow>() {
                    @Override                    public void apply(TimeWindow timeWindow, Iterable<InSufficient> iterable, Collector<List<InSufficient>> out) throws Exception {                        List<InSufficient> inSufficients = Lists.newArrayList(iterable);
                        if(inSufficients.size() > 0) {                            System.out.println("5秒的总共收到的条数:"   inSufficients.size());                            out.collect(inSufficients);                        }
                    }                })                //sink 到数据库                .addSink(new MySQLSinks());        //打印到控制台        //.print();
        env.execute("kafka 消费任务开始");    }}

将项目打包,传到集群中,用Flink on YARN的方式运行作业

代码语言:javascript复制
/*
* 提示:该行代码过长,系统自动注释不进行高亮。一键复制会移除系统注释 
* [root@cdh3 bin]# flink run -m yarn-cluster -c com.iiot.alarm.InSufficientOilAlarms /data0/flinkdemo/stream-1.0-SNAPSHOT-jar-with-dependencies.jar 20/11/30 01:40:15 INFO cli.CliFrontend: --------------------------------------------------------------------------------20/11/30 01:40:15 INFO cli.CliFrontend:  Starting Command Line Client (Version: 1.10.0-csa1.2.0.0, Rev:04dddd1, Date:29.05.2020 @ 14:54:45 UTC)20/11/30 01:40:15 INFO cli.CliFrontend:  OS current user: root20/11/30 01:40:16 INFO cli.CliFrontend:  Current Hadoop/Kerberos user: hdfs20/11/30 01:40:16 INFO cli.CliFrontend:  JVM: Java HotSpot(TM) 64-Bit Server VM - Oracle Corporation - 1.8/25.171-b1120/11/30 01:40:16 INFO cli.CliFrontend:  Maximum heap size: 3531 MiBytes20/11/30 01:40:16 INFO cli.CliFrontend:  JAVA_HOME: /usr/java/latest20/11/30 01:40:16 INFO cli.CliFrontend:  Hadoop version: 2.7.520/11/30 01:40:16 INFO cli.CliFrontend:  JVM Options:20/11/30 01:40:16 INFO cli.CliFrontend:     -Datlas.conf=/etc/atlas/conf/20/11/30 01:40:16 INFO cli.CliFrontend:     -Dlog.file=/var/log/flink/flink-root-client-cdh3.macro.com.log20/11/30 01:40:16 INFO cli.CliFrontend:     -Dlog4j.configuration=file:/etc/flink/conf/log4j-cli.properties20/11/30 01:40:16 INFO cli.CliFrontend:     -Dlogback.configurationFile=file:/etc/flink/conf/logback.xml20/11/30 01:40:16 INFO cli.CliFrontend:  Program Arguments:20/11/30 01:40:16 INFO cli.CliFrontend:     run20/11/30 01:40:16 INFO cli.CliFrontend:     -m20/11/30 01:40:16 INFO cli.CliFrontend:     yarn-cluster20/11/30 01:40:16 INFO cli.CliFrontend:     -c20/11/30 01:40:16 INFO cli.CliFrontend:     com.iiot.alarm.InSufficientOilAlarms20/11/30 01:40:16 INFO cli.CliFrontend:     /data0/flinkdemo/stream-1.0-SNAPSHOT-jar-with-dependencies.jar20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:java.io.tmpdir=/tmp20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:java.compiler=<NA>20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:os.name=Linux20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:os.arch=amd6420/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:os.version=3.10.0-327.el7.x86_6420/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:user.name=root20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:user.home=/root20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:user.dir=/opt/cloudera/parcels/FLINK-1.10.0-csa1.2.0.0-cdh7.1.1.0-565-3454809/bin20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:os.memory.free=134MB20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:os.memory.max=3531MB20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Client environment:os.memory.total=359MB20/11/30 01:40:51 INFO utils.Compatibility: Using emulated InjectSessionExpiration20/11/30 01:40:51 INFO imps.CuratorFrameworkImpl: Starting20/11/30 01:40:51 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=cdh1.macro.com:2181,cdh2.macro.com:2181,cdh3.macro.com:2181 sessionTimeout=60000 watcher=org.apache.flink.shaded.curator.org.apache.curator.ConnectionState@1460c81d20/11/30 01:40:51 INFO common.X509Util: Setting -D jdk.tls.rejectClientInitiatedRenegotiation=true to disable client-initiated TLS renegotiation20/11/30 01:40:51 INFO zookeeper.ClientCnxnSocket: jute.maxbuffer value is 4194304 Bytes20/11/30 01:40:51 INFO zookeeper.ClientCnxn: zookeeper.request.timeout value is 0. feature enabled=20/11/30 01:40:51 WARN zookeeper.ClientCnxn: SASL configuration failed: javax.security.auth.login.LoginException: No JAAS configuration section named 'Client' was found in specified JAAS configuration file: '/tmp/jaas-8202592158525653501.conf'. Will continue connection to Zookeeper server without SASL authentication, if Zookeeper server allows it.20/11/30 01:40:51 INFO zookeeper.ClientCnxn: Opening socket connection to server cdh1.macro.com/192.168.0.171:218120/11/30 01:40:51 INFO zookeeper.ClientCnxn: Socket connection established, initiating session, client: /192.168.0.208:38183, server: cdh1.macro.com/192.168.0.171:218120/11/30 01:40:51 ERROR curator.ConnectionState: Authentication failed20/11/30 01:40:51 INFO imps.CuratorFrameworkImpl: Default schema20/11/30 01:40:51 INFO zookeeper.ClientCnxn: Session establishment complete on server cdh1.macro.com/192.168.0.171:2181, sessionid = 0x3008be9995512b4, negotiated timeout = 6000020/11/30 01:40:51 INFO state.ConnectionStateManager: State change: CONNECTED20/11/30 01:40:51 INFO imps.EnsembleTracker: New config event received: {server.1=cdh2.macro.com:3181:4181:participant, version=0, server.3=cdh1.macro.com:3181:4181:participant, server.2=cdh3.macro.com:3181:4181:participant}20/11/30 01:40:51 ERROR imps.EnsembleTracker: Invalid config event received: {server.1=cdh2.macro.com:3181:4181:participant, version=0, server.3=cdh1.macro.com:3181:4181:participant, server.2=cdh3.macro.com:3181:4181:participant}20/11/30 01:40:51 INFO imps.EnsembleTracker: New config event received: {server.1=cdh2.macro.com:3181:4181:participant, version=0, server.3=cdh1.macro.com:3181:4181:participant, server.2=cdh3.macro.com:3181:4181:participant}20/11/30 01:40:51 ERROR imps.EnsembleTracker: Invalid config event received: {server.1=cdh2.macro.com:3181:4181:participant, version=0, server.3=cdh1.macro.com:3181:4181:participant, server.2=cdh3.macro.com:3181:4181:participant}20/11/30 01:40:52 INFO leaderretrieval.ZooKeeperLeaderRetrievalService: Starting ZooKeeperLeaderRetrievalService /leader/rest_server_lock.
*/

可以在YARN作业中看到Flink的做作业一直在运行。

flink dashboard也可以看到作业一直在运行:

进入YARN reourcemanager里面查看作业运行日志:

可以看到MySQL已经插入数据了。

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