Flink 实战 kafka 写数据到 hbase

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GreenLightt
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    需求

    此次 job 任务的目的是从 kafka 指定 topic 读取消息，并写入到 hbase 中；

    消息体包含 project（消息所属项目）、table（要写入的 hbase 表名）和 data （json 字符串）。

    执行思路：

    1. 使用流式引擎，配置 kafka source；
    2. 过滤不符合格式要求的数据
    3. 调整触发机制：指定时间窗口，同时若在窗口内达成指定次数，也会触发
    4. 接入 hbase sink 批量写数据

    环境准备

    version: '3'
services:
  mysql:
    image: "docker.io/mysql:5.7"
    environment:
      MYSQL_ROOT_PASSWORD: "123456"
    ports:
      - "3306:3306"
  zookeeper:
    image: harbor.oneitfarm.com/cidata/zookeeper:3.4.14
    environment:
      ZOO_MY_ID: 1
      ZOO_SERVERS: server.1=0.0.0.0:2888:3888
      ENABLE_SASL: "true"
      SUPER_PASSWORD: admin
      USER_KAFKA_PASSWORD: 123456
    ports:
      - "2182:2181"
  kafka_broker:
    image: "harbor.oneitfarm.com/cidata/kafka:2.4.0"
    environment:
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      ZOOKEEPER_SASL_ENABLE: "true"
      ZOOKEEPER_SASL_USER_KAFKA_PASSWORD: 123456
      KAFKA_SASL_ENABLE: "true"
      KAFKA_ADMIN_PASSWORD: 123456
      KAFKA_BROKER_ID: 1
      KAFKA_HEAP_OPTS: "-Xmx512M -Xms256M"
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: INSIDE:SASL_PLAINTEXT,OUTSIDE:SASL_PLAINTEXT
      KAFKA_ADVERTISED_LISTENERS: INSIDE://:9094,OUTSIDE://${HOST_IP}:19092
      KAFKA_LISTENERS: INSIDE://:9094,OUTSIDE://:9092
      KAFKA_INTER_BROKER_LISTENER_NAME: INSIDE
    ports:
      - "19092:9092"

    同目录下要有 .env 文件

    # 修改成主机IP
HOST_IP=192.168.50.187

    代码

    pom.xml

        <properties>
        <mainClass>xxx.flinkjob.kafka.Application</mainClass>
        <flink-version>1.10.0</flink-version>
        <hbase-version>1.3.1</hbase-version>
        <maven.compiler.source>1.8</maven.compiler.source>
        <maven.compiler.target>1.8</maven.compiler.target>
        <maven.compiler.compilerVersion>1.8</maven.compiler.compilerVersion>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.25</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.25</version>
        </dependency>

        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>2.3.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink-version}</version>
<!--            <scope>provided</scope>-->
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.11</artifactId>
            <version>${flink-version}</version>
<!--            <scope>provided</scope>-->
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-jdbc_2.11</artifactId>
            <version>1.7.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.11</artifactId>
            <version>${flink-version}</version>
        </dependency>
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.62</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>${hbase-version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-common</artifactId>
            <version>${hbase-version}</version>
        </dependency>
        <dependency>
            <groupId>commons-cli</groupId>
            <artifactId>commons-cli</artifactId>
            <version>1.4</version>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>6.0.6</version>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <artifactId>maven-assembly-plugin</artifactId>
                <configuration>
                    <archive>
                        <manifest>
                            <mainClass>${mainClass}</mainClass>
                        </manifest>
                    </archive>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>

                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>assembly</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>

    model

    package xxx.flinkjob.kafka.model;

public class HttpDataModel {
    private String project;
    private String table;
    private String data;

    public HttpDataModel() {}

    public HttpDataModel(String project, String table, String data) {
        this.project = project;
        this.table   = table;
        this.data    = data;
    }

    public String getProject() {
        return project;
    }

    public String getTable() {
        return table;
    }

    public String getData() {
        return data;
    }

    public String getFullTable() {
        return project + ":" + table;
    }

    public void setProject(String project) {
        this.project = project;
    }

    public void setTable(String table) {
        this.table = table;
    }

    public void setData(String data) {
        this.data = data;
    }

    @Override
    public String toString() {
        return "HttpDataModel{" +
                "project='" + project + '\'' +
                ", table='" + table + '\'' +
                ", data='" + data + '\'' +
                '}';
    }
}

    sink

    package xxx.flinkjob.kafka.sink;

import com.alibaba.fastjson.JSONObject;
import xxx.flinkjob.kafka.model.HttpDataModel;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction;
import org.apache.hadoop.hbase.*;
import org.apache.hadoop.hbase.client.Admin;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.log4j.Logger;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class HbaseSink extends RichSinkFunction<List<HttpDataModel>> implements Serializable {
    private Logger log;

    private String hbase_zookeeper_host;
    private String hbase_zookeeper_port;

    private Connection connection;
    private Admin admin;

    public HbaseSink(String hbase_zookeeper_host, String hbase_zookeeper_port) {
        this.hbase_zookeeper_host = hbase_zookeeper_host;
        this.hbase_zookeeper_port = hbase_zookeeper_port;
    }

    @Override
    public void open(Configuration parameters) throws Exception {
        super.open(parameters);
        log = Logger.getLogger(HbaseSink.class);

        org.apache.hadoop.conf.Configuration configuration = HBaseConfiguration.create();
        configuration.set("hbase.zookeeper.property.clientPort", hbase_zookeeper_port);
        configuration.set("hbase.zookeeper.quorum", hbase_zookeeper_host);

        connection = ConnectionFactory.createConnection(configuration);
        admin = connection.getAdmin();
    }

    public void invoke(List<HttpDataModel> datas, Context context) throws Exception {
        // 按 project:table 归纳
        Map<String, List<HttpDataModel>> map = new HashMap<String, List<HttpDataModel>>();
        for (HttpDataModel data : datas) {
            if (! map.containsKey(data.getFullTable())) {
                map.put(data.getFullTable(), new ArrayList<HttpDataModel>());
            }
            map.get(data.getFullTable()).add(data);
        }
        // 遍历 map
        for(Map.Entry<String, List<HttpDataModel>> entry : map.entrySet()){
            // 如果 表不存在，即创建
            createTable(entry.getKey());
            // 写数据
            List<Put> list = new ArrayList<Put>();
            for (HttpDataModel item : entry.getValue()) {
                Put put = new Put(Bytes.toBytes(String.valueOf(System.currentTimeMillis())));

                JSONObject object = JSONObject.parseObject(item.getData());
                for (String key: object.keySet()) {
                    put.addColumn("data".getBytes(), key.getBytes(), object.getString(key).getBytes());
                }
                list.add(put);
            }
            connection.getTable(TableName.valueOf(entry.getKey())).put(list);
        }
    }

    @Override
    public void close() throws Exception {
        super.close();
    }

    /**
     * 创建 hbase 表
     */
    private void createTable(String tableName) throws Exception {
        createNamespace(tableName.split(":")[0]);
        TableName table = TableName.valueOf(tableName);
        if (! admin.tableExists(table)) {
            HTableDescriptor hTableDescriptor = new HTableDescriptor(table);
            // 固定只有 data 列簇
            hTableDescriptor.addFamily(new HColumnDescriptor("data"));
            admin.createTable(hTableDescriptor);
        }
    }

    /**
     * 创建命名空间
     */
    private void createNamespace(String namespace) throws Exception {
        try {
            admin.getNamespaceDescriptor(namespace);
        } catch (NamespaceNotFoundException e) {
            admin.createNamespace(NamespaceDescriptor.create(namespace).build());
        }
    }
}

    trigger

    package xxx.flinkjob.kafka.trigger;

import org.apache.flink.streaming.api.windowing.triggers.Trigger;
import org.apache.flink.streaming.api.windowing.triggers.TriggerResult;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;

public class CountTrigger<T> extends Trigger<T, TimeWindow> {

    // 当前的计数标志
    private static int flag = 0;

    // 最大数量
    public static int threshold = 0;

    public CountTrigger(Integer threshold) {
        this.threshold = threshold;
    }

    /**
     * 添加到窗口的每个元素都会调此方法
     */
    public TriggerResult onElement(Object element, long timestamp, TimeWindow window, TriggerContext ctx) throws Exception {
        ctx.registerEventTimeTimer(window.maxTimestamp());

        flag++;

        if(flag >= threshold){
            flag = 0;
            ctx.deleteProcessingTimeTimer(window.maxTimestamp());
            return TriggerResult.FIRE_AND_PURGE;
        }

        return TriggerResult.CONTINUE;
    }

    /**
     * 当注册的处理时间计时器触发时，将调用此方法
     */
    public TriggerResult onProcessingTime(long time, TimeWindow window, TriggerContext ctx) throws Exception {
        if(flag > 0){
            // System.out.println("到达窗口时间执行触发：" + flag);
            flag = 0;
            return TriggerResult.FIRE_AND_PURGE;
        }
        return TriggerResult.CONTINUE;
    }

    /**
     * 当注册的事件时间计时器触发时，将调用此方法
     */
    public TriggerResult onEventTime(long time, TimeWindow window, TriggerContext ctx) throws Exception {
        if (time >= window.maxTimestamp() && flag > 0) {
            // System.out.println("到达时间窗口且有数据，触发操作！");
            flag = 0;
            return TriggerResult.FIRE_AND_PURGE;
        } else if (time >= window.maxTimestamp() && flag == 0) {
            // 清除窗口但不触发
            return TriggerResult.PURGE;
        }
        return TriggerResult.CONTINUE;
    }

    /**
     * 执行任何需要清除的相应窗口
     */
    public void clear(TimeWindow window, TriggerContext ctx) throws Exception {
        ctx.deleteProcessingTimeTimer(window.maxTimestamp());
        ctx.deleteEventTimeTimer(window.maxTimestamp());
    }
}

    入口执行文件

    package xxx.flinkjob.kafka;

import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONObject;
import com.ci123.data.flinkjob.kafka.model.HttpDataModel;
import com.ci123.data.flinkjob.kafka.sink.HbaseSink;
import com.ci123.data.flinkjob.kafka.trigger.CountTrigger;
import org.apache.commons.cli.*;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.windowing.AllWindowFunction;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.Window;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.util.Collector;

import java.util.ArrayList;
import java.util.List;
import java.util.Properties;

public class Application {

    @SuppressWarnings(value={"unchecked"})
    public static void main(String[] args) throws Exception {
        // kafka 需要的参数
        String brokers = "127.0.0.1:9092";
        String username = "admin";
        String password = "123456";
        String topic = "test";
        // hbase 需要的参数
        String hbase_zookeeper_host = "hbase";
        String hbase_zookeeper_port = "2181";

        // 接收命令行参数，覆盖默认值
        Options options = new Options();
        options.addOption("kafka_brokers", true, "kafka cluster hosts, such 127.0.0.1:9092");
        options.addOption("kafka_username", true, "kafka cluster username, default: admin");
        options.addOption("kafka_user_password", true, "kafka cluster user password, default: 123456");
        options.addOption("kafka_topic", true, "kafka cluster topic, default: test");

        options.addOption("hbase_zookeeper_host", true, "hbase zookeeper host, default: hbase");
        options.addOption("hbase_zookeeper_port", true, "hbase zookeeper port, default: 2181");

        CommandLineParser parser = new DefaultParser();
        CommandLine line = parser.parse( options, args );

        if ( line.hasOption( "kafka_brokers" ) ) {
            brokers = line.getOptionValue("kafka_brokers");
        } else {
            HelpFormatter formatter = new HelpFormatter();
            formatter.printHelp( "flink write hbase job", options );
            System.exit(1);
        }

        if ( line.hasOption( "kafka_username" ) ) {
            username = line.getOptionValue("kafka_username");
        }
        if ( line.hasOption( "kafka_user_password" ) ) {
            password = line.getOptionValue("kafka_user_password");
        }
        if ( line.hasOption( "kafka_topic" ) ) {
            topic = line.getOptionValue("kafka_topic");
        }
        if ( line.hasOption( "hbase_zookeeper_host" ) ) {
            hbase_zookeeper_host = line.getOptionValue("hbase_zookeeper_host");
        }
        if ( line.hasOption( "hbase_zookeeper_port" ) ) {
            hbase_zookeeper_port = line.getOptionValue("hbase_zookeeper_port");
        }

        // 执行任务
        doExcute(brokers, username, password, topic, hbase_zookeeper_host, hbase_zookeeper_port);
    }

    /**
     * 具体任务执行
     */
    public static void doExcute(String kafka_brokers, String kafka_username, String kafka_password,
                                String topic, String hbase_zookeeper_host, String hbase_zookeeper_port) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 设置 kafka source
        env.enableCheckpointing(5000 * 100000);

        Properties props = getKafkaProperties(kafka_username, kafka_password);
        props.setProperty("bootstrap.servers", kafka_brokers);
        DataStream<String> stream = env.addSource(new FlinkKafkaConsumer(topic, new SimpleStringSchema(), props));

        // 过滤不标准格式的数据，并格式化
        DataStream<HttpDataModel> formated_stream = stream.filter(s -> {
            JSONObject obj = JSONObject.parseObject(s);
            return obj.containsKey("project") && obj.containsKey("table") && obj.containsKey("data");
        }).map(s -> { return JSON.parseObject(s, HttpDataModel.class); });

        // 在 10 秒的时间窗口内，每 100 条触发输出到 hbase
        DataStream<List<HttpDataModel>> batch_stream = formated_stream
                .timeWindowAll(Time.seconds(10))
                .trigger(new CountTrigger(100))
                .apply(new AllWindowFunction<HttpDataModel, List<HttpDataModel>, Window>() {
                    public void apply(Window window, Iterable<HttpDataModel> values, Collector<List<HttpDataModel>> out) throws Exception {
                        List<HttpDataModel> lists = new ArrayList<HttpDataModel>();
                        for (HttpDataModel value : values) {
                            lists.add(value);
                        }
                        out.collect(lists);
                    }
                });

        batch_stream.addSink(new HbaseSink(hbase_zookeeper_host, hbase_zookeeper_port));

        // 控制台输出
        //batch_stream.print();

        env.execute("integration-http");
    }

    /**
     * 获取 kafka 的默认配置
     */
    public static Properties getKafkaProperties(String username, String password) {
        Properties props = new Properties();
        props.setProperty("bootstrap.servers", "127.0.0.1:9092");
        props.setProperty("group.id", "dataworks-integration");
        props.put("enable.auto.commit", "true");
        props.put("auto.offset.reset", "earliest");
        props.put("auto.commit.interval.ms", "1000");
        props.put("session.timeout.ms", "30000");
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

        String jaasTemplate = "org.apache.kafka.common.security.scram.ScramLoginModule required username=\"%s\" password=\"%s\";";
        String jaasCfg = String.format(jaasTemplate, username, password);

        props.put("security.protocol", "SASL_PLAINTEXT");
        props.put("sasl.mechanism", "SCRAM-SHA-256");
        props.put("sasl.jaas.config", jaasCfg);
        return props;
    }
}
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