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使用Flink Jar写入数据到OBS开发指南

概述

DLI提供了使用自定义Jar运行Flink作业并将数据写入到OBS的能力。本章节JAVA样例代码演示将kafka数据处理后写入到OBS，具体参数配置请根据实际环境修改。

环境准备

已安装和配置IntelliJ IDEA等开发工具以及安装JDK和Maven。

  • Maven工程的pom.xml文件配置请参考JAVA样例代码（Flink 1.12）中“pom文件配置”说明。
  • 确保本地编译环境可以正常访问公网。

约束与限制

  • 需要在DLI控制台下“全局配置 > 服务授权”开启Tenant Adminstrator（全局服务）。
  • 写入数据到OBS的桶必须为主账号下所创建的OBS桶。
  • 使用Flink1.15版本的计算引擎时，需要用户自行配置委托，否则可能影响作业运行。

    详细操作请参考自定义DLI委托权限。

Java样例代码（Flink 1.15）

  • pom文件配置 
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    <?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>com.huaweicloud</groupId>
        <artifactId>dli-flink-demo</artifactId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <groupId>org.example</groupId>
    <artifactId>flink-1.15-demo</artifactId>
    <properties>
        <flink.version>1.15.0</flink.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-statebackend-rocksdb</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner_2.12</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
            <version>2.14.2</version>
            <scope>provided</scope>
        </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.3.0</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <archive>
                        <manifest>
                            <mainClass>com.huawei.dli.GetUserConfigFileDemo</mainClass>
                        </manifest>
                    </archive>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
            </plugin>
        </plugins>
        <resources>
            <resource>
                <directory>src/main/resources</directory>
                <filtering>true</filtering>
                <includes>
                    <include>**/*.*</include>
                </includes>
            </resource>
        </resources>
    </build>
</project>
  • 示例代码 
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    package com.huawei.dli;

import com.huawei.dli.source.CustomParallelSource;

import org.apache.flink.api.common.serialization.SimpleStringEncoder;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.contrib.streaming.state.EmbeddedRocksDBStateBackend;
import org.apache.flink.core.fs.Path;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.CheckpointConfig;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink;
import org.apache.flink.streaming.api.functions.sink.filesystem.rollingpolicies.OnCheckpointRollingPolicy;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.File;
import java.io.IOException;
import java.net.URL;
import java.time.LocalDateTime;
import java.time.ZoneOffset;
import java.time.format.DateTimeFormatter;

public class GetUserConfigFileDemo {
    private static final Logger LOG = LoggerFactory.getLogger(GetUserConfigFileDemo.class);

    public static void main(String[] args) {
        try {
            ParameterTool params = ParameterTool.fromArgs(args);
            LOG.info("Params: " + params.toString());

            StreamExecutionEnvironment streamEnv = StreamExecutionEnvironment.getExecutionEnvironment();

            // set checkpoint
            String checkpointPath = params.get("checkpoint.path", "obs://bucket/checkpoint/jobId_jobName/");
            LocalDateTime localDateTime = LocalDateTime.ofEpochSecond(System.currentTimeMillis() / 1000,
                0, ZoneOffset.ofHours(8));
            String dt = localDateTime.format(DateTimeFormatter.ofPattern("yyyyMMdd_HH:mm:ss"));
            checkpointPath = checkpointPath + dt;

            streamEnv.setStateBackend(new EmbeddedRocksDBStateBackend());
            streamEnv.getCheckpointConfig().setCheckpointStorage(checkpointPath);
            streamEnv.getCheckpointConfig().setExternalizedCheckpointCleanup(
                CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
            streamEnv.enableCheckpointing(30 * 1000);

            DataStream<String> stream = streamEnv.addSource(new CustomParallelSource())
                .setParallelism(1)
                .disableChaining();

            String outputPath = params.get("output.path", "obs://bucket/outputPath/jobId_jobName");

            // Get user dependents config
            URL url = GetUserConfigFileDemo.class.getClassLoader().getResource("userData/user.config");
            if (url != null) {
                Path filePath = org.apache.flink.util.FileUtils.absolutizePath(new Path(url.getPath()));
                try {
                    String config = org.apache.flink.util.FileUtils.readFileUtf8(new File(filePath.getPath()));
                    LOG.info("config is {}", config);
                    // Do something by config
                } catch (IOException e) {
                    LOG.error(e.getMessage(), e);
                }
            }

            // Sink OBS
            final StreamingFileSink<String> sinkForRow = StreamingFileSink
                .forRowFormat(new Path(outputPath), new SimpleStringEncoder<String>("UTF-8"))
                .withRollingPolicy(OnCheckpointRollingPolicy.build())
                .build();

            stream.addSink(sinkForRow);

            streamEnv.execute("sinkForRow");
        } catch (Throwable e) {
            LOG.error(e.getMessage(), e);
        }
    }
}
    表1 参数说明

    参数名

    具体含义

    举例

    output.path

    数据写入的OBS路径

    obs://bucket/output

    checkpoint.path

    checkpoint的OBS路径

    obs://bucket/checkpoint

JAVA样例代码（Flink 1.12）

  • pom文件配置 
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    <?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <parent>
        <artifactId>Flink-demo</artifactId>
        <groupId>com.huaweicloud</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <artifactId>flink-kafka-to-obs</artifactId>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <!--Flink 版本-->
        <flink.version>1.12.2</flink.version>
        <!--JDK 版本-->
        <java.version>1.8</java.version>
        <!--Scala 2.11 版本-->
        <scala.binary.version>2.11</scala.binary.version>
        <slf4j.version>2.13.3</slf4j.version>
        <log4j.version>2.10.0</log4j.version>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
    </properties>

    <dependencies>
        <!-- flink -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-statebackend-rocksdb_2.11</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>

        <!--  kafka  -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <!--  logging  -->
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-slf4j-impl</artifactId>
            <version>${slf4j.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-api</artifactId>
            <version>${log4j.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-core</artifactId>
            <version>${log4j.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-jcl</artifactId>
            <version>${log4j.version}</version>
            <scope>provided</scope>
        </dependency>
    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.3.0</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <archive>
                        <manifest>
                            <mainClass>com.huaweicloud.dli.FlinkKafkaToObsExample</mainClass>
                        </manifest>
                    </archive>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
            </plugin>
        </plugins>
        <resources>
            <resource>
                <directory>../main/config</directory>
                <filtering>true</filtering>
                <includes>
                    <include>**/*.*</include>
                </includes>
            </resource>
        </resources>
    </build>
</project>
  • 示例代码 
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    import org.apache.flink.api.common.serialization.SimpleStringEncoder; 
import org.apache.flink.api.common.serialization.SimpleStringSchema; 
import org.apache.flink.api.java.utils.ParameterTool; 
import org.apache.flink.contrib.streaming.state.RocksDBStateBackend; 
import org.apache.flink.core.fs.Path; 
import org.apache.flink.runtime.state.filesystem.FsStateBackend; 
import org.apache.flink.streaming.api.datastream.DataStream; 
import org.apache.flink.streaming.api.environment.CheckpointConfig; 
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; 
import org.apache.flink.streaming.api.functions.sink.filesystem.StreamingFileSink; 
import org.apache.flink.streaming.api.functions.sink.filesystem.bucketassigners.DateTimeBucketAssigner; 
import org.apache.flink.streaming.api.functions.sink.filesystem.rollingpolicies.OnCheckpointRollingPolicy; 
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer; 
import org.apache.kafka.clients.consumer.ConsumerConfig; 
import org.slf4j.Logger; 
import org.slf4j.LoggerFactory; 

import java.util.Properties; 

/** 
 * @author xxx 
 * @date 6/26/21 
 */ 
public class FlinkKafkaToObsExample { 
    private static final Logger LOG = LoggerFactory.getLogger(FlinkKafkaToObsExample.class); 

    public static void main(String[] args) throws Exception { 
        LOG.info("Start Kafka2OBS Flink Streaming Source Java Demo."); 
        ParameterTool params = ParameterTool.fromArgs(args); 
        LOG.info("Params: " + params.toString()); 

        // Kafka连接地址 
        String bootstrapServers; 
        // Kafka消费组 
        String kafkaGroup; 
        // Kafka topic 
        String kafkaTopic; 
        // 消费策略，只有当分区没有Checkpoint或者Checkpoint过期时，才会使用此配置的策略； 
        //          如果存在有效的Checkpoint，则会从此Checkpoint开始继续消费 
        // 取值有： LATEST,从最新的数据开始消费，此策略会忽略通道中已有数据 
        //         EARLIEST,从最初的数据开始消费，此策略会获取通道中所有的有效数据 
        String offsetPolicy; 
        // OBS文件输出路径，格式obs://bucket/path 
        String outputPath; 
        // Checkpoint输出路径，格式obs://bucket/path 
        String checkpointPath; 

        bootstrapServers = params.get("bootstrap.servers", "xxxx:9092,xxxx:9092,xxxx:9092"); 
        kafkaGroup = params.get("group.id", "test-group"); 
        kafkaTopic = params.get("topic", "test-topic"); 
        offsetPolicy = params.get("offset.policy", "earliest"); 
        outputPath = params.get("output.path", "obs://bucket/output"); 
       checkpointPath = params.get("checkpoint.path", "obs://bucket/checkpoint"); 

        try { 
            // 创建执行环境
            StreamExecutionEnvironment streamEnv = StreamExecutionEnvironment.getExecutionEnvironment();
            streamEnv.setParallelism(4);
            RocksDBStateBackend rocksDbBackend = new RocksDBStateBackend(checkpointPath, true);
            RocksDBStateBackend rocksDbBackend = new RocksDBStateBackend(new FsStateBackend(checkpointPath), true); 
            streamEnv.setStateBackend(rocksDbBackend); 
            // 开启Flink CheckPoint配置，开启时若触发CheckPoint，会将Offset信息同步到Kafka 
            streamEnv.enableCheckpointing(300000); 
            // 设置两次checkpoint的最小间隔时间 
            streamEnv.getCheckpointConfig().setMinPauseBetweenCheckpoints(60000); 
            // 设置checkpoint超时时间 
            streamEnv.getCheckpointConfig().setCheckpointTimeout(60000); 
            // 设置checkpoint最大并发数 
            streamEnv.getCheckpointConfig().setMaxConcurrentCheckpoints(1); 
            // 设置作业取消时保留checkpoint 
            streamEnv.getCheckpointConfig().enableExternalizedCheckpoints( 
                    CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION); 

            // Source: 连接kafka数据源 
            Properties properties = new Properties(); 
            properties.setProperty("bootstrap.servers", bootstrapServers); 
            properties.setProperty("group.id", kafkaGroup); 
            properties.setProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, offsetPolicy); 
            String topic = kafkaTopic; 

            // 创建kafka consumer 
            FlinkKafkaConsumer<String> kafkaConsumer = 
                    new FlinkKafkaConsumer<>(topic, new SimpleStringSchema(), properties); 
            /** 
             * 从 Kafka brokers 中的 consumer 组（consumer 属性中的 group.id 设置）提交的偏移量中开始读取分区。 
             * 如果找不到分区的偏移量，那么将会使用配置中的 auto.offset.reset 设置。 
             * 详情 https://ci.apache.org/projects/flink/flink-docs-release-1.13/zh/docs/connectors/datastream/kafka/ 
             */ 
            kafkaConsumer.setStartFromGroupOffsets(); 

            //将kafka 加入数据源 
            DataStream<String> stream = streamEnv.addSource(kafkaConsumer).setParallelism(3).disableChaining(); 

            // 创建文件输出流 
            final StreamingFileSink<String> sink = StreamingFileSink 
                    // 指定文件输出路径与行编码格式 
                    .forRowFormat(new Path(outputPath), new SimpleStringEncoder<String>("UTF-8")) 
                    // 指定文件输出路径批量编码格式，以parquet格式输出 
                    //.forBulkFormat(new Path(outputPath), ParquetAvroWriters.forGenericRecord(schema)) 
                    // 指定自定义桶分配器 
                    .withBucketAssigner(new DateTimeBucketAssigner<>()) 
                    // 指定滚动策略 
                    .withRollingPolicy(OnCheckpointRollingPolicy.build()) 
                    .build(); 

            // Add sink for DIS Consumer data source 
            stream.addSink(sink).disableChaining().name("obs"); 

            // stream.print(); 
            streamEnv.execute(); 
        } catch (Exception e) { 
            LOG.error(e.getMessage(), e); 
        } 
    } 
}
    表2 参数说明

    参数名

    具体含义

    举例

    bootstrap.servers

    kafka连接地址

    kafka服务IP地址1:9092,kafka服务IP地址2:9092,kafka服务IP地址3:9092

    group.id

    kafka消费组

    如当前kafka消费组为test-group

    topic

    kafka消费topic

    如当前kafka消费topic为test-topic

    offset.policy

    kafka的offset策略

    如当前kafka的offset策略为earliest

    output.path

    数据写入的OBS路径

    obs://bucket/output

    checkpoint.path

    checkpoint的OBS路径

    obs://bucket/checkpoint

编译运行

应用程序开发完成后，参考Flink Jar作业开发基础样例将编译打包的JAR包上传到DLI运行，查看对应OBS路径下是否有相关的数据信息。

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