#yyds干货盘点#将CSV的数据发送到kafka(java版)
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列名称 | 说明 |
---|---|
用户ID | 整数类型,序列化后的用户ID |
商品ID | 整数类型,序列化后的商品ID |
商品类目ID | 整数类型,序列化后的商品所属类目ID |
行为类型 | 字符串,枚举类型,包括(pv, buy, cart, fav) |
时间戳 | 行为发生的时间戳 |
时间字符串 | 根据时间戳字段生成的时间字符串 |
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关于该数据集的详情,请参考《准备数据集用于flink学习》
Java应用简介
编码前,先把具体内容列出来,然后再挨个实现:
- 从CSV读取记录的工具类:UserBehaviorCsvFileReader
- 每条记录对应的Bean类:UserBehavior
- Java对象序列化成JSON的序列化类:JsonSerializer
- 向kafka发送消息的工具类:KafkaProducer
- 应用类,程序入口:SendMessageApplication
上述五个类即可完成Java应用的工作,接下来开始编码吧;
直接下载源码
- 如果您不想写代码,您可以直接从GitHub下载这个工程的源码,地址和链接信息如下表所示:
名称 | 链接 | 备注 |
---|---|---|
项目主页 | https://github.com/zq2599/blog_demos | 该项目在GitHub上的主页 |
git仓库地址(https) | https://github.com/zq2599/blog_demos.git | 该项目源码的仓库地址,https协议 |
git仓库地址(ssh) | git@github.com:zq2599/blog_demos.git | 该项目源码的仓库地址,ssh协议 |
- 这个git项目中有多个文件夹,本章源码在flinksql这个文件夹下,如下图红框所示:
编码
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创建maven工程,pom.xml如下,比较重要的jackson和javacsv的依赖:
<?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> <groupId>com.bolingcavalry</groupId> <artifactId>flinksql</artifactId> <version>1.0-SNAPSHOT</version> <properties> <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding> <flink.version>1.10.0</flink.version> <kafka.version>2.2.0</kafka.version> <java.version>1.8</java.version> <scala.binary.version>2.11</scala.binary.version> <maven.compiler.source>$java.version</maven.compiler.source> <maven.compiler.target>$java.version</maven.compiler.target> </properties> <dependencies> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-clients</artifactId> <version>$kafka.version</version> </dependency> <dependency> <groupId>com.fasterxml.jackson.core</groupId> <artifactId>jackson-databind</artifactId> <version>2.9.10.1</version> </dependency> <!-- Logging dependencies --> <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-log4j12</artifactId> <version>1.7.7</version> <scope>runtime</scope> </dependency> <dependency> <groupId>log4j</groupId> <artifactId>log4j</artifactId> <version>1.2.17</version> <scope>runtime</scope> </dependency> <dependency> <groupId>net.sourceforge.javacsv</groupId> <artifactId>javacsv</artifactId> <version>2.0</version> </dependency> </dependencies> <build> <plugins> <!-- Java Compiler --> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-compiler-plugin</artifactId> <version>3.1</version> <configuration> <source>$java.version</source> <target>$java.version</target> </configuration> </plugin> <!-- Shade plugin to include all dependencies --> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-shade-plugin</artifactId> <version>3.0.0</version> <executions> <!-- Run shade goal on package phase --> <execution> <phase>package</phase> <goals> <goal>shade</goal> </goals> <configuration> <artifactSet> <excludes> </excludes> </artifactSet> <filters> <filter> <!-- Do not copy the signatures in the META-INF folder. Otherwise, this might cause SecurityExceptions when using the JAR. --> <artifact>*:*</artifact> <excludes> <exclude>META-INF/*.SF</exclude> <exclude>META-INF/*.DSA</exclude> <exclude>META-INF/*.RSA</exclude> </excludes> </filter> </filters> </configuration> </execution> </executions> </plugin> </plugins> </build> </project>
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从CSV读取记录的工具类:==UserBehaviorCsvFileReader==,后面在主程序中会用到java8的Steam API来处理集合,所以UserBehaviorCsvFileReader实现了Supplier接口:
public class UserBehaviorCsvFileReader implements Supplier<UserBehavior> private final String filePath; private CsvReader csvReader; public UserBehaviorCsvFileReader(String filePath) throws IOException this.filePath = filePath; try csvReader = new CsvReader(filePath); csvReader.readHeaders(); catch (IOException e) throw new IOException("Error reading TaxiRecords from file: " + filePath, e); @Override public UserBehavior get() UserBehavior userBehavior = null; try if(csvReader.readRecord()) csvReader.getRawRecord(); userBehavior = new UserBehavior( Long.valueOf(csvReader.get(0)), Long.valueOf(csvReader.get(1)), Long.valueOf(csvReader.get(2)), csvReader.get(3), new Date(Long.valueOf(csvReader.get(4))*1000L)); catch (IOException e) throw new NoSuchElementException("IOException from " + filePath); if (null==userBehavior) throw new NoSuchElementException("All records read from " + filePath); return userBehavior;
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每条记录对应的Bean类:==UserBehavior==,和CSV记录格式保持一致即可,表示时间的==ts==字段,使用了JsonFormat注解,在序列化的时候以此来控制格式:
public class UserBehavior @JsonFormat private long user_id; @JsonFormat private long item_id; @JsonFormat private long category_id; @JsonFormat private String behavior; @JsonFormat(shape = JsonFormat.Shape.STRING, pattern = "yyyy-MM-ddTHH:mm:ssZ") private Date ts; public UserBehavior() public UserBehavior(long user_id, long item_id, long category_id, String behavior, Date ts) this.user_id = user_id; this.item_id = item_id; this.category_id = category_id; this.behavior = behavior; this.ts = ts;
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Java对象序列化成JSON的序列化类:JsonSerializer
public class JsonSerializer<T> private final ObjectMapper jsonMapper = new ObjectMapper(); public String toJSONString(T r) try return jsonMapper.writeValueAsString(r); catch (JsonProcessingException e) throw new IllegalArgumentException("Could not serialize record: " + r, e); public byte[] toJSONBytes(T r) try return jsonMapper.writeValueAsBytes(r); catch (JsonProcessingException e) throw new IllegalArgumentException("Could not serialize record: " + r, e);
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向kafka发送消息的工具类:==KafkaProducer==:
public class KafkaProducer implements Consumer<UserBehavior> private final String topic; private final org.apache.kafka.clients.producer.KafkaProducer<byte[], byte[]> producer; private final JsonSerializer<UserBehavior> serializer; public KafkaProducer(String kafkaTopic, String kafkaBrokers) this.topic = kafkaTopic; this.producer = new org.apache.kafka.clients.producer.KafkaProducer<>(createKafkaProperties(kafkaBrokers)); this.serializer = new JsonSerializer<>(); @Override public void accept(UserBehavior record) // 将对象序列化成byte数组 byte[] data = serializer.toJSONBytes(record); // 封装 ProducerRecord<byte[], byte[]> kafkaRecord = new ProducerRecord<>(topic, data); // 发送 producer.send(kafkaRecord); // 通过sleep控制消息的速度,请依据自身kafka配置以及flink服务器配置来调整 try Thread.sleep(500); catch(InterruptedException e) e.printStackTrace(); /** * kafka配置 * @param brokers The brokers to connect to. * @return A Kafka producer configuration. */ private static Properties createKafkaProperties(String brokers) Properties kafkaProps = new Properties(); kafkaProps.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, brokers); kafkaProps.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, ByteArraySerializer.class.getCanonicalName()); kafkaProps.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, ByteArraySerializer.class.getCanonicalName()); return kafkaProps;
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最后是应用类SendMessageApplication,CSV文件路径、kafka的topic和borker地址都在此设置,另外借助java8的Stream API,只需少量代码即可完成所有工作:
public class SendMessageApplication public static void main(String[] args) throws Exception // 文件地址 String filePath = "D:\\\\temp\\\\202005\\\\02\\\\UserBehavior.csv"; // kafka topic String topic = "user_behavior"; // kafka borker地址 String broker = "192.168.50.43:9092"; Stream.generate(new UserBehaviorCsvFileReader(filePath)) .sequential() .forEachOrdered(new KafkaProducer(topic, broker));
验证
- 请确保kafka已经就绪,并且名为==user_behavior==的topic已经创建;
- 请将CSV文件准备好;
- 确认SendMessageApplication.java中的文件地址、kafka topic、kafka broker三个参数准确无误;
- 运行SendMessageApplication.java;
- 开启一个 控制台消息kafka消息,参考命令如下:
./kafka-console-consumer.sh \\ --bootstrap-server 127.0.0.1:9092 \\ --topic user_behavior \\ --consumer-property group.id=old-consumer-test \\ --consumer-property consumer.id=old-consumer-cl \\ --from-beginning
- 正常情况下可以立即见到消息,如下图:
至此,通过Java应用模拟用户行为消息流的操作就完成了,接下来的flink实战就用这个作为数据源;
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