需求
需求就是将流量数据（json格式）中某个接口数据抽取一下。如：有个identityUri="yiyang/user/getById/13782" , 这里的13782，是个userId，我们需要将其处理成 identityUri="yiyang/user/getById/{}"
关于接口抽取，有两种方式：
- 使用正则替换。正则替换不全，而且有风险，可能会被误替换
- 如果能拿到swagger的接口列表，我们可以根据前缀树算法来进行匹配替换（推荐）。这种不会被误替换，但是如果增加接口，我们需要更新swagger的接口数据
实际上我们生产中是将二者接口使用的。先使用2，如果没有匹配到，在使用1
这里是演示flink kafka的用法，我们简单使用正则处理
依赖jar包
<properties>
<flink.version>1.12.0</flink.version>
<java.version>1.8</java.version>
<scala.binary.version>2.11</scala.binary.version>
</properties>
<dependencies>
<!-- kafka连接器 -->
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-kafka_${scala.binary.version}</artifactId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>fastjson</artifactId>
<version>1.2.75</version>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
<version>1.12.2</version>
</dependency>
<dependency>
<artifactId>flink-clients_${scala.binary.version}</artifactId>
<groupId>org.apache.flink</groupId>
<version>${flink.version}</version>
</dependency>
<dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<version>1.2.3</version>
</dependency>
</dependencies>
编写代码
package com.liufei.flink;
import com.alibaba.fastjson.JSONObject;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.Properties;
public class ConsumeKafkaTest {
private static final Logger log = LoggerFactory.getLogger(ConsumeKafkaTest.class);
public static void main(String[] args) {
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// checkpoint
// env.enableCheckpointing(10 * 1000L);
Properties prop = new Properties();
prop.setProperty("bootstrap.servers", "192.168.18.144:9092"); // kafka地址
prop.setProperty("group.id", "consumer_flink");
// 消费消息的topic
String consumeTopic = "yiyang";
FlinkKafkaConsumer<String> kafkaConsumer = new FlinkKafkaConsumer<>(
consumeTopic, new SimpleStringSchema(), prop);
// 从最新的数据开始消费
// kafkaConsumer.setStartFromLatest();
kafkaConsumer.setStartFromGroupOffsets();
// sink的topic
String produceTopic = "yiyang_sink";
FlinkKafkaProducer<String> kafkaProducer = new FlinkKafkaProducer<>(
produceTopic, new SimpleStringSchema(), prop);
env.addSource(kafkaConsumer)
.flatMap(new FlatMapFunction<String, String>() {
@Override
public void flatMap(String content, Collector<String> collector) throws Exception {
log.info("Flink msg: {}", content);
JSONObject jsonObject = JSONObject.parseObject(content);
jsonObject.put("identityUri", replaceUri(jsonObject.getString("identityUri")));
String contentSink = jsonObject.toJSONString();
log.info("Flink sink: {}", contentSink);
collector.collect(contentSink);
}
})
.addSink(kafkaProducer)
.setParallelism(2);
try {
env.execute("My Flink Test");
} catch (Exception e) {
e.printStackTrace();
}
}
/**
* 接口抽取
* @param identityUri
* @return
*/
private static String replaceUri(String identityUri) {
if (identityUri == null) {
return null;
}
return identityUri.replaceAll("[0-9]+", "{}");
}
}
注意：kafka消费的方式是： kafkaConsumer.setStartFromGroupOffsets();
- 从最早位点开始消费
consumer.setStartFromEarliest();
- 从指定时间点开始消费
consumer.setStartFromTimestamp(1559801580000l);
- 从最新的数据开始消费
# 如果消费组中之前有没有消费的消息，则不会被消费，会重置offset成最新的值，这种情况会导致消息丢失。一般不用这个，用下面的
consumer.setStartFromLatest();
2022-07-03 18:31:07.029 INFO PID_IS_UNDEFINED --- [Kafka Fetcher for Source: Custom Source -> Flat Map (8/8)#0] o.a.k.clients.consumer.internals.SubscriptionState - [Consumer clientId=consumer-consumer_flink-15, groupId=consumer_flink] Resetting offset for partition yiyang-0 to offset 22.
2022-07-03 18:31:12.093 INFO PID_IS_UNDEFINED --- [Kafka Fetcher for Source: Custom Source -> Flat Map (8/8)#0] o.a.k.c.consumer.internals.AbstractCoordinator - [Consumer clientId=consumer-consumer_flink-15, groupId=consumer_flink] Discovered group coordinator 192.168.18.144:9092 (id: 2147483647 rack: null)
看下上面的启动日志，有这样的信息：Resetting offset for partition yiyang-0 to offset 22.
- 从上次消费位点开始消费
consumer.setStartFromGroupOffsets();
验证
我们另外启动一个程序，发送消息，并消费两个topic中的数据
{"ip":"127.0.0.5","identityUri":"yiyang/user/getById/13782"}
看下 ConsumeKafkaTest 中的日志
2022-07-03 18:58:48.594 INFO PID_IS_UNDEFINED --- [Legacy Source Thread - Source: Custom Source -> Flat Map (8/8)#0] com.liufei.flink.ConsumeKafkaTest - Flink msg: {"ip":"127.0.0.5","identityUri":"yiyang/user/getById/13782"}
2022-07-03 18:58:48.655 INFO PID_IS_UNDEFINED --- [Legacy Source Thread - Source: Custom Source -> Flat Map (8/8)#0] com.liufei.flink.ConsumeKafkaTest - Flink sink: {"ip":"127.0.0.5","identityUri":"yiyang/user/getById/{}"}
在看下另外一个服务（消费两个topic数据）的日志：
image.png
说明已经成功的把处理好的消息发送到另外一个topic中了
扩展
关于数据处理，如果只是简单的增加字段，减少字段，正则替换，也可以使用logstash工具
