阅读 245

Kafka基础(四):Kafka API 实战

1 环境准备

1)启动 zk 和 kafka 集群,在 kafka 集群中打开一个消费者
[atguigu@hadoop102 kafka]$ bin/kafka-console-consumer.sh --zookeeper hadoop102:2181 --topic first
2)导入 pom 依赖

 
 
 org.apache.kafka
 kafka-clients
 0.11.0.0
 
 
 
 org.apache.kafka
 kafka_2.12
 0.11.0.0
 

2 Kafka 生产者 Java API

2.1 创建生产者(过时的 API)
package com.atguigu.kafka;
import java.util.Properties;
import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
public class OldProducer {
@SuppressWarnings("deprecation")
public static void main(String[] args) {
Properties properties = new Properties();
properties.put("metadata.broker.list", "hadoop102:9092");
properties.put("request.required.acks", "1");
properties.put("serializer.class", "kafka.serializer.StringEncoder");
Producer producer = new Producer(new
ProducerConfig(properties));
KeyedMessage message = new KeyedMessage<Integer, 
String>("first", "hello world");
producer.send(message );
} }
View Code
2.2 创建生产者(新 API)
package com.atguigu.kafka;
import java.util.Properties;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;
public class NewProducer {
public static void main(String[] args) {
Properties props = new Properties();
// Kafka 服务端的主机名和端口号
props.put("bootstrap.servers", "hadoop103:9092");
// 等待所有副本节点的应答
props.put("acks", "all");
// 消息发送最大尝试次数
props.put("retries", 0);
// 一批消息处理大小
props.put("batch.size", 16384);
// 请求延时
props.put("linger.ms", 1);
// 发送缓存区内存大小
props.put("buffer.memory", 33554432);
// key 序列化
props.put("key.serializer", 
"org.apache.kafka.common.serialization.StringSerializer");
// value 序列化
props.put("value.serializer", 
"org.apache.kafka.common.serialization.StringSerializer");
Producer producer = new KafkaProducer<>(props);
for (int i = 0; i < 50; i++) {
producer.send(new ProducerRecord("first", 
Integer.toString(i), "hello world-" + i));
}
producer.close();
} }
View Code
2.3 创建生产者带回调函数(新 API)
package com.atguigu.kafka;
import java.util.Properties;
import org.apache.kafka.clients.producer.Callback;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
public class CallBackProducer {
public static void main(String[] args) {
Properties props = new Properties();
// Kafka 服务端的主机名和端口号
props.put("bootstrap.servers", "hadoop103:9092");
// 等待所有副本节点的应答
props.put("acks", "all");
// 消息发送最大尝试次数
props.put("retries", 0);
// 一批消息处理大小
props.put("batch.size", 16384);
// 增加服务端请求延时
props.put("linger.ms", 1);
// 发送缓存区内存大小
props.put("buffer.memory", 33554432);
// key 序列化
props.put("key.serializer", 
"org.apache.kafka.common.serialization.StringSerializer");
// value 序列化
props.put("value.serializer", 
"org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer kafkaProducer = new KafkaProducer<>(props);
for (int i = 0; i < 50; i++) {
kafkaProducer.send(new ProducerRecord("first", "hello" 
+ i), new Callback() {
@Override
public void onCompletion(RecordMetadata metadata, Exception 
exception) {
if (metadata != null) {
System.err.println(metadata.partition() + "---" + 
metadata.offset());
} }
});
}
kafkaProducer.close();
} }
View Code
2.4 自定义分区生产者
0)需求:将所有数据存储到 topic 的第 0 号分区上
1)定义一个类实现 Partitioner 接口,重写里面的方法(过时 API)
package com.atguigu.kafka;
import java.util.Map;
import kafka.producer.Partitioner;
public class CustomPartitioner implements Partitioner {
public CustomPartitioner() {
super();
}
@Override
public int partition(Object key, int numPartitions) {
// 控制分区
return 0;
} }
View Code
2)自定义分区(新 API)
package com.atguigu.kafka;
import java.util.Map;
import org.apache.kafka.clients.producer.Partitioner;
import org.apache.kafka.common.Cluster;
public class CustomPartitioner implements Partitioner {
@Override
public void configure(Map configs) {
}
@Override
public int partition(String topic, Object key, byte[] keyBytes, Object value, byte[] 
valueBytes, Cluster cluster) {
 // 控制分区
return 0;
}
@Override
public void close() {
} }
View Code
3)在代码中调用
package com.atguigu.kafka;
import java.util.Properties;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;
public class PartitionerProducer {
public static void main(String[] args) {
Properties props = new Properties();
// Kafka 服务端的主机名和端口号
props.put("bootstrap.servers", "hadoop103:9092");
// 等待所有副本节点的应答
props.put("acks", "all");
// 消息发送最大尝试次数
props.put("retries", 0);
// 一批消息处理大小
props.put("batch.size", 16384);
// 增加服务端请求延时
props.put("linger.ms", 1);
// 发送缓存区内存大小
props.put("buffer.memory", 33554432);
// key 序列化
props.put("key.serializer", 
"org.apache.kafka.common.serialization.StringSerializer");
// value 序列化
props.put("value.serializer", 
"org.apache.kafka.common.serialization.StringSerializer");
// 自定义分区
props.put("partitioner.class", "com.atguigu.kafka.CustomPartitioner");
Producer producer = new KafkaProducer<>(props);
producer.send(new ProducerRecord("first", "1", "atguigu"));
producer.close();
} }
View Code
4)测试
(1)在 hadoop102 上监控/opt/module/kafka/logs/目录下 first 主题 3 个分区的 log 日志动态变化情况
[atguigu@hadoop102 first-0]$ tail -f 00000000000000000000.log
[atguigu@hadoop102 first-1]$ tail -f 00000000000000000000.log
[atguigu@hadoop102 first-2]$ tail -f 00000000000000000000.log
(2)发现数据都存储到指定的分区了。

3 Kafka 消费者 Java API

3.1 高级 API
0)在控制台创建发送者
[atguigu@hadoop104 kafka]$ bin/kafka-console-producer.sh --broker-list hadoop102:9092 --topic first
>hello world
1)创建消费者(过时 API)
package com.atguigu.kafka.consume;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import kafka.consumer.Consumer;
import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
public class CustomConsumer {
@SuppressWarnings("deprecation")
public static void main(String[] args) {
Properties properties = new Properties();
properties.put("zookeeper.connect", "hadoop102:2181");
properties.put("group.id", "g1");
properties.put("zookeeper.session.timeout.ms", "500");
properties.put("zookeeper.sync.time.ms", "250");
properties.put("auto.commit.interval.ms", "1000");
// 创建消费者连接器
ConsumerConnector consumer = Consumer.createJavaConsumerConnector(new
ConsumerConfig(properties));
HashMap topicCount = new HashMap<>();
topicCount.put("first", 1);
Mapbyte[], byte[]>>> consumerMap = 
consumer.createMessageStreams(topicCount);
KafkaStream<byte[], byte[]> stream = consumerMap.get("first").get(0);
ConsumerIterator<byte[], byte[]> it = stream.iterator();
while (it.hasNext()) {
System.out.println(new String(it.next().message()));
} } }
View Code
2)官方提供案例(自动维护消费情况)(新 API)
package com.atguigu.kafka.consume;
import java.util.Arrays;
import java.util.Properties;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
public class CustomNewConsumer {
public static void main(String[] args) {
Properties props = new Properties();
// 定义 kakfa 服务的地址,不需要将所有 broker 指定上
props.put("bootstrap.servers", "hadoop102:9092");
// 制定 consumer group 
props.put("group.id", "test");
// 是否自动确认 offset 
props.put("enable.auto.commit", "true");
// 自动确认 offset 的时间间隔
props.put("auto.commit.interval.ms", "1000");
// key 的序列化类
props.put("key.deserializer", 
"org.apache.kafka.common.serialization.StringDeserializer");
// value 的序列化类
props.put("value.deserializer", 
"org.apache.kafka.common.serialization.StringDeserializer");
// 定义 consumer 
KafkaConsumer consumer = new KafkaConsumer<>(props);
// 消费者订阅的 topic, 可同时订阅多个
consumer.subscribe(Arrays.asList("first", "second","third"));
while (true) {
// 读取数据,读取超时时间为 100ms 
ConsumerRecords records = consumer.poll(100);
for (ConsumerRecord record : records)
System.out.printf("offset = %d, key = %s, value = %s%n", 
record.offset(), record.key(), record.value());
} } }
View Code
3.2 低级 API
3)代码:
package com.atguigu;
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import kafka.api.FetchRequest;
import kafka.api.FetchRequestBuilder;
import kafka.api.PartitionOffsetRequestInfo;
import kafka.cluster.BrokerEndPoint;
import kafka.common.ErrorMapping;
import kafka.common.TopicAndPartition;
import kafka.javaapi.FetchResponse;
import kafka.javaapi.OffsetResponse;
import kafka.javaapi.PartitionMetadata;
import kafka.javaapi.TopicMetadata;
import kafka.javaapi.TopicMetadataRequest;
import kafka.javaapi.consumer.SimpleConsumer;
import kafka.message.MessageAndOffset;
public class SimpleExample {
 private List m_replicaBrokers = new ArrayList<>();
 public SimpleExample() {
 m_replicaBrokers = new ArrayList<>();
 }
 public static void main(String args[]) {
 SimpleExample example = new SimpleExample();
 // 最大读取消息数量
 long maxReads = Long.parseLong("3");
 // 要订阅的 topic
 String topic = "test1";
 // 要查找的分区
 int partition = Integer.parseInt("0");
 // broker 节点的 ip
 List seeds = new ArrayList<>();
 seeds.add("192.168.9.102");
 seeds.add("192.168.9.103");
 seeds.add("192.168.9.104");
 // 端口
 int port = Integer.parseInt("9092");
 try {
 example.run(maxReads, topic, partition, seeds, port);
 } catch (Exception e) {
 System.out.println("Oops:" + e);
 e.printStackTrace();
 }
 }
 public void run(long a_maxReads, String a_topic, int a_partition, List 
a_seedBrokers, int a_port) throws Exception {
 // 获取指定 Topic partition 的元数据
 PartitionMetadata metadata = findLeader(a_seedBrokers, a_port, a_topic, 
a_partition);
 if (metadata == null) {
 System.out.println("Can‘t find metadata for Topic and Partition. Exiting");
 return;
 }
 if (metadata.leader() == null) {
 System.out.println("Can‘t find Leader for Topic and Partition. Exiting");
 return;
 }
 String leadBroker = metadata.leader().host();
 String clientName = "Client_" + a_topic + "_" + a_partition;
 SimpleConsumer consumer = new SimpleConsumer(leadBroker, a_port, 100000, 64 * 
1024, clientName);
 long readOffset = getLastOffset(consumer, a_topic, a_partition, 
kafka.api.OffsetRequest.EarliestTime(), clientName);
 int numErrors = 0;
 while (a_maxReads > 0) {
 if (consumer == null) {
 consumer = new SimpleConsumer(leadBroker, a_port, 100000, 64 * 1024, 
clientName);
 }
 FetchRequest req = new 
FetchRequestBuilder().clientId(clientName).addFetch(a_topic, a_partition, 
readOffset, 100000).build();
 FetchResponse fetchResponse = consumer.fetch(req);
 if (fetchResponse.hasError()) {
 numErrors++;
 // Something went wrong!
 short code = fetchResponse.errorCode(a_topic, a_partition);
 System.out.println("Error fetching data from the Broker:" + leadBroker 
+ " Reason: " + code);
 if (numErrors > 5)
 break;
 if (code == ErrorMapping.OffsetOutOfRangeCode()) {
 // We asked for an invalid offset. For simple case ask for
 // the last element to reset
 readOffset = getLastOffset(consumer, a_topic, a_partition, 
kafka.api.OffsetRequest.LatestTime(), clientName);
 continue;
 }
 consumer.close();
 consumer = null;
 leadBroker = findNewLeader(leadBroker, a_topic, a_partition, a_port);
 continue;
 }
 numErrors = 0;
 long numRead = 0;
 for (MessageAndOffset messageAndOffset : fetchResponse.messageSet(a_topic, 
a_partition)) {
 long currentOffset = messageAndOffset.offset();
 if (currentOffset < readOffset) {
 System.out.println("Found an old offset: " + currentOffset + " 
Expecting: " + readOffset);
 continue;
 }
 readOffset = messageAndOffset.nextOffset();
 ByteBuffer payload = messageAndOffset.message().payload();
 byte[] bytes = new byte[payload.limit()];
 payload.get(bytes);
 System.out.println(String.valueOf(messageAndOffset.offset()) + ": " + 
new String(bytes, "UTF-8"));
 numRead++;
 a_maxReads--;
 }
 if (numRead == 0) {
 try {
 Thread.sleep(1000);
 } catch (InterruptedException ie) {
 }
 }
 }
 if (consumer != null)
 consumer.close();
 }
 public static long getLastOffset(SimpleConsumer consumer, String topic, int 
partition, long whichTime, String clientName) {
 TopicAndPartition topicAndPartition = new TopicAndPartition(topic, partition);
 Map requestInfo = new 
HashMap();
 requestInfo.put(topicAndPartition, new PartitionOffsetRequestInfo(whichTime, 
1));
 kafka.javaapi.OffsetRequest request = new 
kafka.javaapi.OffsetRequest(requestInfo, kafka.api.OffsetRequest.CurrentVersion(), 
clientName);
 OffsetResponse response = consumer.getOffsetsBefore(request);
 if (response.hasError()) {
 System.out.println("Error fetching data Offset Data the Broker. Reason: " 
+ response.errorCode(topic, partition));
 return 0;
 }
 long[] offsets = response.offsets(topic, partition);
 return offsets[0];
 }
 private String findNewLeader(String a_oldLeader, String a_topic, int a_partition, 
int a_port) throws Exception {
 for (int i = 0; i < 3; i++) {
 boolean goToSleep = false;
 PartitionMetadata metadata = findLeader(m_replicaBrokers, a_port, a_topic, 
a_partition);
 if (metadata == null) {
 goToSleep = true;
 } else if (metadata.leader() == null) {
 goToSleep = true;
 } else if (a_oldLeader.equalsIgnoreCase(metadata.leader().host()) && i == 
0) {
 // first time through if the leader hasn‘t changed give
 // ZooKeeper a second to recover
 // second time, assume the broker did recover before failover,
 // or it was a non-Broker issue
 //
 goToSleep = true;
 } else {
 return metadata.leader().host();
 }
 if (goToSleep) {
 Thread.sleep(1000);
 }
 }
 System.out.println("Unable to find new leader after Broker failure. Exiting");
 throw new Exception("Unable to find new leader after Broker failure. Exiting");
 }
 private PartitionMetadata findLeader(List a_seedBrokers, int a_port, 
String a_topic, int a_partition) {
 PartitionMetadata returnMetaData = null;
 loop:
 for (String seed : a_seedBrokers) {
 SimpleConsumer consumer = null;
 try {
 consumer = new SimpleConsumer(seed, a_port, 100000, 64 * 1024, 
"leaderLookup");
 List topics = Collections.singletonList(a_topic);
 TopicMetadataRequest req = new TopicMetadataRequest(topics);
 kafka.javaapi.TopicMetadataResponse resp = consumer.send(req);
 List metaData = resp.topicsMetadata();
 for (TopicMetadata item : metaData) {
 for (PartitionMetadata part : item.partitionsMetadata()) {
 if (part.partitionId() == a_partition) {
 returnMetaData = part;
 break loop;
 }
 }
 }
 } catch (Exception e) {
 System.out.println("Error communicating with Broker [" + seed + "] to 
find Leader for [" + a_topic + ", " + a_partition + "] Reason: " + e);
 } finally {
 if (consumer != null)
 consumer.close();
 }
 }
 if (returnMetaData != null) {
 m_replicaBrokers.clear();
 for (BrokerEndPoint replica : returnMetaData.replicas()) {
 m_replicaBrokers.add(replica.host());
 }
 }
 return returnMetaData;
 } }
View Code

 

 

原文:https://www.cnblogs.com/qiu-hua/p/13388411.html

文章分类
代码人生
文章标签
版权声明:本站是系统测试站点,无实际运营。本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌抄袭侵权/违法违规的内容, 请发送邮件至 XXXXXXo@163.com 举报,一经查实,本站将立刻删除。
相关推荐