4.1 環(huán)境準(zhǔn)備
1）在eclipse中創(chuàng)建一個java工程
2）在工程的根目錄創(chuàng)建一個lib文件夾
3）解壓kafka安裝包缺脉，將安裝包libs目錄下的jar包拷貝到工程的lib目錄下，并build path秕衙。
4）啟動zk和kafka集群贴唇，在kafka集群中打開一個消費者
[itstar@bigdata11 kafka]$ bin/kafka-console-consumer.sh --zookeeper
bigdata11:2181 --topic first
4.2 Kafka生產(chǎn)者Java API
4.2.1 創(chuàng)建生產(chǎn)者（過時的API）
package com.itstar.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", "bigdata11:9092");
properties.put("request.required.acks", "1");
properties.put("serializer.class", "kafka.serializer.StringEncoder");
Producer<Integer, String> producer = new Producer<Integer,String>(new
ProducerConfig(properties));
KeyedMessage<Integer, String> message = new KeyedMessage<Integer,
String>("first", "hello world");
producer.send(message );
}
}
4.2.2 創(chuàng)建生產(chǎn)者（新API）
package com.itstar.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服務(wù)端的主機名和端口號
props.put("bootstrap.servers", "bigdata12:9092");
// 等待所有副本節(jié)點的應(yīng)答
props.put("acks", "all");
// 消息發(fā)送最大嘗試次數(shù)
props.put("retries", 0);
// 一批消息處理大小
props.put("batch.size", 16384);
// 請求延時
props.put("linger.ms", 1);
// 發(fā)送緩存區(qū)內(nèi)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<String, String> producer = new KafkaProducer<>(props);
for (int i = 0; i < 50; i++) {
producer.send(new ProducerRecord<String, String>("first",
Integer.toString(i), "hello world-" + i));
}
producer.close();
}
}
4.2.3 創(chuàng)建生產(chǎn)者帶回調(diào)函數(shù)（新API）
package com.itstar.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服務(wù)端的主機名和端口號
props.put("bootstrap.servers", "bigdata12:9092");
// 等待所有副本節(jié)點的應(yīng)答
props.put("acks", "all");
// 消息發(fā)送最大嘗試次數(shù)
props.put("retries", 0);
// 一批消息處理大小
props.put("batch.size", 16384);
// 增加服務(wù)端請求延時
props.put("linger.ms", 1);
// 發(fā)送緩存區(qū)內(nèi)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<String, String> kafkaProducer = new KafkaProducer<>
(props);
for (int i = 0; i < 50; i++) {
kafkaProducer.send(new ProducerRecord<String, String>("first",
"hello" + i), new Callback() {
@Override
public void onCompletion(RecordMetadata metadata, Exception
exception) {
if (metadata != null) {
System.out.println(metadata.partition() + "---" +
metadata.offset());
}
}
});
}
kafkaProducer.close();
}
}
4.2.4 自定義分區(qū)生產(chǎn)者
0）需求：將所有數(shù)據(jù)存儲到topic的第0號分區(qū)上
1）定義一個類實現(xiàn)Partitioner接口，重寫里面的方法（過時API）
package com.itstar.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) {
// 控制分區(qū)
return 0;
}
}
2）自定義分區(qū)（新API）
package com.itstar.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<String, ?> configs) {
}
@Override
public int partition(String topic, Object key, byte[] keyBytes, Object
value, byte[] valueBytes, Cluster cluster) {
// 控制分區(qū)
return 0;
}
@Override
public void close() {
}
}
3）在代碼中調(diào)用
package com.itstar.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服務(wù)端的主機名和端口號
props.put("bootstrap.servers", "bigdata12:9092");
// 等待所有副本節(jié)點的應(yīng)答
props.put("acks", "all");
// 消息發(fā)送最大嘗試次數(shù)
props.put("retries", 0);
// 一批消息處理大小
props.put("batch.size", 16384);
// 增加服務(wù)端請求延時
props.put("linger.ms", 1);
// 發(fā)送緩存區(qū)內(nèi)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");
// 自定義分區(qū)
props.put("partitioner.class", "com.itstar.kafka.CustomPartitioner");
Producer<String, String> producer = new KafkaProducer<>(props);
producer.send(new ProducerRecord<String, String>("first", "1",
"itstar"));
producer.close();
}
}
4）測試
（1）在bigdata11上監(jiān)控/opt/module/kafka/logs/目錄下fifirst主題3個分區(qū)的log日志動態(tài)變化情況
[itstar@bigdata11 first-0]$ tail -f 00000000000000000000.log
[itstar@bigdata11 first-1]$ tail -f 00000000000000000000.log
[itstar@bigdata11 first-2]$ tail -f 00000000000000000000.log
（2）發(fā)現(xiàn)數(shù)據(jù)都存儲到指定的分區(qū)了。
4.3 Kafka消費者Java API
0）在控制臺創(chuàng)建發(fā)送者
[itstar@bigdata13 kafka]$ bin/kafka-console-producer.sh --broker-list
bigdata11:9092 --topic first
>hello world
1）創(chuàng)建消費者（過時API）
package com.itstar.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", "bigdata11:2181");
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");
// 創(chuàng)建消費者連接器
ConsumerConnector consumer = Consumer.createJavaConsumerConnector(new
ConsumerConfig(properties));
HashMap<String, Integer> topicCount = new HashMap<>();
topicCount.put("first", 1);
Map<String, List<KafkaStream<byte[], 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()));
}
}
}
2）官方提供案例（自動維護(hù)消費情況）（新API）
package com.itstar.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();
// 定義kakfa 服務(wù)的地址瞻坝，不需要將所有broker指定上
props.put("bootstrap.servers", "bigdata11:9092");
// 制定consumer group
props.put("group.id", "test");
// 是否自動確認(rèn)offset
props.put("enable.auto.commit", "true");
// 自動確認(rèn)offset的時間間隔
props.put("auto.commit.interval.ms", "1000");
// key的序列化類
props.put("key.deserializer",
"org.apache.kafka.common.serialization.StringDeserializer");
// value的序列化類
props.put("value.deserializer",
"org.apache.kafka.common.serialization.StringDeserializer");
// 定義consumer
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
// 消費者訂閱的topic, 可同時訂閱多個
consumer.subscribe(Arrays.asList("first", "second","third"));
while (true) {
// 讀取數(shù)據(jù)，讀取超時時間為100ms
ConsumerRecords<String, String> records = consumer.poll(100);
for (ConsumerRecord<String, String> record : records)
System.out.printf("offset = %d, key = %s, value = %s%n",
record.offset(), record.key(), record.value());
}
}
}
