以下kafka集群的节点分别是node01,node02,node03
习题一:
在kafka集群中创建student主题 副本为2个,分区为3个
生产者设置:
设置key的序列化为 org.apache.kafka.common.serialization. StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
其他都是默认设置
消费者设置:
消费者组id为test
设置key的序列化为org.apache.kafka.common.serialization. StringDeserializer
设置value的序列化为org.apache.kafka.common.serialization. StringDeserializer
其他都是默认设置
模拟生产者,请写出代码向student主题中生产数据0-99
模拟消费者,请写出代码把student主题中的数据0-99消费掉,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_01 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 0);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("student", i+"");
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_01 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("student"));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(consumerRecord.value());
}
}
}
}
习题二:
在kafka集群中创建teacher主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为2
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为默认轮询方式
消费者设置:
消费者组id为test
设置自动提交偏移量
设置自动提交偏移量的时间间隔
设置 当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,从头开始消费
auto.offset.reset
//earliest: 当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,从头开始消费
//latest: 当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,消费新产生的该分区下的数据
//none : topic各分区都存在已提交的offset时,从offset后开始消费;只要有一个分区不存在已提交的offset,则抛出异常
设置key的序列化为org.apache.kafka.common.serialization. StringDeserializer
设置value的序列化为org.apache.kafka.common.serialization. StringDeserializer
模拟生产者,请写出代码向teacher主题中生产数据bigdata0-bigdata99
模拟消费者,请写出代码把teacher主题中的数据bigdata0-bigdata99消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_02 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 2);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("teacher", "bigdata" + i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_02 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("auto.offset.reset","earliest");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("teacher"));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(consumerRecord.value());
}
}
}
}
习题三:
在kafka集群中创建title主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为1
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为指定数据key为title,分发到同一个分区中
消费者设置:
消费者组id为test
设置自动提交偏移量
设置自动提交偏移量的时间间隔
设置 当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,消费新产生的该分区下的数据
设置key的序列化为org.apache.kafka.common.serialization. StringDeserializer
设置value的序列化为org.apache.kafka.common.serialization. StringDeserializer
模拟生产者,请写出代码向title主题中生产数据kafka0-kafka99
模拟消费者,请写出代码把title主题中的数据kafka0-kafka99消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_03 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 1);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("title","title" ,"kafka" + i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_03 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("auto.offset.reset","latest");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("title"));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(consumerRecord.value());
}
}
}
}
习题四:
在kafka集群中创建title主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为2
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为指定分区2,把数据发送到指定的分区中
消费者设置:
消费者组id为test
设置自动提交偏移量
设置自动提交偏移量的时间间隔
设置 topic各分区都存在已提交的offset时,从offset后开始消费;只要有一个分区不存在已提交的offset,则抛出异常
设置key的序列化为org.apache.kafka.common.serialization. StringDeserializer
设置value的序列化为org.apache.kafka.common.serialization. StringDeserializer
模拟生产者,请写出代码向title主题中生产数据test0-test99
模拟消费者,请写出代码把title主题中的数据test0-test99消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_04 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 2);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("title","test" + i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_04 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("auto.offset.reset","none ");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("title"));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(consumerRecord.value());
}
}
}
}
习题五:
在kafka集群中创建order主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为1
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为自定义,请把生产的数据100以内的数据分发到分区0中,100-200以内的数据分发到分区1中,200-300内的数据分发到分区2中
消费者设置:
消费者组id为test
设置自动提交偏移量
设置自动提交偏移量的时间间隔
设置当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,从头开始消费
设置key的序列化为org.apache.kafka.common.serialization. StringDeserializer
设置value的序列化为org.apache.kafka.common.serialization. StringDeserializer
模拟生产者,请写出代码向title主题中生产数据0-299
模拟消费者,请写出代码把title主题中的数据0-299消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_05 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 1);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("partitioner.class","HomeWork.ProducerPartition");
KafkaProducer<String, String> producer = new KafkaProducer<>(props);
for (int i = 0; i < 300; i++) {
ProducerRecord record = new ProducerRecord("order", i + "");
producer.send(record);
}
producer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.util.Arrays;
import java.util.Properties;
public class Consumer05 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("auto.offset.reset","earliest");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Arrays.asList("order"));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println("数据:"+consumerRecord.value()+" 分区:"+consumerRecord.partition());
}
}
}
}
自定义分区代码:
import org.apache.kafka.clients.producer.Partitioner;
import org.apache.kafka.common.Cluster;
import java.util.Map;
public class Partition implements Partitioner {
@Override
public int partition(String s, Object o, byte[] bytes, Object o1, byte[] bytes1, Cluster cluster) {
int a = Integer.parseInt((String) o1);
if (a<=100){
return 0;
}
if (a>100&&a<=200){
return 1;
}
return 2;
}
@Override
public void close() {
}
@Override
public void configure(Map<String, ?> map) {
}
}
习题六:
在kafka集群中创建18BD-10主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为2
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为指定分区2,把数据发送到指定的分区中
消费者设置:
消费者组id为test
设置自动提交偏移量
设置自动提交偏移量的时间间隔
设置 topic各分区都存在已提交的offset时,从offset后开始消费;只要有一个分区不存在已提交的offset,则抛出异常
设置key的反序列化为org.apache.kafka.common.serialization.StringDeserializer
设置value的反序列化为org.apache.kafka.common.serialization.StringDeserializer
消费指定分区2中的数据
模拟生产者,请写出代码向18BD-10主题中生产数据test0-test99
模拟消费者,请写出代码把18BD-10主题中的2号分区的数据消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_06 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 2);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("18BD-10",2,"test", "test"+i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_06 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("auto.offset.reset","latest");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
TopicPartition topicPartition = new TopicPartition("18BD-10", 2);
consumer.assign(Arrays.asList(topicPartition));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(" 自定义分区:"+consumerRecord.partition()+consumerRecord.value());
}
}
}
}
习题七:
在kafka集群中创建18BD-20主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为1
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为轮询方式发送到每个分区中
手动提交每条数据
消费者设置:
消费者组id为test
设置手动提交偏移量
设置key的反序列化为org.apache.kafka.common.serialization.StringDeserializer
设置value的反序列化为org.apache.kafka.common.serialization.StringDeserializer
模拟生产者,请写出代码向18BD-20主题中生产数据test0-test99
模拟消费者,请写出代码把18BD-20主题中的2号分区的数据消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_07 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 1);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("18BD-20", "test"+i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_07 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "false");
props.put("auto.commit.interval.ms", "1000");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
TopicPartition topicPartition = new TopicPartition("18BD-20", 2);
consumer.assign(Arrays.asList(topicPartition));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(" 分区:"+consumerRecord.partition()+" "+consumerRecord.value());
}
consumer.commitAsync();
}
}
}
习题八:
在kafka集群中创建18BD-30主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为1
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为轮询方式发送到每个分区中
消费者设置:
消费者组id为test
设置手动提交偏移量
设置key的反序列化为org.apache.kafka.common.serialization.StringDeserializer
设置value的反序列化为org.apache.kafka.common.serialization.StringDeserializer
依次消费完每个分区之后手动提交offset
模拟生产者,请写出代码向18BD-30主题中生产数据test0-test99
模拟消费者,请写出代码把18BD-30主题中的2号分区的数据消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_08 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 1);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("18BD-30", "test"+i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_08 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "false");
props.put("auto.commit.interval.ms", "1000");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
TopicPartition topicPartition = new TopicPartition("18BD-30", 2);
consumer.assign(Arrays.asList(topicPartition));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(" 分区:"+consumerRecord.partition()+" "+consumerRecord.value());
}
consumer.commitAsync();
}
}
}
习题九:
在kafka集群中创建18BD-40主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为1
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为轮询方式发送到每个分区中
消费者设置:
消费者组id为test
设置自动提交偏移量
设置当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,从头开始消费
设置key的反序列化为org.apache.kafka.common.serialization.StringDeserializer
设置value的反序列化为org.apache.kafka.common.serialization.StringDeserializer
消费指定分区0和分区2中的数据
模拟生产者,请写出代码向18BD-40主题中生产数据test0-test99
模拟消费者,请写出代码把18BD-40主题中的0和2号分区的数据消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_09 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 1);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("18BD-40", "test"+i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_09 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("auto.offset.reset","earliest");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
TopicPartition topicPartition = new TopicPartition("18BD-40", 0);
TopicPartition topicPartition1 = new TopicPartition("18BD-40", 2);
consumer.assign(Arrays.asList(topicPartition,topicPartition1));
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(" 分区:"+consumerRecord.partition()+" "+consumerRecord.value());
}
consumer.commitAsync();
}
}
}
习题十:
在kafka集群中创建18BD-50主题 副本为2个,分区为3个
生产者设置:
消息确认机制 为all
重试次数 为1
批量处理消息字节数 为16384
设置缓冲区大小 为 33554432
设置每条数据生产延迟1ms
设置key的序列化为org.apache.kafka.common.serialization.StringSerializer
设置value的序列化为org.apache.kafka.common.serialization.StringSerializer
数据分发策略为轮询方式发送到每个分区中
消费者设置:
消费者组id为test
设置自动提交偏移量
设置当各分区下有已提交的offset时,从提交的offset开始消费;无提交的offset时,从头开始消费
设置key的反序列化为org.apache.kafka.common.serialization.StringDeserializer
设置value的反序列化为org.apache.kafka.common.serialization.StringDeserializer
消费指定分区0和分区2中的数据,并且设置消费0分区的数据offerset值从0开始,消费2分区的数据offerset值从10开始
模拟生产者,请写出代码向18BD-50主题中生产数据test0-test99
模拟消费者,请写出代码把18BD-50主题中的0和2号分区的数据消费掉 ,打印输出到控制台
生产者答案代码:
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;
public class Producer_10 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("acks", "all");
props.put("retries", 1);
props.put("batch.size", 16384);
props.put("linger.ms", 1);
props.put("buffer.memory", 33554432);
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
KafkaProducer<String, String> kafkaProducer = new KafkaProducer<String, String>
(props);
for (int i = 0; i < 100; i++) {
ProducerRecord record = new ProducerRecord("18BD-50", "test"+i);
kafkaProducer.send(record);
}
kafkaProducer.close();
}
}
消费者答案代码:
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import java.util.Arrays;
import java.util.Properties;
public class Consumer_10 {
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "node01:9092,node02:9092,node03:9092");
props.put("group.id", "test");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("auto.offset.reset","earliest");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
TopicPartition topicPartition0 = new TopicPartition("18BD-50", 0);
TopicPartition topicPartition2 = new TopicPartition("18BD-50", 2);
consumer.assign(Arrays.asList(topicPartition0,topicPartition2));
consumer.seek(topicPartition0,0);
consumer.seek(topicPartition2,10);
while (true){
ConsumerRecords<String, String> consumerRecords = consumer.poll(1000);
for (ConsumerRecord<String, String> consumerRecord : consumerRecords) {
System.out.println(" offset:"+consumerRecord.offset()+" 分区: "+consumerRecord.partition()+" "+consumerRecord.value());
}
}
}
}