kafka学习之-java api测试
1.配置
package com.storm.storm_my.kafka; /** * * @author Peng.Li * */ public class KafkaConfigApiConstant { /** * * @author 配置的key * */ public interface kafkaPropertiesKeys { public static final String ZK_CONNECT = "zookeeper.connect"; public static final String ZK_CONNECTIONTIMEOUT_MS = "zookeeper.connectiontimeout.ms"; public static final String AUTO_COMMIT_INTERVAL_MS = "zookeeper.session.timeout.ms"; public static final String ZK_SESSION_TIMEOUT_MS = "zookeeper.sync.time.ms"; // 自动更新时间。默认60 * 1000 public static final String ZK_SYNC_TIME_MS = "auto.commit.interval.ms"; // 当consumer消费一定量的消息之后,将会自动向zookeeper提交offset信息, // 注意offset信息并不是每消费一次消息就向zk提交一次,而是现在本地保存(内存),并定期提交,默认为true public static final String AUTO_COMMIT_ENABLE = "auto.commit.enable"; public static final String TOPIC = "topic"; public static final String SERIALIZER_CLASS = "serializer.class"; public static final String METADATA_BROKER_LIST = "metadata.broker.list"; public static final String GROUP_ID = "group.id"; public static final String FETCH_MESSAGE_MAX_BYTES = "fetch.message.max.bytes"; // 最大取多少块缓存到消费者 public static final String QUEUED_MAX_MESSAGE_CHUNKS = "queued.max.message.chunks"; public static final String PARTITIONER_CLASS = "partitioner.class"; public static final String FETCH_SIZE = "fetch.size"; /** * 生产者单次最大生产能力 */ public static final String MAX_MESSAGE_SIZE = "max.message.size"; } /** * * @author 配置的value * */ public interface KafkaPropertiesValues { // 1.zk的信息 public final static String ZK_CONNECT = "192.168.14.100:2181,192.168.14.105:2181,192.168.14.102:2181"; public final static int ZK_CONNECTIONTIMEOUT_MS = 6000; public final static int ZK_SESSION_TIMEOUT_MS = 6000; public final static int ZK_SYNC_TIME_MS = 6000; public final static int AUTO_COMMIT_INTERVAL_MS = 1000; public final static boolean AUTO_COMMIT_ENABLE = true; // 2.公用的配置 public final static String TOPIC = "lp_topic"; public final static String GROUP_ID = "lp_group1"; // 3. kafka consumer config public static final int FETCH_MESSAGE_MAX_BYTES = 2 * 1024; public static final int FETCH_SIZE = 2 * 1024; // ?? public final static int QUEUED_MAX_MESSAGE_CHUNKS = 10; // 4.kafka prducer public final static String METADATA_BROKER_LIST = "192.168.14.100:9092,192.168.14.105:9092,192.168.14.102:9092"; public final static String PARTITIONER_CLASS = "kafka.producer.DefaultPartitioner"; public static final String SERIALIZER_CLASS = "kafka.serializer.StringEncoder"; public static final int MAX_MESSAGE_SIZE = 1024 * 1024; } }
2.kafka cusumer
package com.storm.storm_my.kafka; 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; import com.storm.storm_my.kafka.KafkaConfigApiConstant.KafkaPropertiesValues; import com.storm.storm_my.kafka.KafkaConfigApiConstant.kafkaPropertiesKeys; /** * * @author Peng.Li * */ public class KafkaConsumer implements Runnable { private ConsumerConnector consumer; private String topic; /** * * @param topic */ public KafkaConsumer(String topic) { consumer = Consumer.createJavaConsumerConnector(this.newConsumerConfig()); this.topic = topic; } /** * * @return 配置 */ public ConsumerConfig newConsumerConfig() { Properties props = new Properties(); props.put(kafkaPropertiesKeys.ZK_CONNECT, KafkaPropertiesValues.ZK_CONNECT); props.put(kafkaPropertiesKeys.ZK_CONNECTIONTIMEOUT_MS, String.valueOf(KafkaPropertiesValues.ZK_CONNECTIONTIMEOUT_MS)); props.put(kafkaPropertiesKeys.ZK_SESSION_TIMEOUT_MS, String.valueOf(KafkaPropertiesValues.ZK_SESSION_TIMEOUT_MS)); props.put(kafkaPropertiesKeys.ZK_SYNC_TIME_MS, String.valueOf(KafkaPropertiesValues.ZK_SYNC_TIME_MS)); props.put(kafkaPropertiesKeys.AUTO_COMMIT_ENABLE, String.valueOf(KafkaPropertiesValues.AUTO_COMMIT_ENABLE)); props.put(kafkaPropertiesKeys.TOPIC, KafkaPropertiesValues.TOPIC); props.put(kafkaPropertiesKeys.GROUP_ID, KafkaPropertiesValues.GROUP_ID); props.put(kafkaPropertiesKeys.FETCH_MESSAGE_MAX_BYTES, String.valueOf(KafkaPropertiesValues.FETCH_MESSAGE_MAX_BYTES)); props.put(kafkaPropertiesKeys.QUEUED_MAX_MESSAGE_CHUNKS, String.valueOf(KafkaPropertiesValues.QUEUED_MAX_MESSAGE_CHUNKS)); props.put(kafkaPropertiesKeys.FETCH_SIZE, String.valueOf(KafkaPropertiesValues.FETCH_SIZE)); return new ConsumerConfig(props); } @Override public void run() { Map<String, Integer> topicMap = new HashMap<String, Integer>(); topicMap.put(topic, new Integer(1)); Map<String, List<KafkaStream<byte[], byte[]>>> topicOutPutStreamMap = consumer.createMessageStreams(topicMap); KafkaStream<byte[], byte[]> topicStream = topicOutPutStreamMap.get(topic).get(0); ConsumerIterator<byte[], byte[]> steamIt = topicStream.iterator(); while (steamIt.hasNext()) { try { System.out.println("Recieve -> [" + new String(steamIt.next().message(), "UTF-8") + "]"); try { Thread.sleep(1000 * 3); } catch (InterruptedException e) { // TODO Auto-generated catch block e.printStackTrace(); } } catch (Exception e) { // TODO Auto-generated catch block e.printStackTrace(); } } } }
3.kafka producer
package com.storm.storm_my.kafka; import java.util.Properties; import com.storm.storm_my.kafka.KafkaConfigApiConstant.KafkaPropertiesValues; import com.storm.storm_my.kafka.KafkaConfigApiConstant.kafkaPropertiesKeys; import kafka.javaapi.producer.Producer; import kafka.producer.KeyedMessage; import kafka.producer.ProducerConfig; /** * * @author Peng.Li * */ public class KafaProducer implements Runnable { private String topic; private Producer<String, String> producer; /** * * @param topic */ public KafaProducer(String topic) { this.topic = topic; producer = new Producer<String, String>(this.newProducerConfig()); } /** * 构建生产者需要的配置 * @return */ public ProducerConfig newProducerConfig() { Properties producerProperties = new Properties(); // zk producerProperties.put(kafkaPropertiesKeys.ZK_CONNECT, KafkaPropertiesValues.ZK_CONNECT); producerProperties.put(kafkaPropertiesKeys.ZK_CONNECTIONTIMEOUT_MS, String.valueOf(KafkaPropertiesValues.ZK_CONNECTIONTIMEOUT_MS)); producerProperties.put(kafkaPropertiesKeys.ZK_SESSION_TIMEOUT_MS, String.valueOf(KafkaPropertiesValues.ZK_SESSION_TIMEOUT_MS)); producerProperties.put(kafkaPropertiesKeys.ZK_SYNC_TIME_MS, String.valueOf(KafkaPropertiesValues.ZK_SYNC_TIME_MS)); producerProperties.put(kafkaPropertiesKeys.AUTO_COMMIT_ENABLE, String.valueOf(KafkaPropertiesValues.AUTO_COMMIT_ENABLE)); producerProperties.put(kafkaPropertiesKeys.TOPIC, KafkaPropertiesValues.TOPIC); // producer producerProperties.put(kafkaPropertiesKeys.SERIALIZER_CLASS, KafkaPropertiesValues.SERIALIZER_CLASS); producerProperties.put(kafkaPropertiesKeys.METADATA_BROKER_LIST, KafkaPropertiesValues.METADATA_BROKER_LIST); producerProperties.put(kafkaPropertiesKeys.PARTITIONER_CLASS, KafkaPropertiesValues.PARTITIONER_CLASS); producerProperties.put(kafkaPropertiesKeys.MAX_MESSAGE_SIZE, String.valueOf(KafkaPropertiesValues.MAX_MESSAGE_SIZE)); return new ProducerConfig(producerProperties); } @Override public void run() { int offsetNo = 1; while (true) { String msg = new String("Message_" + offsetNo); System.out.println("Send->[" + msg + "]"); producer.send(new KeyedMessage<String, String>(topic, msg)); offsetNo++; try { Thread.sleep(1000 * 3); } catch (InterruptedException e) { // TODO Auto-generated catch block e.printStackTrace(); } } } }
4. consumer Client
package com.storm.storm_my.kafka.client; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import com.storm.storm_my.kafka.KafkaConfigApiConstant; import com.storm.storm_my.kafka.KafkaConsumer; /** * * @author user * */ public class KafkaConsumerClient { public static void main(String[] args) { KafkaConsumer consumerRunnable = new KafkaConsumer(KafkaConfigApiConstant.KafkaPropertiesValues.TOPIC); ExecutorService executorService = Executors.newCachedThreadPool(); executorService.execute(consumerRunnable); } }
5.kafka producer Client
package com.storm.storm_my.kafka.client; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import com.storm.storm_my.kafka.KafaProducer; import com.storm.storm_my.kafka.KafkaConfigApiConstant; /** * * @author Peng.Li * */ public class KafkaProducerClient { public static void main(String[] args) { KafaProducer producerRunnble = new KafaProducer(KafkaConfigApiConstant.KafkaPropertiesValues.TOPIC); ExecutorService executorService = Executors.newCachedThreadPool(); executorService.execute(producerRunnble); } }
结果:
Face your past without regret. Handle your present with confidence.Prepare for future without fear. keep the faith and drop the fear.
面对过去无怨无悔,把握现在充满信心,备战未来无所畏惧。保持信念,克服恐惧!一点一滴的积累,一点一滴的沉淀,学技术需要不断的积淀!