Java 自定义方法 - KAFKA:修订间差异
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props 配置变化,需要 new consumer。 | props 配置变化,需要 new consumer。 | ||
当 N 较大时,需要设置 fetch.max.bytes(默认值 52428800,单位 byte,下同),该参数与 fetch.min.bytes(默认值 1)参数对应,用来配置 Consumer 在一次请求中从 Kafka | 当 N 较大时,需要设置 fetch.max.bytes(默认值 52428800,单位 byte,下同),该参数与 fetch.min.bytes(默认值 1)参数对应,用来配置 Consumer 在一次请求中从 Kafka 中拉取的多批总数据量大小。若一批次的数据大于该值,仍然可以拉取。 | ||
==== 获取消费记录 ==== | ==== 获取消费记录 ==== |
2024年3月8日 (五) 09:33的版本
Java 自定义函数 - KAFKA
Producer
producer 是线程安全的。
Producer<String, String> producer
集群同步规则
ack 配置项用来控制 producer 要求 leader 确认多少消息后返回调用成功
- 0 不需要等待任何确认消息
- 1 需要等待leader确认
- -1或all 需要全部 ISR 集合返回确认,默认值
ack=-1 # 默认需要全部 ISR 集合返回确认
缓冲区
缓冲一批数据发送或超过延时时间(linger.ms=0)发送,默认 16k。
batch.size=1048576 # 1M linger.ms=10 # 10ms
消息重发
消息发送错误时设置的系统重发消息次数(retries=2147483647)、重发间隔(retry.backoff.ms=100)。若保证消息的有序性,设置 max_in_flight_requests_per_connection=1。
max_in_flight_requests_per_connection=1 retries=10 retry.backoff.ms=200
压缩方式
发送的所有数据的压缩方式:none(默认), gzip, snappy, lz4, zstd。
compression.type=gzip
消息分区策略
消息键保序(key-ordering )策略:Kafka 中每条消息都可以定义 Key,同一个 Key 的所有消息都进入到相同的分区中。否则采用轮询(Round-robin)、随机策略(Randomness)等策略。
producer.send(new ProducerRecord<String, String>(TOPIC, key, val) -.OR.- producer.send(new ProducerRecord<String, String>(TOPIC, val)
其他
enable.idempotence=true # 默认开启幂等性 bootstrap.servers=node1:9092,node2:9092,... # 并非需要所有的broker地址,生产者可以从给定的 broker 里查找到其他 broker 信息
Consumer
设置每次消费最大记录数
默认值为 500 条。
Properties props = new Properties(); props.put("max.poll.records", N); ... consumer = new KafkaConsumer(props);
props 配置变化,需要 new consumer。
当 N 较大时,需要设置 fetch.max.bytes(默认值 52428800,单位 byte,下同),该参数与 fetch.min.bytes(默认值 1)参数对应,用来配置 Consumer 在一次请求中从 Kafka 中拉取的多批总数据量大小。若一批次的数据大于该值,仍然可以拉取。
获取消费记录
直到取到 max.poll.records 条记录或超过指定时长(如下面语句为 1000 毫秒)。
KafkaConsumer<String, String> consumer; consumer.poll(Duration.ofMillis(1000));
Sample
No | Method | Explain | Example |
---|---|---|---|
KAFKA | 定义 kafka,默认从 db.cnf 中取 default | KAFKA k1 = new KAFKA("kafkap182", "test", "test", "db.cnf") | |
1 | consumer | 改变消费模式 | k1.consumer("test", "test", N) # 从N开始消费 |
2 | get | 获取记录 | k1.get(9) # 指定条数
k1.get() # 默认条数,1000 |
3 | getos | begin, end, offset | k1.getos() # [0, 16, 8] |
4 | put | 生产记录 | k1.put("test", ldat1) # ArrayList<String> ldat1 |
package com.udf.base; /* ------------------------------------------------------------------------------ Name : Udf.base.KAFKA Purpose : Kafka product & consumer Author : Adam Revisions: Ver Date Author Description --------- ---------- --------------- ------------------------------------ 1.0 2024/3/5 Adam Create. format: property: consumer method : get, put <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-clients</artifactId> <version>2.0.0</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka_2.11</artifactId> <version>0.10.0.1</version> </dependency> <dependency> <groupId>org.apache.kafka</groupId> <artifactId>kafka-streams</artifactId> <version>1.0.0</version> </dependency> ------------------------------------------------------------------------------ */ import org.apache.kafka.clients.admin.AdminClient; import org.apache.kafka.clients.admin.KafkaAdminClient; 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.clients.consumer.OffsetAndMetadata; import org.apache.kafka.clients.producer.KafkaProducer; import org.apache.kafka.clients.producer.Producer; import org.apache.kafka.clients.producer.ProducerRecord; import org.apache.kafka.common.PartitionInfo; import org.apache.kafka.common.TopicPartition; import org.apache.kafka.common.serialization.StringDeserializer; import org.apache.kafka.common.serialization.StringSerializer; import org.apache.log4j.Logger; import java.time.Duration; import java.util.*; public class KAFKA extends BASE { public static final String VERSION = "v1.0"; public static Producer<String, String> producer; public static KafkaConsumer<String, String> consumer; public static ConsumerRecords<String, String> cr; // set stream public static ArrayList<String> topics = new ArrayList<>(); // topic list public static HashMap<Long, ArrayList<String>> val = new HashMap<>(); // set result, [offset, value] public static String jval = ""; // json set result public static int cs = 0; // rows count public static boolean status = false; // MQ connect status public static int PullMS = 1000; // default pull max 1000 millisecond public static int MaxRows = 1000; private static String sServ, sTopic, sGroup; private static final Properties props = new Properties(); private static final Logger logger = Logger.getLogger(KAFKA.class); public KAFKA(String mqname1, String topic1, String group1, String mq1) { // get db jdbc info CNF cnf1 = new CNF(mq1); sServ = cnf1.get(mqname1); // s1:9092,s2:9092,... sTopic = topic1; sGroup = group1; props.put("bootstrap.servers", sServ); AdminClient client = KafkaAdminClient.create(props); // get topic list Set topics1 = null; try { topics1 = client.listTopics().names().get(); } catch (Exception e) { logger.error(e); } topics = new ArrayList<>(topics1); init(); } public KAFKA(String mqname1) { this(mqname1, "test", "test", "db.cnf"); } public static void init() { props.put("bootstrap.servers", sServ); props.put("group.id", sGroup); // producer props.put("key.serializer", StringSerializer.class.getName()); props.put("value.serializer", StringSerializer.class.getName()); props.put("acks", "all"); props.put("retries", 0); props.put("batch.size", 16384); props.put("linger.ms", 1); props.put("buffer.memory", 33554432); //consumer props.put("key.deserializer", StringDeserializer.class.getName()); props.put("value.deserializer", StringDeserializer.class.getName()); props.put("enable.auto.commit", "true"); props.put("auto.commit.interval.ms", "1000"); props.put("session.timeout.ms", "30000"); props.put("auto.offset.reset", "earliest"); props.put("max.poll.records", MaxRows); } public static void consumer(String topic1, String group1, long offset1) { sTopic = topic1; sGroup = group1; _consumer(topic1, group1, 1); reset(offset1); } public static void consumer(String topic1, String group1) { sTopic = topic1; sGroup = group1; _consumer(topic1, group1, MaxRows); } public static void get(int rows) { if (rows < 1) return; _consumer(sTopic, sGroup, rows); _get(); } public static void get() { _consumer(sTopic, sGroup, MaxRows); _get(); } public static ArrayList getos() { //consumer(sTopic, sGroup); long osb = 0; // beginOffsets long ose = 0; // endOffsets long osc = 0; // currentOffsets ArrayList los1 = new ArrayList(); Map<Integer, Long> beginOffsetMap = new HashMap<Integer, Long>(); Map<Integer, Long> endOffsetMap = new HashMap<Integer, Long>(); Map<Integer, Long> commitOffsetMap = new HashMap<Integer, Long>(); List<TopicPartition> topicPartitions = new ArrayList<TopicPartition>(); List<PartitionInfo> partitionsFor; try { partitionsFor = consumer.partitionsFor(sTopic); } catch (Exception e) { consumer(sTopic, sGroup);; partitionsFor = consumer.partitionsFor(sTopic); } for (PartitionInfo partitionInfo : partitionsFor) { TopicPartition topicPartition = new TopicPartition(partitionInfo.topic(), partitionInfo.partition()); topicPartitions.add(topicPartition); } // beginOffsetMap Map<TopicPartition, Long> beginOffsets = consumer.beginningOffsets(topicPartitions); for (TopicPartition partitionInfo : beginOffsets.keySet()) { beginOffsetMap.put(partitionInfo.partition(), beginOffsets.get(partitionInfo)); } // for (Integer partitionId : beginOffsetMap.keySet()) { // logger.info(String.format("topic:%s, partition:%s, logSize:%s", sTopic, partitionId, beginOffsetMap.get(partitionId))); // } // endOffsetMap Map<TopicPartition, Long> endOffsets = consumer.endOffsets(topicPartitions); for (TopicPartition partitionInfo : endOffsets.keySet()) { endOffsetMap.put(partitionInfo.partition(), endOffsets.get(partitionInfo)); } // for (Integer partitionId : endOffsetMap.keySet()) { // logger.info(String.format("topic:%s, partition:%s, logSize:%s", sTopic, partitionId, endOffsetMap.get(partitionId))); // } //commitOffsetMap for (TopicPartition topicAndPartition : topicPartitions) { OffsetAndMetadata committed = consumer.committed(topicAndPartition); commitOffsetMap.put(topicAndPartition.partition(), committed.offset()); } //sum lag long lagSum = 0; osb = 9999999999999999l; ose = 0; if (endOffsetMap.size() == commitOffsetMap.size()) { for (Integer partition : endOffsetMap.keySet()) { long beginOffSet = beginOffsetMap.get(partition); long endOffSet = endOffsetMap.get(partition); long commitOffSet = commitOffsetMap.get(partition); long diffOffset = endOffSet - commitOffSet; lagSum += diffOffset; osb = Math.min(osb, beginOffSet); ose = Math.max(ose, endOffSet); osc = Math.max(osc, commitOffSet); // logger.info("Topic:" + sTopic + ", groupID:" + sGroup + ", partition:" + partition + ", beginOffSet:" + beginOffSet + ", endOffset:" + endOffSet + ", commitOffset:" + commitOffSet + ", diffOffset:" + diffOffset); } // logger.info("Topic:" + sTopic + ", groupID:" + sGroup + ", LAG:" + lagSum); } else { logger.error("this topic partitions lost."); } los1.addAll(Arrays.asList(osb, ose, osc)); return los1; } // !!!! traversed all the records, consumer needs to be closed. // .consumer.close() public static void getStream(int rows) { if (rows < 1) return; _consumer(sTopic, sGroup, rows); cr = consumer.poll(Duration.ofMillis(PullMS)); cs = cr.count(); logger.info("Get records: " + cs); } public static void put(String topic1, ArrayList<String> dat1) { producer = new KafkaProducer<>(props); for (String s : dat1) { producer.send(new ProducerRecord<String, String>(topic1, s)); } producer.close(); logger.info(String.format("Producer %s records successed.", dat1.size())); } protected static void _consumer(String topic1, String group1, int records1) { // Consumer properties sTopic = topic1; sGroup = group1; // Create consumer if (status) { consumer.close(); status = false; } props.put("max.poll.records", records1); consumer = new KafkaConsumer(props); // Subscribe to topic consumer.subscribe(Arrays.asList(sTopic)); status = true; } protected static void _get() { long i; cr = consumer.poll(Duration.ofMillis(PullMS)); cs = cr.count(); logger.info("Get records: " + cs); i = 0; ArrayList lrs1; for (ConsumerRecord<String, String> record : cr) { lrs1 = new ArrayList(); lrs1.add(record.offset()); lrs1.add(record.value()); // lrs1.add(record.key()); // lrs1.add(record.timestamp()); val.put(i++, lrs1); } consumer.close(); status = false; jval = json.toJson(val); } private static void reset(long offset1) { Set<TopicPartition> assignment1 = new HashSet<>(); while (assignment1.size() == 0) { consumer.poll(Duration.ofMillis(100)); assignment1 = consumer.assignment(); } logger.info("Partition Assignment: " + assignment1); Map<TopicPartition, Long> beginOffsets = consumer.beginningOffsets(assignment1); Map<TopicPartition, Long> endOffsets = consumer.endOffsets(assignment1); for (TopicPartition tp : assignment1) { if (offset1 < 0) { offset1 = Math.max(beginOffsets.get(tp), endOffsets.get(tp) + offset1 + 1); } else { offset1 = Math.max(offset1, beginOffsets.get(tp)); offset1 = Math.min(offset1, endOffsets.get(tp)); } logger.info(beginOffsets.get(tp)); logger.info(endOffsets.get(tp)); logger.info("Reset Partition " + tp + " from " + offset1 + " offset consumer."); consumer.seek(tp, offset1); } consumer.close(); status = false; } }