kafka指定partiton生产

kafka发送一个消息的时候需要封装成一个ProducerRecord ：

public ProducerRecord(String topic, Integer partition, Long timestamp, K key, V value) {
        if (topic == null)
            throw new IllegalArgumentException("Topic cannot be null");
        if (timestamp != null && timestamp < 0)
            throw new IllegalArgumentException("Invalid timestamp " + timestamp);
        this.topic = topic;
        this.partition = partition;
        this.key = key;
        this.value = value;
        this.timestamp = timestamp;
    }

我们需要关注的是partition和key。

kafka在调用send的时候实际上是将消息放到了内存中，并没有发送出去。在放到内存队列之前，会计算消息应该放到哪个partiton中

private Future<RecordMetadata> doSend(ProducerRecord<K, V> record, Callback callback) {
    // 忽略
    int partition = partition(record, serializedKey, serializedValue, metadata.fetch()); // partiton用来计算书消息具体放置的partiton
    //忽略
    if (result.batchIsFull || result.newBatchCreated) {
                log.trace("Waking up the sender since topic {} partition {} is either full or getting a new batch", record.topic(), partition);
                this.sender.wakeup();
            }
            return result.future;
    // 忽略
}

我们来分析下partiton方法：

private int partition(ProducerRecord<K, V> record, byte[] serializedKey , byte[] serializedValue, Cluster cluster) {
        Integer partition = record.partition(); // ProducerRecord中partiton参数
        if (partition != null) {
            List<PartitionInfo> partitions = cluster.partitionsForTopic(record.topic());
            int lastPartition = partitions.size() - 1;
            // they have given us a partition, use it
            if (partition < 0 || partition > lastPartition) {
                throw new IllegalArgumentException(String.format("Invalid partition given with record: %d is not in the range [0...%d].", partition, lastPartition));
            }
            return partition; // 指定了partiton，则消息发送到该指定的partiton
        }
        // 否则使用partitioner根据ProducerRecord的key参数来计算发送的partiton
        return this.partitioner.partition(record.topic(), record.key(), serializedKey, record.value(), serializedValue,
            cluster);
    }

可以通过在配置中指定“partitioner.class”配置项使用自定义的partitioner，自定义的partitioner需要实现Partitioner接口：

public interface Partitioner extends Configurable {
    /**
     * Compute the partition for the given record.
     *
     * @param topic The topic name
     * @param key The key to partition on (or null if no key)
     * @param keyBytes The serialized key to partition on( or null if no key)
     * @param value The value to partition on or null
     * @param valueBytes The serialized value to partition on or null
     * @param cluster The current cluster metadata
     */
    public int partition(String topic, Object key, byte[] keyBytes, Object value, byte[] valueBytes, Cluster cluster);
    /**
     * This is called when partitioner is closed.
     */
    public void close();
}

如果没有指定“partitioner.class”配置项则使用默认的partitioner：DefaultPartitioner。我们来看下DefaultPartitioner的分配方法

public int partition(String topic, Object key, byte[] keyBytes, Object value, byte[] valueBytes, Cluster cluster) {
        List<PartitionInfo> partitions = cluster.partitionsForTopic(topic); // 获取partiton列表，该列表是更新metadata的时候获取的，默认每30s更新一次metadata
        int numPartitions = partitions.size();
        if (keyBytes == null) { // 如果ProducerRecord没有传入key，则从一个随机数开始，采用round-robin方式
            int nextValue = counter.getAndIncrement(); // counter被初始化为一个随机值，每次递增
            List<PartitionInfo> availablePartitions = cluster.availablePartitionsForTopic(topic);
            if (availablePartitions.size() > 0) {
                int part = DefaultPartitioner.toPositive(nextValue) % availablePartitions.size();
                return availablePartitions.get(part).partition();
            } else {
                // no partitions are available, give a non-available partition
                return DefaultPartitioner.toPositive(nextValue) % numPartitions;
            }
        } else { // 对 keyBytes 进行 hash 选出一个 patition
            // hash the keyBytes to choose a partition
            return DefaultPartitioner.toPositive(Utils.murmur2(keyBytes)) % numPartitions;
        }
    }