go - Kafka 生产者意外行为

Question

我的 Kafka 生产者和消费者遇到了一种奇怪的行为。以下是我在本地机器上的设置

• 1 个 ZooKeeper 节点
• 2个kafka代理节点
• 1 个生产者（进行异步写入）和 1 个订阅者使用这个库编写

我正在使用 kafka 的命令行工具创建一个主题，如下所示

./kafka-topics.sh --zookeeper localhost:2181 --create --topic foo --partitions 1 --replication-factor 2 --config min.insync.replicas=2

问题是，每当我杀死分区的领导节点时，即使min.insync.replicas我的主题设置为 2，生产者和消费者仍然会继续从 kafka 集群推送和拉取消息。我希望生产者抛出异常并且不允许分区根据文档编写。

我发现了一个与我类似的线程，其中建议为每个主题设置 min.insync.replicas 我已经完成但仍然没有关于生产者的错误

我在某处做错了吗？

生产者代码（golang）

func main() {
    kafkaProducer, kafkaConErr = kafka.NewProducer( & kafka.ConfigMap {
        "bootstrap.servers": "localhost:9092",
        "acks": "-1"
    })
    if kafkaConErr != nil {
        fmt.Println("Error creating InfluxDB Client: ", kafkaConErr.Error())
    }
    defer kafkaProducer.Close()

    topic: = "foo"
        /* for range []string{"Welcome", "to", "the", "Confluent", "Kafka", "Golang", "client"} { */
    perr: = kafkaProducer.Produce( & kafka.Message {
        TopicPartition: kafka.TopicPartition {
            Topic: & topic,
            Partition: kafka.PartitionAny
        },
        Value: empData,
    }, nil)
    if perr != nil {
        fmt.Println(err.Error())
        return
    }
    deliveryReportHandler()

}

func deliveryReportHandler() {
    // Delivery report handler for produced messages
    go func() {
        for e: = range kafkaProducer.Events() {
            switch ev: = e.(type) {
                case *kafka.Message:
                    if ev.TopicPartition.Error != nil {
                        fmt.Printf("Delivery failed: %v\n", ev.TopicPartition)
                    } else {
                        fmt.Printf("Delivered message to topic %s [%d] at offset %v\n", * ev.TopicPartition.Topic, ev.TopicPartition.Partition, ev.TopicPartition.Offset)
                    }
                default:
                    fmt.Printf("Ignored event: %s\n", ev)
            }
        }
    }()
}

我的经纪人配置如下

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0

############################# Socket Server Settings #############################

# The address the socket server listens on. It will get the value returned from 
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = listener_name://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
listeners=PLAINTEXT://:9092

# Hostname and port the broker will advertise to producers and consumers. If not set, 
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092

# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL

# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400

# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600


############################# Log Basics #############################

# A comma separated list of directories under which to store log files
log.dirs=/tmp/kafka-logs

# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1

# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1

############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3.
#offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1

############################# Log Flush Policy #############################

# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
#    1. Durability: Unflushed data may be lost if you are not using replication.
#    2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
#    3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.

# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000

# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000

############################# Log Retention Policy #############################

# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.

# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168

# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#log.retention.bytes=1073741824

# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824

# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000

############################# Zookeeper #############################

# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=localhost:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000


############################# Group Coordinator Settings #############################

# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0

auto.leader.rebalance.enable=true

leader.imbalance.check.interval.seconds=5

leader.imbalance.per.broker.percentage=0

min.insync.replicas=2

offsets.topic.replication.factor=2

replica.lag.time.max.ms=1000

更新- 在 github repo链接中提交了一个问题

标签： goapache-kafkaconfluent-platform