【发布时间】：2018-09-04 17:20:20
【问题描述】：
早上好。 首先，我创建了一个带有 2 个物理主机和一个覆盖网络的 docker swarm。在同一台主机上，我创建了 2 个容器（postgres 和 ambari 服务器）和一个带有 ambari 代理的容器，我将在其中安装来自 ambari 的 kafka、zookeeper、spark……。范围是在多个主机中安装多个容器，但我首先尝试这样，因为我没有让它工作。
事实是，一旦使用 Ambari 部署，我将 kafka 配置更改为将advertised.host.name 添加到物理主机的 ip 并将advertised.port 添加到 9092 以将其绑定到物理主机的 9092 端口。
在尝试时，我总是收到以下错误：
WARN Error while fetching metadata with correlation id 17 : {prueba2=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
如果尝试发送到容器的 6667 端口 或
[2018-08-30 12:06:28,758] WARN Bootstrap broker 192.168.0.28:9092 disconnected (org.apache.kafka.clients.NetworkClient)
如果尝试物理主机的端口 9092。
感谢您的帮助，请询问帮助解决此问题所需的任何进一步信息。
编辑1：
并且 kafka-broker 没有运行。 server.log 显示以下跟踪：
root@host1:/usr/hdp/2.6.3.0-235/kafka# cat /var/log/kafka/server.log
[2018-09-04 09:17:46,964] INFO KafkaConfig values:
advertised.host.name = host1.ambari
advertised.listeners = INTERNO://host1.ambari:6667,EXTERNO://192.168.0.28:9092
advertised.port = 9092
authorizer.class.name =
auto.create.topics.enable = true
auto.leader.rebalance.enable = true
background.threads = 10
broker.id = -1
broker.id.generation.enable = true
broker.rack = null
compression.type = producer
connections.max.idle.ms = 600000
controlled.shutdown.enable = true
controlled.shutdown.max.retries = 3
controlled.shutdown.retry.backoff.ms = 5000
controller.socket.timeout.ms = 30000
default.replication.factor = 1
delete.topic.enable = false
fetch.purgatory.purge.interval.requests = 10000
group.max.session.timeout.ms = 300000
group.min.session.timeout.ms = 6000
host.name =
inter.broker.protocol.version = 0.10.1-IV2
leader.imbalance.check.interval.seconds = 300
leader.imbalance.per.broker.percentage = 10
listeners = INTERNO://host1.ambari:6667,EXTERNO://host1.ambari:6667
log.cleaner.backoff.ms = 15000
log.cleaner.dedupe.buffer.size = 134217728
log.cleaner.delete.retention.ms = 86400000
log.cleaner.enable = true
log.cleaner.io.buffer.load.factor = 0.9
log.cleaner.io.buffer.size = 524288
log.cleaner.io.max.bytes.per.second = 1.7976931348623157E308
log.cleaner.min.cleanable.ratio = 0.5
log.cleaner.min.compaction.lag.ms = 0
log.cleaner.threads = 1
log.cleanup.policy = [delete]
log.dir = /tmp/kafka-logs
log.dirs = /kafka-logs
log.flush.interval.messages = 9223372036854775807
log.flush.interval.ms = null
log.flush.offset.checkpoint.interval.ms = 60000
log.flush.scheduler.interval.ms = 9223372036854775807
log.index.interval.bytes = 4096
log.index.size.max.bytes = 10485760
log.message.format.version = 0.10.1-IV2
log.message.timestamp.difference.max.ms = 9223372036854775807
log.message.timestamp.type = CreateTime
log.preallocate = false
log.retention.bytes = -1
log.retention.check.interval.ms = 300000
log.retention.hours = 168
log.retention.minutes = null
log.retention.ms = null
log.roll.hours = 168
log.roll.jitter.hours = 0
log.roll.jitter.ms = null
log.roll.ms = null
log.segment.bytes = 1073741824
log.segment.delete.delay.ms = 60000
max.connections.per.ip = 2147483647
max.connections.per.ip.overrides =
message.max.bytes = 1000000
metric.reporters = []
metrics.num.samples = 2
metrics.sample.window.ms = 30000
min.insync.replicas = 1
num.io.threads = 8
num.network.threads = 3
num.partitions = 1
num.recovery.threads.per.data.dir = 1
num.replica.fetchers = 1
offset.metadata.max.bytes = 4096
offsets.commit.required.acks = -1
offsets.commit.timeout.ms = 5000
offsets.load.buffer.size = 5242880
offsets.retention.check.interval.ms = 600000
offsets.retention.minutes = 86400000
offsets.topic.compression.codec = 0
offsets.topic.num.partitions = 50
offsets.topic.replication.factor = 3
offsets.topic.segment.bytes = 104857600
port = 6667
principal.builder.class = class org.apache.kafka.common.security.auth.DefaultPrincipalBuilder
producer.purgatory.purge.interval.requests = 10000
queued.max.requests = 500
quota.consumer.default = 9223372036854775807
quota.producer.default = 9223372036854775807
quota.window.num = 11
quota.window.size.seconds = 1
replica.fetch.backoff.ms = 1000
replica.fetch.max.bytes = 1048576
replica.fetch.min.bytes = 1
replica.fetch.response.max.bytes = 10485760
replica.fetch.wait.max.ms = 500
replica.high.watermark.checkpoint.interval.ms = 5000
replica.lag.time.max.ms = 10000
replica.socket.receive.buffer.bytes = 65536
replica.socket.timeout.ms = 30000
replication.quota.window.num = 11
replication.quota.window.size.seconds = 1
request.timeout.ms = 30000
reserved.broker.max.id = 1000
sasl.enabled.mechanisms = [GSSAPI]
sasl.kerberos.kinit.cmd = /usr/bin/kinit
sasl.kerberos.min.time.before.relogin = 60000
sasl.kerberos.principal.to.local.rules = [DEFAULT]
sasl.kerberos.service.name = null
sasl.kerberos.ticket.renew.jitter = 0.05
sasl.kerberos.ticket.renew.window.factor = 0.8
sasl.mechanism.inter.broker.protocol = GSSAPI
security.inter.broker.protocol = PLAINTEXT
socket.receive.buffer.bytes = 102400
socket.request.max.bytes = 104857600
socket.send.buffer.bytes = 102400
ssl.cipher.suites = null
ssl.client.auth = none
ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
ssl.endpoint.identification.algorithm = null
ssl.key.password = null
ssl.keymanager.algorithm = SunX509
ssl.keystore.location = null
ssl.keystore.password = null
ssl.keystore.type = JKS
ssl.protocol = TLS
ssl.provider = null
ssl.secure.random.implementation = null
ssl.trustmanager.algorithm = PKIX
ssl.truststore.location = null
ssl.truststore.password = null
ssl.truststore.type = JKS
unclean.leader.election.enable = true
zookeeper.connect = host1.ambari:2181
zookeeper.connection.timeout.ms = 25000
zookeeper.session.timeout.ms = 30000
zookeeper.set.acl = false
zookeeper.sync.time.ms = 2000
(kafka.server.KafkaConfig)
[2018-09-04 09:17:46,974] FATAL (kafka.Kafka$)
java.lang.IllegalArgumentException: Error creating broker listeners from 'INTERNO://host1.ambari:6667,EXTERNO://host1.ambari:6667': No enum constant org.apache.kafka.common.protocol.SecurityProtocol.INTERNO
at kafka.server.KafkaConfig.validateUniquePortAndProtocol(KafkaConfig.scala:994)
at kafka.server.KafkaConfig.getListeners(KafkaConfig.scala:1013)
at kafka.server.KafkaConfig.<init>(KafkaConfig.scala:966)
at kafka.server.KafkaConfig$.fromProps(KafkaConfig.scala:779)
at kafka.server.KafkaConfig$.fromProps(KafkaConfig.scala:776)
at kafka.server.KafkaServerStartable$.fromProps(KafkaServerStartable.scala:28)
at kafka.Kafka$.main(Kafka.scala:58)
at kafka.Kafka.main(Kafka.scala)
【问题讨论】：
-
您能否解释一下您的 Kafka 和 Zookeeper 属性？此外，如果它是 docker，您还必须公开这些端口，而不仅仅是设置配置文件......另外，当有其他 Docker GUI 可以更好地管理容器时，我不确定我是否理解 Ambari 的目的
-
现在使用 Robin 的回答信息进行了更新。我们在没有 Docker 的情况下使用 ambari，因此尝试通过使用 docker 容器作为 ambari 主机来使其相似。欢迎任何其他想法。
-
好吧，docker 和 Ambari 的主要问题是您需要将配置文件目录直接挂载到主机上，从而使容器有状态并绑定到机器。远程在容器中安装服务也需要 SSH，这通常是 Docker 的一种反模式，所以它确实比它的价值更麻烦......但无论如何，
broker.id = -1......这必须是一个非负值 -
如果你真的想要 Hadoop 上的 Docker 服务，你可以升级到 HDP 3.x，并直接作为 YARN 服务运行它们，但是 Ambari 代理应该仍然在机器的基础操作系统上
标签： docker apache-kafka docker-compose apache-zookeeper