Apache kafka Can';t通过java代码从windows连接到远程卡夫卡制作者
我试图测试我的卡夫卡制作者代码,从windows eclipse到远程卡夫卡制作者(在AWS云中运行),但我在下面遇到了错误,我附加了我的代码和错误,我搜索了很多,但仍然不起作用Apache kafka Can';t通过java代码从windows连接到远程卡夫卡制作者,apache-kafka,Apache Kafka,我试图测试我的卡夫卡制作者代码,从windows eclipse到远程卡夫卡制作者(在AWS云中运行),但我在下面遇到了错误,我附加了我的代码和错误,我搜索了很多,但仍然不起作用 public static void main(String[] args) { Properties props = new Properties(); props.put("metadata.broker.list", "52.74.109.118:9092"); props.put("
public static void main(String[] args) {
Properties props = new Properties();
props.put("metadata.broker.list", "52.74.109.118:9092");
props.put("serializer.class", "kafka.serializer.StringEncoder");
props.put("advertised.host.name", "kafka");
// props.put("serializer.class",
// com.funspot.utils.SerializerUtils.class);
props.put("request.required.acks", "1");
ProducerConfig config = new ProducerConfig(props);
Producer<String, String> kafkaProducer = new Producer<String, String>(
config);
String msg = "hai";
KeyedMessage<String, String> keyedMessage = new KeyedMessage<String, String>(
"messaging.sms", msg);
System.out.println(msg);
kafkaProducer.send(keyedMessage);
System.out.println("message sent");
}
Server.properties
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# see kafka.server.KafkaConfig for additional details and defaults
############################# 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 port the socket server listens on
port=9092
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=kafka
# Hostname the broker will advertise to producers and consumers. If not set, it uses the
# value for "host.name" if configured. Otherwise, it will use the value returned from
# java.net.InetAddress.getCanonicalHostName().
# advertised.host.name=<>
# The port to publish to ZooKeeper for clients to use. If this is not set,
# it will publish the same port that the broker binds to.
# advertised.port=<>
# The number of threads handling network requests
num.network.threads=3
# The number of threads doing 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 seperated list of directories under which to store log files
log.dirs=/home/ubuntu/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
############################# 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 exceessive 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
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes.
#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
# By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires.
# If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction.
log.cleaner.enable=false
############################# 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=zookeeper:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
<代码>被授予Apache软件基金会(ASF)以下一个或多个
#贡献者许可协议。请参阅随附的通知文件
#本作品提供了有关版权所有权的更多信息。
#ASF根据Apache许可证2.0版将此文件许可给您
#(以下简称“许可证”);除非符合以下要求,否则不得使用此文件
#执照。您可以通过以下方式获得许可证副本:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#除非适用法律要求或书面同意,软件
#根据许可证进行的分发是按“原样”进行分发的,
#无任何明示或暗示的保证或条件。
#请参阅许可证以了解管理权限和权限的特定语言
#许可证下的限制。
#有关更多详细信息和默认值,请参见kafka.server.kafkanconfig
#############################服务器基础#############################
#代理的id。对于每个代理,必须将其设置为唯一的整数。
broker.id=0
#############################套接字服务器设置#############################
#套接字服务器侦听的端口
端口=9092
#代理将绑定到的主机名。如果未设置,服务器将绑定到所有接口
host.name=kafka
#代理将向生产者和消费者公布主机名。如果未设置,则使用
#“host.name”的值(如果已配置)。否则,它将使用从返回的值
#java.net.InetAddress.getCanonicalHostName()。
#advised.host.name=
#要发布到ZooKeeper供客户端使用的端口。如果没有设置,
#它将发布代理绑定到的同一端口。
#A.港口=
#处理网络请求的线程数
num.network.threads=3
#执行磁盘I/O的线程数
num.io.threads=8
#套接字服务器使用的发送缓冲区(sou SNDBUF)
socket.send.buffer.bytes=102400
#套接字服务器使用的接收缓冲区(SO_RCVBUF)
socket.receive.buffer.bytes=102400
#套接字服务器将接受的请求的最大大小(针对OOM的保护)
socket.request.max.bytes=104857600
#############################日志基础#############################
#以逗号分隔的目录列表,用于存储日志文件
log.dirs=/home/ubuntu/kafka日志
#每个主题的默认日志分区数。更多的分区允许更大的容量
#并行性,但这也会导致跨
#经纪人。
num.partitions=1
#启动时用于日志恢复和关闭时用于刷新的每个数据目录的线程数。
#对于数据目录位于RAID阵列中的安装,建议增加此值。
num.recovery.threads.per.data.dir=1
#############################日志刷新策略#############################
#消息会立即写入文件系统,但默认情况下,我们只需fsync()进行同步
#操作系统缓存很慢。以下配置控制数据到磁盘的刷新。
#这里有几个重要的权衡:
# 1. 持久性:如果不使用复制,未刷新的数据可能会丢失。
# 2. 延迟:当确实发生刷新时,非常大的刷新间隔可能会导致延迟峰值,因为将有大量数据要刷新。
# 3. 吞吐量:刷新通常是最昂贵的操作,较小的刷新间隔可能导致过度搜索。
#下面的设置允许用户配置刷新策略,以便在一段时间或之后刷新数据
#每N条消息(或两者都有)。这可以在全局范围内完成,并在每个主题的基础上覆盖。
#强制将数据刷新到磁盘之前要接受的消息数
#log.flush.interval.messages=10000
#在我们强制刷新之前,消息在日志中的最长时间
#log.flush.interval.ms=1000
#############################日志保留策略#############################
#以下配置控制日志段的处理。政策可以
#设置为在一段时间后或在给定大小累积后删除段。
#只要满足这些条件中的*任一*项,就会删除一个段。删除总是发生的
#从日志的末尾。
#符合删除条件的日志文件的最短期限
log.retention.hours=168
#基于大小的日志保留策略。只要剩余的部分被删除,就从日志中删除这些部分
#段不会下降到log.retention.bytes以下。
#log.retention.bytes=1073741824
#日志段文件的最大大小。当达到此大小时,将创建一个新的日志段。
log.segment.bytes=1073741824
#检查日志段以查看是否可以根据需要删除日志段的间隔
#保留策略
log.retention.check.interval.ms=300000
#默认情况下,日志清理器处于禁用状态,日志保留策略将默认为在保留期到期后仅删除段。
#如果设置了log.cleaner.enable=true,则将启用清洁器,然后可以标记单个日志以进行日志压缩。
log.cleaner.enable=false
#############################动物园管理员#############################
#Zookeeper连接字符串(有关详细信息,请参阅Zookeeper文档)。
#这是一个逗号分隔的主机:端口对,每个对应一个zk
#服务器。e、 g.“127.0.0.1:3000127.0.0.1:3001127.0.0.1:3002”。
#您还可以将可选的chroot字符串附加到URL以指定
#所有kafka znode的根目录。
zookeeper.connect=zookeeper:2181
#连接到zookeeper的超时(毫秒)
zookeeper.connection.timeout.ms=6000
问题已修复
在kafka配置中的server.properties中添加了该行advised.host.name=ec2ap-southerast-1.compute.amazonaws.com
(您必须提供完全合格的
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# see kafka.server.KafkaConfig for additional details and defaults
############################# 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 port the socket server listens on
port=9092
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=kafka
# Hostname the broker will advertise to producers and consumers. If not set, it uses the
# value for "host.name" if configured. Otherwise, it will use the value returned from
# java.net.InetAddress.getCanonicalHostName().
# advertised.host.name=<>
# The port to publish to ZooKeeper for clients to use. If this is not set,
# it will publish the same port that the broker binds to.
# advertised.port=<>
# The number of threads handling network requests
num.network.threads=3
# The number of threads doing 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 seperated list of directories under which to store log files
log.dirs=/home/ubuntu/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
############################# 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 exceessive 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
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes.
#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
# By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires.
# If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction.
log.cleaner.enable=false
############################# 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=zookeeper:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
advertised.host.name