无法与azure IoT集线器建立Kafka源连接



从过去的5天到今天,我一直在努力解决这个问题。我已经启动并运行了azure Iot Hub,许多设备都可以连接并向其发送消息。与此同时,我正在探索使用kafka源连接铺设管道的选项,发现了toketikafka连接iothub,并使用它与我的iot hub集成。现在,从设备发送到物联网集线器的消息可以通过连接器在kafka接收器的另一端接收,但当我试图通过curl脚本向物联网集线器发送一些数据时就无法接收。

我已经验证了azure物联网中心能够接收来自我的curl脚本的消息。如果我手动生成一些关于卡夫卡主题的消息,消息就可以在另一端接收。这确认连接器有问题。任何人都可以帮助我缩小根本原因,这将对你非常有帮助。

curl -X POST 
'https://XXX.azure-devices.net/devices/devvXXX/messages/events?api-version=2016-02-03' 
-H 'authorization: SharedAccessSignature sr=device_key_valid' 
-H 'cache-control: no-cache' 
-H 'content-type: application/json' 
-d '{ "name":"John", "age":31, "city":"New York" }'

我的kafka服务器设置如下所示:

# 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
message.max.bytes=1347385956
############################# 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=100
# 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=300

连接器设置如下:

############################# Connector Config #############################
# Identifies the Azure IoT Hub source connector.
# Do not change this if you want to use the Azure IotHub source connector
connector.class=com.microsoft.azure.iot.kafka.connect.source.IotHubSourceConnector
# Name of the connector
name=AzureIotHubConnector
# Maximum number of tasks that should be created for this connector.
# More tasks means more parallelism. For optimal performance,
# this should equal the number of Azure IoT Hub partitions
tasks.max=1
# Kafka topic to which the data should be written to
Kafka.Topic=test
############################# IoTHub Config #############################
# Azure IoT Hub settings can be retrieved from the Azure portal at
# https://portal.azure.com. For more information on how to get the IoT Hub settings,
# please refer to the documentation here -
# https://learn.microsoft.com/en-us/azure/iot-hub/iot-hub-create-through-portal#endpoints
# https://learn.microsoft.com/en-us/azure/iot-hub/iot-hub-java-java-getstarted
# "IoT Hub" >> your hub >> "Endpoints" >> "Events" >> "Event Hub-compatible name"
IotHub.EventHubCompatibleName=iothub-valisnameXX
# "IoT Hub" >> your hub > "Endpoints" >> "Events" >> "Event Hub-compatible endpoint"
IotHub.EventHubCompatibleEndpoint=sb://XXvalidoneXX.servicebus.windows.net/
# "IoT Hub" >> your hub >> "Shared access policies"
# You can use the predefined value "service"
IotHub.AccessKeyName=iothubowner
# "IoT Hub" >> your hub >> "Shared access policies" >> key name >> "Primary key"
IotHub.AccessKeyValue=xxxvalidvaluexxx
# "IoT Hub" >> your hub > "Endpoints" >> "Events" >> Consumer groups
# "$Default" is predefined value.
IotHub.ConsumerGroup=XXvalidgrupnaeXX
# "IoT Hub" >> your hub >> "Endpoints" >> "Events" >> "Partitions"
IotHub.Partitions=2
# The time from which to start retrieving messages from IoTHub.
# The value should be in UTC and in the format yyyy-mm-ddThh:mm:ssZ
# This setting is mutually exclusive with IotHub.Offsets.
# If StartTime is provided, the Offsets value will be ignored.
IotHub.StartTime=2018-07-18 06:02:53,534
# The offsets for each IoTHub partition from which to start retrieving messages
# from IoTHub, as a comma separated string. For example, for 4 partitions,
# the value would be something like "abc,lmn,pqr,xyz".
# This setting is mutually exclusive with IotHub.StartTime.
# If StartTime is provided, the Offsets value will be ignored.
IotHub.Offsets=4
# The size of each batch for retrieving messages from IoTHub. The max supported value is 999.
BatchSize=1
# The max duration in seconds to wait for a full batch when retrieving messages from IoTHub. The default is 60.
ReceiveTimeout=60

我无法区分我的curl请求与直接来自我的设备的请求有何不同。。。不确定是否有任何与SSL相关的内容。

对不起,观测错误。从curl脚本发送的数据包实际上在kafka的另一端接收,但在队列中。当我看到昨天的包裹今天被阅读时,我才意识到这一点。

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