Cannot start apache kafka from command line on hortonworks sandbox - apache-kafka

I need to override server.properties for kafka to add advertised host name, advertised listener and advertised port.
I tried changing server.properties and restarting kafka from ambari but the server.properties go back to previous values once the kafka server is up.
Then i figured i could start zookeeper and kafka from command line. I tried
/usr/hdp/current/zookeeper-server/bin/zkServer.sh start
The zookeeper started fine and reflected that it started in ambari but
/usr/hdp/3.0.1.0-187/kafka/bin/kafka-server-start.sh /usr/hdp/3.0.1.0-187/kafka/config/server.properties --override advertised.host.name=localhost --override advertised.listeners=PLAINTEXT
://:sandbox-hdp.hortonworks.com:6667 --override advertised.port=6667
This did not start kafka server or not atleast when i tried some consumers and did not reflect in the Ambari GUI.
The ports are mentioned in the properties file, any leads on how to override advertised listeners? And if yes what should be the advertised host name, listener and port values?
I am attaching the properties files, IP addresses for both windows(Host OS) and sandbox.
Sandbox IP: 172.18.0.2
Windows IP: 192.168.0.21
This is consumer.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 org.apache.kafka.clients.consumer.ConsumerConfig for more details
# list of brokers used for bootstrapping knowledge about the rest of the cluster
# format: host1:port1,host2:port2 ...
bootstrap.servers=localhost:9092
# consumer group id
group.id=test-consumer-group
# What to do when there is no initial offset in Kafka or if the current
# offset does not exist any more on the server: latest, earliest, none
#auto.offset.reset=
This is producer.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 org.apache.kafka.clients.producer.ProducerConfig for more details
############################# Producer Basics #############################
# list of brokers used for bootstrapping knowledge about the rest of the cluster
# format: host1:port1,host2:port2 ...
bootstrap.servers=localhost:9092
# specify the compression codec for all data generated: none, gzip, snappy, lz4
compression.type=none
# name of the partitioner class for partitioning events; default partition spreads data randomly
#partitioner.class=
# the maximum amount of time the client will wait for the response of a request
#request.timeout.ms=
# how long `KafkaProducer.send` and `KafkaProducer.partitionsFor` will block for
#max.block.ms=
# the producer will wait for up to the given delay to allow other records to be sent so that the sends can be batched together
#linger.ms=
# the maximum size of a request in bytes
#max.request.size=
# the default batch size in bytes when batching multiple records sent to a partition
#batch.size=
# the total bytes of memory the producer can use to buffer records waiting to be sent to the server
#buffer.memory=
This is server.properties
# Generated by Apache Ambari. Sun May 3 19:25:08 2020
auto.create.topics.enable=true
auto.leader.rebalance.enable=true
compression.type=producer
controlled.shutdown.enable=true
controlled.shutdown.max.retries=3
controlled.shutdown.retry.backoff.ms=5000
controller.message.queue.size=10
controller.socket.timeout.ms=30000
default.replication.factor=1
delete.topic.enable=true
external.kafka.metrics.exclude.prefix=kafka.network.RequestMetrics,kafka.server.DelayedOperationPurgatory,kafka.server.BrokerTopicMetrics.BytesRejectedPerSec
external.kafka.metrics.include.prefix=kafka.network.RequestMetrics.ResponseQueueTimeMs.request.OffsetCommit.98percentile,kafka.network.RequestMetrics.ResponseQueueTimeMs.request.Offsets.95percentile,kafka.network.RequestMetrics.ResponseSendTimeMs.request.Fetch.95percentile,kafka.network.RequestMetrics.RequestsPerSec.request
fetch.purgatory.purge.interval.requests=10000
kafka.ganglia.metrics.group=kafka
kafka.ganglia.metrics.host=localhost
kafka.ganglia.metrics.port=8671
kafka.ganglia.metrics.reporter.enabled=true
kafka.metrics.reporters=
kafka.timeline.metrics.host_in_memory_aggregation=
kafka.timeline.metrics.host_in_memory_aggregation_port=
kafka.timeline.metrics.host_in_memory_aggregation_protocol=
kafka.timeline.metrics.hosts=
kafka.timeline.metrics.maxRowCacheSize=10000
kafka.timeline.metrics.port=
kafka.timeline.metrics.protocol=
kafka.timeline.metrics.reporter.enabled=true
kafka.timeline.metrics.reporter.sendInterval=5900
kafka.timeline.metrics.truststore.password=
kafka.timeline.metrics.truststore.path=
kafka.timeline.metrics.truststore.type=
leader.imbalance.check.interval.seconds=300
leader.imbalance.per.broker.percentage=10
listeners=PLAINTEXT://sandbox-hdp.hortonworks.com:6667
log.cleanup.interval.mins=10
log.dirs=/kafka-logs
log.index.interval.bytes=4096
log.index.size.max.bytes=10485760
log.retention.bytes=-1
log.retention.check.interval.ms=600000
log.retention.hours=168
log.roll.hours=168
log.segment.bytes=1073741824
message.max.bytes=1000000
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=1
offsets.topic.segment.bytes=104857600
port=6667
producer.metrics.enable=false
producer.purgatory.purge.interval.requests=10000
queued.max.requests=500
replica.fetch.max.bytes=1048576
replica.fetch.min.bytes=1
replica.fetch.wait.max.ms=500
replica.high.watermark.checkpoint.interval.ms=5000
replica.lag.max.messages=4000
replica.lag.time.max.ms=10000
replica.socket.receive.buffer.bytes=65536
replica.socket.timeout.ms=30000
sasl.enabled.mechanisms=GSSAPI
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.client.auth=none
ssl.key.password=
ssl.keystore.location=
ssl.keystore.password=
ssl.truststore.location=
ssl.truststore.password=
zookeeper.connect=sandbox-hdp.hortonworks.com:2181
zookeeper.connection.timeout.ms=25000
zookeeper.session.timeout.ms=30000
zookeeper.sync.time.ms=2000
This is zookeeper.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.
# the directory where the snapshot is stored.
dataDir=/tmp/zookeeper
# the port at which the clients will connect
clientPort=2181
# disable the per-ip limit on the number of connections since this is a non-production config
maxClientCnxns=0

Cannot be sure if you are hitting this, but the generic solution to 'I changed properties and my change disappeared' can be explained as follows:
There are config files used by the services, these are managed by Ambari.
It is possible to change these files directly, but this is not recommended as Ambari will simply overwrite them as soon as it gets the chance.
As such the root cause of your problem may be that you updated configs directly in the file, rather than through Ambari.
You may also want to check out this thread: https://community.cloudera.com/t5/Support-Questions/Producing-to-Kafka-HDP-Sandbox-2-6-4/td-p/189742

Related

Create pyFlink DataStream Consumer from Tweets Kafka Producer in Python

I want to create I stream kafka consumer in pyFlink, which can read tweets data after deserialization (json),
I have pyflink version 1.14.4 (last version)
Can I have an example of kafka producer and a simple code of flink consumer for stream in python?
Here is an example given in PyFlink examples which shows how to read json data from Kafka consumer in PyFlink DataStream API:
################################################################################
# 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.
################################################################################
import logging
import sys
from pyflink.common import Types, JsonRowDeserializationSchema, JsonRowSerializationSchema
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.datastream.connectors import FlinkKafkaProducer, FlinkKafkaConsumer
# Make sure that the Kafka cluster is started and the topic 'test_json_topic' is
# created before executing this job.
def write_to_kafka(env):
type_info = Types.ROW([Types.INT(), Types.STRING()])
ds = env.from_collection(
[(1, 'hi'), (2, 'hello'), (3, 'hi'), (4, 'hello'), (5, 'hi'), (6, 'hello'), (6, 'hello')],
type_info=type_info)
serialization_schema = JsonRowSerializationSchema.Builder() \
.with_type_info(type_info) \
.build()
kafka_producer = FlinkKafkaProducer(
topic='test_json_topic',
serialization_schema=serialization_schema,
producer_config={'bootstrap.servers': 'localhost:9092', 'group.id': 'test_group'}
)
# note that the output type of ds must be RowTypeInfo
ds.add_sink(kafka_producer)
env.execute()
def read_from_kafka(env):
deserialization_schema = JsonRowDeserializationSchema.Builder() \
.type_info(Types.ROW([Types.INT(), Types.STRING()])) \
.build()
kafka_consumer = FlinkKafkaConsumer(
topics='test_json_topic',
deserialization_schema=deserialization_schema,
properties={'bootstrap.servers': 'localhost:9092', 'group.id': 'test_group_1'}
)
kafka_consumer.set_start_from_earliest()
env.add_source(kafka_consumer).print()
env.execute()
if __name__ == '__main__':
logging.basicConfig(stream=sys.stdout, level=logging.INFO, format="%(message)s")
env = StreamExecutionEnvironment.get_execution_environment()
env.add_jars("file:///path/to/flink-sql-connector-kafka-1.15.0.jar")
print("start writing data to kafka")
write_to_kafka(env)
print("start reading data from kafka")
read_from_kafka(env)

Not able to replicate groups in Mirror Maker 2

Initially, I created a topic named "quickstart-events" and then produced some messages into it, then consumed it from the kafka-console-consumer with consumer group "quickstartGroup" and now I want to replicate the group from source to destination.
When I run describe command to describe the group in the source cluster
~/kafka/bin/kafka-consumer-groups.sh --bootstrap-server localhost:9092 --describe --group quickstartGroup
The output I'm getting is
Consumer group 'quickstartGroup' has no active members.
GROUP TOPIC PARTITION CURRENT-OFFSET LOG-END-OFFSET LAG CONSUMER-ID HOST CLIENT-ID
quickstartGroup quickstart-events 1 9 12 3 - - -
quickstartGroup quickstart-events 0 9 12 3 - - - -
Here, the topic is getting replicated but when I run the command to describe the group in the destination cluster
kafka-consumer-groups.sh --bootstrap-server localhost:9093 --describe --group quickstartGroup
Getting error as
Error: Consumer group 'quickstartGroup' does not exist
My Mirror Maker 2 properties file contents are:
# Licensed to the Apache Software Foundation (ASF) under A 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 org.apache.kafka.clients.consumer.ConsumerConfig for more details
# Sample MirrorMaker 2.0 top-level configuration file
# Run with ./bin/connect-mirror-maker.sh connect-mirror-maker.properties
# specify any number of cluster aliases
clusters = A, B
# connection information for each cluster
# This is a comma separated host:port pairs for each cluster
# for e.g. "A_host1:9092, A_host2:9092, A_host3:9092"
A.bootstrap.servers = localhost:9092
B.bootstrap.servers = localhost:9093
# enable and configure individual replication flows
A->B.enabled = true
# regex which defines which topics gets replicated. For eg "foo-.*"
A->B.topics = quickstart-events.*
A->B.groups = quickstartGroup.*
# Setting replication factor of newly created remote topics
replication.factor=2
############################# Internal Topic Settings #############################
# The replication factor for mm2 internal topics "heartbeats", "B.checkpoints.internal" and
# "mm2-offset-syncs.B.internal"
# For anything other than development testing, a value greater than 1 is recommended to ensure availability such as 3.
checkpoints.topic.replication.factor=1
heartbeats.topic.replication.factor=1
offset-syncs.topic.replication.factor=1
# The replication factor for connect internal topics "mm2-configs.B.internal", "mm2-offsets.B.internal" and
# "mm2-status.B.internal"
# For anything other than development testing, a value greater than 1 is recommended to ensure availability such as 3.
offset.storage.replication.factor=1
status.storage.replication.factor=1
config.storage.replication.factor=1
# customize as needed
# replication.policy.separator = _
# sync.topic.acls.enabled = false
# emit.heartbeats.interval.seconds = 5
groups.exclude = ''
replication.policy.class=ch.mawileo.kafka.mm2.PrefixlessReplicationPolicy
P.S: I am using Kafka 2.8

Kafka topics with different retention although having the same configuration

I have a question regarding retention of topics messages.
I have the following situation:
Two Kafka topics;
Broker has properties log.retention.hours=1;
Describe command for each of the two topics:
[oracleas#zkafka01vdc bin]$ ./kafka-topics.sh --zookeeper 192.168.163.71:2181 --describe --topic digital-lending
Topic:digital-lending PartitionCount:3 ReplicationFactor:2 Configs:
Topic: digital-lending Partition: 0 Leader: 3 Replicas: 1,3 Isr: 3,1
Topic: digital-lending Partition: 1 Leader: 2 Replicas: 2,1 Isr: 1,2
Topic: digital-lending Partition: 2 Leader: 3 Replicas: 3,2 Isr: 3,2
[oracleas#zkafka01vdc bin]$ ./kafka-topics.sh --zookeeper 192.168.163.71:2181 --describe --topic digital-onboarding
Topic:digital-onboarding PartitionCount:1 ReplicationFactor:1 Configs:
Topic: digital-onboarding Partition: 0 Leader: 1 Replicas: 1 Isr: 1
The question are:
How is possible that topic digital-onboarding have retention 1 day and digital-lending 1 week (based on my observation - tried several times to take all the messages from queue and for one topics the retention was 1 day and for the other one was 1 week)?
Is there another place where it is setuped besides the --describe command and server.properties file?
Edit 1:
server.properties file:
# 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=1
# Switch to enable topic deletion or not, default value is false
delete.topic.enable=true
############################# 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://10.206.23.71:9092
listeners=EXTERNAL://zkafka01vdc-pub:9092,INTERNAL://zkafka01vdc-int:9093
# 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://zkafka01vdc.bcr.wan:9092
advertised.listeners=EXTERNAL://zkafka01vdc.bcr.wan:9092,INTERNAL://zkafka01vdc-int:9093
# 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
listener.security.protocol.map=EXTERNAL:PLAINTEXT,INTERNAL:PLAINTEXT
inter.broker.listener.name=INTERNAL
# 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 seperated list of directories under which to store log files
log.dirs=/zkafka/kafka
# 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 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 due to age
log.retention.hours=1
# 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. 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=30000
############################# 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=zkafka01vdc-int:2181,zkafka02vdc-int:2181,zkafka03vdc-int: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
You can run the following commands in order to set per-topic retention configuration:
bin/kafka-configs.sh \
--zookeeper 192.168.163.71:2181 \
--alter \
--entity-type topics \
--entity-name digital-onboarding \
--add-config retention.hours=24
and
bin/kafka-configs.sh \
--zookeeper 192.168.163.71:2181 \
--alter \
--entity-type topics \
--entity-name digital-lengid \
--add-config retention.hours=168
Once changed, you can verify that the configuration is effective by describing the topic:
bin/kafka-topics.sh \
--zookeeper 192.168.163.71:2181
--describe \
--topic digital-onboarding
The new retention policy should be listed under Configs:
Remember that the retention time is not a hard upper limit but more a lower bound for your message to stay in a topic. It is important to note that messages out of an active segment will never be deleted out of a topic, even if the message exceeds the retention time. More details can be found in data still remains in kafka topic even after retention time
In Kafka you can set the retention time either by a cluster wide setting or by a topic specific setting. If you do not specify a topic specific value when creating the topic, the cluster wide setting serves as default.
In the Kafka documentation on Topic Configs it is written:
retention.ms: This configuration controls the maximum time we will retain a log before we will discard old log segments to free up space if we are using the "delete" retention policy. This represents an SLA on how soon consumers must read their data. If set to -1, no time limit is applied.
Type: long
Default: 604800000
Valid Values: [-1,...]
Server Default Property: log.retention.ms
Importance: medium
It you do not set this, the log.retention.ms (or log.retention.hours) will be used.

Unable to setup Apache Zookeeper and Kafka on windows machine

I am very new to Apache Zookeeper and Kafka. I've downloaded below on windows machine.
Apache Zookeeper - http://zookeeper.apache.org/releases.html
Kafka - https://kafka.apache.org/downloads.html
I am not very clear on what to execute next or where to make necessary changes.
I went to C:\apache-zookeeper-3.6.0\bin and executed zkServer.bat file
C:\apache-zookeeper-3.6.0\bin>call "C:\Program Files\Java\jdk1.8.0_151"\bin\java "-Dzookeeper.log.dir=C:\apache-zookeeper-3.6.0\bin\..\logs" "-Dzookeeper.root.logger=INFO,CONSOLE" "-Dzookeeper.log.file=zookeeper-pc-server-DESKTOP-NQ639DU.log" "-XX:+HeapDumpOnOutOfMemoryError" "-XX:OnOutOfMemoryError=cmd /c taskkill /pid %%p /t /f" -cp "C:\apache-zookeeper-3.6.0\bin\..\build\classes;C:\apache-zookeeper-3.6.0\bin\..\build\lib\*;C:\apache-zookeeper-3.6.0\bin\..\*;C:\apache-zookeeper-3.6.0\bin\..\lib\*;C:\apache-zookeeper-3.6.0\bin\..\conf" org.apache.zookeeper.server.quorum.QuorumPeerMain "C:\apache-zookeeper-3.6.0\bin\..\conf\zoo.cfg"
Error: Could not find or load main class org.apache.zookeeper.server.quorum.QuorumPeerMain
C:\apache-zookeeper-3.6.0\bin>endlocal
And Kafka from the location: C:\kafka_2.11-2.3.1\bin\windows
C:\kafka_2.11-2.3.1\bin\windows>kafka-server-start.bat
USAGE: kafka-server-start.bat server.properties
C:\kafka_2.11-2.3.1\bin\windows>
I've setup ZOOKEEPER_HOME=C:\apache-zookeeper-3.6.0 and PATH to C:\apache-zookeeper-3.6.0/bin.
I went through this video https://www.youtube.com/watch?v=TTsOoQ6_QB0 and it solved my issue.
Apache Zookeeper :
Create zookeeper_data (You can choose any name) inside C:\kafka_2.11-2.3.1 where my Kafka distribution has kept.
Then go to C:\kafka_2.11-2.3.1\config and edit zookeeper.properties file and use dataDir=C:\kafka_2.11-2.3.1\zookeeper_data
Step to Start Zookeeper:
zookeeper-server-start.bat C:\kafka_2.11-2.3.1\config\zookeeper.properties
Apache Kafka:
Create kafka-logs folder under C:\kafka_2.11-2.3.1 and then
Go to C:\kafka_2.11-2.3.1\config and edit server.properties file and use below
# A comma separated list of directories under which to store log files
log.dirs=C:\kafka_2.11-2.3.1\kafka-logs
############################# 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.num.partitions=1
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1
min.insync.replicas=1
default.replication.factor=1
Step To start Apache Kafka
kafka-server-start.bat C:\kafka_2.11-2.3.1\config\server.properties

launching multiple kafka broker fails

The repo used is: https://github.com/Yolean/kubernetes-kafka/
So I'm trying to run a Kafka cluster that connects to a Zookeeper cluster in Kubernetes, the first pod runs alright, but then the second Kafka pod tries to connect to the zookeeper cluster and it has this error:
kafka.common.InconsistentBrokerIdException: Configured broker.id 1
doesn't match stored broker.id 0 in meta.properties. If you moved your
data, make sure your configured broker.id matches. If you intend to
create a new broker, you should remove all data in your data
directories (log.dirs).
I understand the error is in the second broker id but shouldn't the zookeeper cluster allow multiple broker connections? or how could the config be changed to allow it?
or is it a Kafka configuration problem? The config file is:
kind: ConfigMap
metadata:
name: broker-config
namespace: whitenfv
labels:
name: kafka
system: whitenfv
apiVersion: v1
data:
init.sh: |-
#!/bin/bash
set -x
cp /etc/kafka-configmap/log4j.properties /etc/kafka/
KAFKA_BROKER_ID=${HOSTNAME##*-}
SEDS=("s/#init#broker.id=#init#/broker.id=$KAFKA_BROKER_ID/")
LABELS="kafka-broker-id=$KAFKA_BROKER_ID"
ANNOTATIONS=""
hash kubectl 2>/dev/null || {
SEDS+=("s/#init#broker.rack=#init#/#init#broker.rack=# kubectl not found in path/")
} && {
ZONE=$(kubectl get node "$NODE_NAME" -o=go-template='{{index .metadata.labels "failure-domain.beta.kubernetes.io/zone"}}')
if [ $? -ne 0 ]; then
SEDS+=("s/#init#broker.rack=#init#/#init#broker.rack=# zone lookup failed, see -c init-config logs/")
elif [ "x$ZONE" == "x<no value>" ]; then
SEDS+=("s/#init#broker.rack=#init#/#init#broker.rack=# zone label not found for node $NODE_NAME/")
else
SEDS+=("s/#init#broker.rack=#init#/broker.rack=$ZONE/")
LABELS="$LABELS kafka-broker-rack=$ZONE"
fi
OUTSIDE_HOST=$(kubectl get node "$NODE_NAME" -o jsonpath='{.status.addresses[?(#.type=="InternalIP")].address}')
if [ $? -ne 0 ]; then
echo "Outside (i.e. cluster-external access) host lookup command failed"
else
OUTSIDE_PORT=3240${KAFKA_BROKER_ID}
SEDS+=("s|#init#advertised.listeners=OUTSIDE://#init#|advertised.listeners=OUTSIDE://${OUTSIDE_HOST}:${OUTSIDE_PORT}|")
ANNOTATIONS="$ANNOTATIONS kafka-listener-outside-host=$OUTSIDE_HOST kafka-listener-outside-port=$OUTSIDE_PORT"
fi
if [ ! -z "$LABELS" ]; then
kubectl -n $POD_NAMESPACE label pod $POD_NAME $LABELS || echo "Failed to label $POD_NAMESPACE.$POD_NAME - RBAC issue?"
fi
if [ ! -z "$ANNOTATIONS" ]; then
kubectl -n $POD_NAMESPACE annotate pod $POD_NAME $ANNOTATIONS || echo "Failed to annotate $POD_NAMESPACE.$POD_NAME - RBAC issue?"
fi
}
printf '%s\n' "${SEDS[#]}" | sed -f - /etc/kafka-configmap/server.properties > /etc/kafka/server.properties.tmp
[ $? -eq 0 ] && mv /etc/kafka/server.properties.tmp /etc/kafka/server.properties
server.properties: |-
############################# Log Basics #############################
# A comma seperated list of directories under which to store log files
# Overrides log.dir
log.dirs=/var/lib/kafka/data/topics
# 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
default.replication.factor=3
min.insync.replicas=2
auto.create.topics.enable=true
# 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
############################# Server Basics #############################
# The id of the broker. This must be set to a unique integer for each broker.
#init#broker.id=#init#
#init#broker.rack=#init#
############################# 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
listeners=OUTSIDE://:9094,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
#init#advertised.listeners=OUTSIDE://#init#,PLAINTEXT://: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
listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL,OUTSIDE:PLAINTEXT
inter.broker.listener.name=PLAINTEXT
# 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
############################# 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.
# https://cwiki.apache.org/confluence/display/KAFKA/KIP-186%3A+Increase+offsets+retention+default+to+7+days
offsets.retention.minutes=10080
# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=-1
# 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=zoo-0.zoo:2181,zoo-1.zoo:2181,zoo-2.zoo: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
log4j.properties: |-
# Unspecified loggers and loggers with additivity=true output to server.log and stdout
# Note that INFO only applies to unspecified loggers, the log level of the child logger is used otherwise
log4j.rootLogger=INFO, stdout
log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=[%d] %p %m (%c)%n
log4j.appender.kafkaAppender=org.apache.log4j.DailyRollingFileAppender
log4j.appender.kafkaAppender.DatePattern='.'yyyy-MM-dd-HH
log4j.appender.kafkaAppender.File=${kafka.logs.dir}/server.log
log4j.appender.kafkaAppender.layout=org.apache.log4j.PatternLayout
log4j.appender.kafkaAppender.layout.ConversionPattern=[%d] %p %m (%c)%n
log4j.appender.stateChangeAppender=org.apache.log4j.DailyRollingFileAppender
log4j.appender.stateChangeAppender.DatePattern='.'yyyy-MM-dd-HH
log4j.appender.stateChangeAppender.File=${kafka.logs.dir}/state-change.log
log4j.appender.stateChangeAppender.layout=org.apache.log4j.PatternLayout
log4j.appender.stateChangeAppender.layout.ConversionPattern=[%d] %p %m (%c)%n
log4j.appender.requestAppender=org.apache.log4j.DailyRollingFileAppender
log4j.appender.requestAppender.DatePattern='.'yyyy-MM-dd-HH
log4j.appender.requestAppender.File=${kafka.logs.dir}/kafka-request.log
log4j.appender.requestAppender.layout=org.apache.log4j.PatternLayout
log4j.appender.requestAppender.layout.ConversionPattern=[%d] %p %m (%c)%n
log4j.appender.cleanerAppender=org.apache.log4j.DailyRollingFileAppender
log4j.appender.cleanerAppender.DatePattern='.'yyyy-MM-dd-HH
log4j.appender.cleanerAppender.File=${kafka.logs.dir}/log-cleaner.log
log4j.appender.cleanerAppender.layout=org.apache.log4j.PatternLayout
log4j.appender.cleanerAppender.layout.ConversionPattern=[%d] %p %m (%c)%n
log4j.appender.controllerAppender=org.apache.log4j.DailyRollingFileAppender
log4j.appender.controllerAppender.DatePattern='.'yyyy-MM-dd-HH
log4j.appender.controllerAppender.File=${kafka.logs.dir}/controller.log
log4j.appender.controllerAppender.layout=org.apache.log4j.PatternLayout
log4j.appender.controllerAppender.layout.ConversionPattern=[%d] %p %m (%c)%n
log4j.appender.authorizerAppender=org.apache.log4j.DailyRollingFileAppender
log4j.appender.authorizerAppender.DatePattern='.'yyyy-MM-dd-HH
log4j.appender.authorizerAppender.File=${kafka.logs.dir}/kafka-authorizer.log
log4j.appender.authorizerAppender.layout=org.apache.log4j.PatternLayout
log4j.appender.authorizerAppender.layout.ConversionPattern=[%d] %p %m (%c)%n
# Change the two lines below to adjust ZK client logging
log4j.logger.org.I0Itec.zkclient.ZkClient=INFO
log4j.logger.org.apache.zookeeper=INFO
# Change the two lines below to adjust the general broker logging level (output to server.log and stdout)
log4j.logger.kafka=INFO
log4j.logger.org.apache.kafka=INFO
# Change to DEBUG or TRACE to enable request logging
log4j.logger.kafka.request.logger=WARN, requestAppender
log4j.additivity.kafka.request.logger=false
# Uncomment the lines below and change log4j.logger.kafka.network.RequestChannel$ to TRACE for additional output
# related to the handling of requests
#log4j.logger.kafka.network.Processor=TRACE, requestAppender
#log4j.logger.kafka.server.KafkaApis=TRACE, requestAppender
#log4j.additivity.kafka.server.KafkaApis=false
log4j.logger.kafka.network.RequestChannel$=WARN, requestAppender
log4j.additivity.kafka.network.RequestChannel$=false
log4j.logger.kafka.controller=TRACE, controllerAppender
log4j.additivity.kafka.controller=false
log4j.logger.kafka.log.LogCleaner=INFO, cleanerAppender
log4j.additivity.kafka.log.LogCleaner=false
log4j.logger.state.change.logger=TRACE, stateChangeAppender
log4j.additivity.state.change.logger=false
# Change to DEBUG to enable audit log for the authorizer
log4j.logger.kafka.authorizer.logger=WARN, authorizerAppender
log4j.additivity.kafka.authorizer.logger=false
As per this: Launching multiple Kafka brokers fails, it's an issue with log.dirs in your server.properties where it can't be the same for all your brokers or it can't be shared.
You can probably use the ${HOSTNAME##*-} bash environment setting to modify your container entrypoint script that in of itself modifies your server.properties before the start, but the downside of that is that you are going to have to rebuild your Docker image.
Another strategy using StatefulSets is described here: How to pass args to pods based on Ordinal Index in StatefulSets?. But you will also have to make changes on how the Kafka entrypoint is called.
You could also try using completely different volumes for each of your Kafka broker pods.
First you must see the server configuration in the server.properties file.
~/kafka_2.11-2.1.0/bin$ egrep -v '^#|^$' ../config/server.properties
broker.id=0
num.network.threads=3
num.io.threads=8
socket.send.buffer.bytes=102400
socket.receive.buffer.bytes=102400
socket.request.max.bytes=104857600
log.dirs=/tmp/kafka-logs
...
Here you can see an attribute called log.dirs and a directory /tmp/kafka-logs as a value. Make sure that the directory has the right permissions for the user you are using to start the Kafka process.
~/kafka_2.11-2.1.0/bin$ ls -lrtd /tmp/kafka-logs
drwxr-xr-x 2 kafkauser kafkauser 4096 mar 1 08:26 /tmp/kafka-logs
Rremove all files under /tmp/kafka-logs
~/kafka_2.11-2.1.0/bin$ rm -fr /tmp/kafka-logs/*
And finally try again. Probably your problem is solved.