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Created February 4, 2022 23:21
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Slack Kafka server config
# 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
# Switch to enable topic deletion or not, default value is false.
# Topics can now only be deleted via
delete.topic.enable=false
# As our clusters grow in size, we would like to have more control of topic allocation and broker placement. Enabling automatic topic creation takes away this control. Further, topics are also
# created during metadata fetch requests. So, a fat fingered script can accientally create topics and cause issues. So, we should disable it in our clusters.
auto.create.topics.enable=false
# The default replication factor for automatically created topics.
default.replication.factor=3
# Number of threads used to replicate messages from leaders.
# Increasing this value can increase the degree of I/O parallelism in the follower broker.
num.replica.fetchers=4
# Minimum bytes expected for each fetch response. If not enough bytes, wait up to replicaMaxWaitTimeMs
# Default 1
replica.fetch.min.bytes=65536
# The socket receive buffer for network requests.
# Default 65536
replica.socket.receive.buffer.bytes=1048576
# max wait time for each fetcher request issued by follower replicas.
# This value should always be less than the replica.lag.time.max.ms at all times
# to prevent frequent shrinking of ISR for low throughput topics.
# Default 500
replica.fetch.wait.max.ms=5000
# If a follower hasn't sent any fetch requests or hasn't consumed up to the leaders log end offset
# for at least this time, the leader will remove the follower from isr.
# Default 10000
replica.lag.time.max.ms=10000
# The socket timeout for network requests. Its value should be at least replica.fetch.wait.max.ms.
# Default 30000
replica.socket.timeout.ms=30000
# The largest record batch size allowed by Kafka.
# If this is increased and there are consumers older than 0.10.2,
# the consumers' fetch size must also be increased so that the they can fetch record batches this large.
message.max.bytes = 1000000
# migrate any partitions the server is the leader for to other replicas prior to shutting down
controlled.shutdown.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://0.0.0.0:9092
# 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=1048576
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=1048576
# 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=/your/kafka/partitions
# 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=8
# 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=6
############################# 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=3
# TODO: these are for only-once semantics; factor of 1 is for dev environment
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=48
# 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=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=zkhost1:2181,zkhost2:2181,zkhost3:2181,zkhost4:2181,zkhost5:2181
# 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=3000
metric.reporters=com.linkedin.kafka.cruisecontrol.metricsreporter.CruiseControlMetricsReporter
# The rack awareness feature spreads replicas of the same partition across different racks.
# This extends the guarantees Kafka provides for broker-failure to cover rack-failure,
# limiting the risk of data loss should all the brokers on a rack fail at once.
broker.rack=<we partition by availability zone>
# Enables auto leader balancing. A background thread checks and triggers leader balance if required at regular intervals
auto.leader.rebalance.enable=false
# this is a very controversial setting, events and jq are OK with this, but it can lead to data losss
# This flag was turned on in previous versions of Kafka since we ran with Replication factor of 2.
# In Kafka 2.0, we want to run the cluster with RF=3.
# So, this flag should be turned off.
# This flag should only be turned on when the Kafka cluster is being brought up form an inconsistent state.
unclean.leader.election.enable=false
# Leader imbalance settings
# The ratio of leader imbalance allowed per broker. The controller would trigger a leader balance if it goes above this value per broker. The value is specified in percentage.
leader.imbalance.per.broker.percentage=0
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