Kafka benchmark-commands

Producer

Setup

bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test-rep-one --partitions 6 --replication-factor 1

bin/kafka-topics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test --partitions 6 --replication-factor 3

Single thread, no replication

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test7 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

Single-thread, async 3x replication

bin/kafktopics.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --create --topic test --partitions 6 --replication-factor 3

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test6 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

Single-thread, sync 3x replication

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test 50000000 100 -1 acks=-1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=64000

Three Producers, 3x async replication

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

Throughput Versus Stored Data

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test 50000000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

Effect of message size

for i in 10 100 1000 10000 100000;

do

echo ""

echo $i

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test $((1000*1024*1024/$i)) $i -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=128000

done;

Consumer

Consumer throughput

bin/kafka-consumer-perf-test.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --messages 50000000 --topic test --threads 1

3 Consumers

On three servers, run:

bin/kafka-consumer-perf-test.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --messages 50000000 --topic test --threads 1

End-to-end Latency

bin/kafka-run-class.sh kafka.tools.TestEndToEndLatency esv4-hcl198.grid.linkedin.com:9092 esv4-hcl197.grid.linkedin.com:2181 test 5000

Producer and consumer

bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance test 50000000 100 -1 acks=1 bootstrap.servers=esv4-hcl198.grid.linkedin.com:9092 buffer.memory=67108864 batch.size=8196

bin/kafka-consumer-perf-test.sh --zookeeper esv4-hcl197.grid.linkedin.com:2181 --messages 50000000 --topic test --threads 1

server-config.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 and advertise to producers and consumers.

# If not set, the server will bind to all interfaces and advertise the value returned from

# from java.net.InetAddress.getCanonicalHostName().

#host.name=localhost

# The number of threads handling network requests

num.network.threads=4

 

# 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=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 #############################

# The directory under which to store log files

log.dirs=/grid/a/dfs-data/kafka-logs,/grid/b/dfs-data/kafka-logs,/grid/c/dfs-data/kafka-logs,/grid/d/dfs-data/kafka-logs,/grid/e/dfs-data/kafka-logs,/grid/f/dfs-data/kafka-logs

# The number of logical partitions per topic per server. More partitions allow greater parallelism

# for consumption, but also mean more files.

num.partitions=8

############################# Log Flush Policy #############################

# The following configurations control the flush of data to disk. This is the most

# important performance knob in kafka.

# There are a few important trade-offs here:

#    1. Durability: Unflushed data is at greater risk of loss in the event of a crash.

#    2. Latency: Data is not made available to consumers until it is flushed (which adds latency).

#    3. Throughput: The flush is generally the most expensive operation. 

# 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.

# Per-topic overrides for log.flush.interval.ms

#log.flush.intervals.ms.per.topic=topic1:1000, topic2:3000

############################# 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=536870912

# The interval at which log segments are checked to see if they can be deleted according 

# to the retention policies

log.cleanup.interval.mins=1

############################# 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=esv4-hcl197.grid.linkedin.com:2181

# Timeout in ms for connecting to zookeeper

zookeeper.connection.timeout.ms=1000000

# metrics reporter properties

kafka.metrics.polling.interval.secs=5

kafka.metrics.reporters=kafka.metrics.KafkaCSVMetricsReporter

kafka.csv.metrics.dir=/tmp/kafka_metrics

# Disable csv reporting by default.

kafka.csv.metrics.reporter.enabled=false

replica.lag.max.messages=10000000