惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

H
Hackread – Cybersecurity News, Data Breaches, AI and More
T
The Blog of Author Tim Ferriss
IT之家
IT之家
J
Java Code Geeks
C
Check Point Blog
F
Full Disclosure
B
Blog RSS Feed
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Engineering at Meta
Engineering at Meta
Recorded Future
Recorded Future
博客园 - 聂微东
Stack Overflow Blog
Stack Overflow Blog
M
MIT News - Artificial intelligence
大猫的无限游戏
大猫的无限游戏
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
月光博客
月光博客
The Cloudflare Blog
罗磊的独立博客
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
有赞技术团队
有赞技术团队
MongoDB | Blog
MongoDB | Blog
GbyAI
GbyAI
量子位
宝玉的分享
宝玉的分享
博客园 - 三生石上(FineUI控件)
F
Fortinet All Blogs
V
V2EX
人人都是产品经理
人人都是产品经理
A
About on SuperTechFans
D
Docker
MyScale Blog
MyScale Blog
P
Proofpoint News Feed
Blog — PlanetScale
Blog — PlanetScale
Recent Announcements
Recent Announcements
腾讯CDC
The GitHub Blog
The GitHub Blog
L
LangChain Blog
爱范儿
爱范儿
G
Google Developers Blog
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
阮一峰的网络日志
阮一峰的网络日志
U
Unit 42
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园_首页
aimingoo的专栏
aimingoo的专栏
S
SegmentFault 最新的问题
Microsoft Security Blog
Microsoft Security Blog
V
Visual Studio Blog

Apache Kafka

Important configuration properties for Kafka broker Important configuration properties for the high-level consumer Kafka Configuration API Design API Design API Design API Design API Design API Design API Design Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Basic Kafka Operations Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Broker Configs Datacenters Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design Design
Broker Configs
2001-01-01 · via Apache Kafka

You are viewing documentation for an older version (0.8.0) of Kafka. For up-to-date documentation, see the latest version.

Broker Configs

The essential configurations are the following:

  • broker.id
  • log.dirs
  • zookeeper.connect

Property

Default

Description

broker.id

Each broker is uniquely identified by a non-negative integer id. This id serves as the brokers “name” and allows the broker to be moved to a different host/port without confusing consumers. You can choose any number you like so long as it is unique.

log.dirs

/tmp/kafka-logs

A comma-separated list of one or more directories in which Kafka data is stored. Each new partition that is created will be placed in the directory which currently has the fewest partitions.

port

6667

The port on which the server accepts client connections.

zookeeper.connect

null

Specifies the zookeeper connection string in the form hostname:port, where hostname and port are the host and port for a node in your zookeeper cluster. To allow connecting through other zookeeper nodes when that host is down you can also specify multiple hosts in the form hostname1:port1,hostname2:port2,hostname3:port3.

Zookeeper also allows you to add a “chroot” path which will make all kafka data for this cluster appear under a particular path. This is a way to setup multiple Kafka clusters or other applications on the same zookeeper cluster. To do this give a connection string in the form hostname1:port1,hostname2:port2,hostname3:port3/chroot/path which would put all this cluster’s data under the path /chroot/path. Note that you must create this path yourself prior to starting the broker and consumers must use the same connection string.

message.max.bytes

1000000

The maximum size of a message that the server can receive. It is important that this property be in sync with the maximum fetch size your consumers use or else an unruly producer will be able to publish messages too large for consumers to consume.

num.network.threads

3

The number of network threads that the server uses for handling network requests. You probably don’t need to change this.

num.io.threads

8

The number of I/O threads that the server uses for executing requests. You should have at least as many threads as you have disks.

queued.max.requests

500

The number of requests that can be queued up for processing by the I/O threads before the network threads stop reading in new requests.

host.name

null

Hostname of broker. If this is set, it will only bind to this address. If this is not set, it will bind to all interfaces, and publish one to ZK.

socket.send.buffer.bytes

100 * 1024

The SO_SNDBUFF buffer the server prefers for socket connections.

socket.receive.buffer.bytes

100 * 1024

The SO_RCVBUFF buffer the server prefers for socket connections.

socket.request.max.bytes

100 * 1024 * 1024

The maximum request size the server will allow. This prevents the server from running out of memory and should be smaller than the Java heap size.

num.partitions

1

The default number of partitions per topic.

log.segment.bytes

1024 * 1024 * 1024

The log for a topic partition is stored as a directory of segment files. This setting controls the size to which a segment file will grow before a new segment is rolled over in the log.

log.segment.bytes.per.topic

""

This setting allows overriding log.segment.bytes on a per-topic basis.

log.roll.hours

24 * 7

This setting will force Kafka to roll a new log segment even if the log.segment.bytes size has not been reached.

log.roll.hours.per.topic

""

This setting allows overriding log.roll.hours on a per-topic basis.

log.retention.hours

24 * 7

The number of hours to keep a log segment before it is deleted, i.e. the default data retention window for all topics. Note that if both log.retention.hours and log.retention.bytes are both set we delete a segment when either limit is exceeded.

log.retention.hours.per.topic

""

A per-topic override for log.retention.hours.

log.retention.bytes

-1

The amount of data to retain in the log for each topic-partitions. Note that this is the limit per-partition so multiply by the number of partitions to get the total data retained for the topic. Also note that if both log.retention.hours and log.retention.bytes are both set we delete a segment when either limit is exceeded.

log.retention.bytes.per.topic

""

A per-topic override for log.retention.bytes.

log.retention.check.interval.ms

300000

The frequency in milliseconds that the log cleaner checks whether any log segment is eligible for deletion to meet the retention policies.

log.index.size.max.bytes

10 * 1024 * 1024

The maximum size in bytes we allow for the offset index for each log segment. Note that we will always pre-allocate a sparse file with this much space and shrink it down when the log rolls. If the index fills up we will roll a new log segment even if we haven’t reached the log.segment.bytes limit.

log.index.interval.bytes

4096

The byte interval at which we add an entry to the offset index. When executing a fetch request the server must do a linear scan for up to this many bytes to find the correct position in the log to begin and end the fetch. So setting this value to be larger will mean larger index files (and a bit more memory usage) but less scanning. However the server will never add more than one index entry per log append (even if more than log.index.interval worth of messages are appended). In general you probably don’t need to mess with this value.

log.flush.interval.messages

10000

The number of messages written to a log partition before we force an fsync on the log. Setting this higher will improve performance a lot but will increase the window of data at risk in the event of a crash (though that is usually best addressed through replication). If both this setting and log.flush.interval.ms are both used the log will be flushed when either criteria is met.

log.flush.interval.ms.per.topic

""

The per-topic override for log.flush.interval.messages, e.g., topic1:3000,topic2:6000

log.flush.scheduler.interval.ms

3000

The frequency in ms that the log flusher checks whether any log is eligible to be flushed to disk.

log.flush.interval.ms

3000

The maximum time between fsync calls on the log. If used in conjuction with log.flush.interval.messages the log will be flushed when either criteria is met.

auto.create.topics.enable

true

Enable auto creation of topic on the server. If this is set to true then attempts to produce, consume, or fetch metadata for a non-existent topic will automatically create it with the default replication factor and number of partitions.

controller.socket.timeout.ms

30000

The socket timeout for commands from the partition management controller to the replicas.

controller.message.queue.size

10

The buffer size for controller-to-broker-channels

default.replication.factor

1

The default replication factor for automatically created topics.

replica.lag.time.max.ms

10000

If a follower hasn’t sent any fetch requests for this window of time, the leader will remove the follower from ISR (in-sync replicas) and treat it as dead.

replica.lag.max.messages

4000

If a replica falls more than this many messages behind the leader, the leader will remove the follower from ISR and treat it as dead.

replica.socket.timeout.ms

30 * 1000

The socket timeout for network requests to the leader for replicating data.

replica.socket.receive.buffer.bytes

64 * 1024

The socket receive buffer for network requests to the leader for replicating data.

replica.fetch.max.bytes

1024 * 1024

The number of byes of messages to attempt to fetch for each partition in the fetch requests the replicas send to the leader.

replica.fetch.wait.max.ms

500

The maximum amount of time to wait time for data to arrive on the leader in the fetch requests sent by the replicas to the leader.

replica.fetch.min.bytes

1

Minimum bytes expected for each fetch response for the fetch requests from the replica to the leader. If not enough bytes, wait up to replica.fetch.wait.max.ms for this many bytes to arrive.

num.replica.fetchers

1

Number of threads used to replicate messages from leaders. Increasing this value can increase the degree of I/O parallelism in the follower broker.

replica.high.watermark.checkpoint.interval.ms

5000

The frequency with which each replica saves its high watermark to disk to handle recovery.

fetch.purgatory.purge.interval.requests

10000

The purge interval (in number of requests) of the fetch request purgatory.

producer.purgatory.purge.interval.requests

10000

The purge interval (in number of requests) of the producer request purgatory.

zookeeper.session.timeout.ms

6000

Zookeeper session timeout. If the server fails to heartbeat to zookeeper within this period of time it is considered dead. If you set this too low the server may be falsely considered dead; if you set it too high it may take too long to recognize a truly dead server.

zookeeper.connection.timeout.ms

6000

The maximum amount of time that the client waits to establish a connection to zookeeper.

zookeeper.sync.time.ms

2000

How far a ZK follower can be behind a ZK leader.

controlled.shutdown.enable

false

Enable controlled shutdown of the broker. If enabled, the broker will move all leaders on it to some other brokers before shutting itself down. This reduces the unavailability window during shutdown.

controlled.shutdown.max.retries

3

Number of retries to complete the controlled shutdown successfully before executing an unclean shutdown.

controlled.shutdown.retry.backoff.ms

5000

Backoff time between shutdown retries.

More details about broker configuration can be found in the scala class kafka.server.KafkaConfig.