发布时间: 2018-01-18 17:33:50
Kafka是什么:
kafka + storm/spark streaming Apache Kafka是一个开源消息系统,由Scala写成。是由Apache软件基金会开发的一个开源消息系统项目。 Kafka最初是由LinkedIn开发,并于2011年初开源。2012年10月从Apache Incubator毕业。该项目的目标是为处理实时数据提供一个统一、高通量、低等待的平台。 Kafka是一个分布式消息队列:生产者、消费者的功能。它提供了类似于JMS的特性,但是在设计实现上完全不同,此外它并不是JMS规范的实现。 Kafka对消息保存时根据Topic进行归类,发送消息者称为Producer,消息接受者称为Consumer,此外kafka集群有多个kafka实例组成,每个实例(server)成为broker。 无论是kafka集群,还是producer和consumer都依赖于zookeeper集群保存一些meta(元数据)信息,来保证系统可用性 Kafka核心组件: Topic :消息根据Topic进行归类 Producer:发送消息者 Consumer:消息接受者 broker:每个kafka实例(server) Zookeeper:依赖集群保存meta信息。
Kafka集群部署:
1. 集群部署的基本流程
下载安装包、解压安装包、修改配置文件、分发安装包、启动集群
2. Kafka集群部署
1) 下载安装包
http://kafka.apache.org/downloads
2) 解压安装包
[hadoop@hdp08 ~]$ tar zxvf kafka_2.12-1.0.0.tgz -C apps
3) 修改配置文件
[hadoop@hdp08 kafka]$ vi config/server.properties
输入以下内容:
# 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
############################# 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
#用来监听链接的端口,producer或consumer将在此端口建立连接
port=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
# 处理网络请求的线程数量
num.network.threads=3
# 用来处理磁盘IO的线程数量
num.io.threads=8
# 发送socket的缓冲区大小
socket.send.buffer.bytes=102400
# 接受socket的缓冲区大小
socket.receive.buffer.bytes=102400
# The maximum size of a request that the socket server will accept (protection against OOM)
# 请求socket的缓冲区大小
socket.request.max.bytes=104857600
############################# Log Basics #############################
# kafka运行日志存放的路径
log.dirs=/home/hadoop/apps/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
# topic在当前broker上的分片个数
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.
# 用来恢复和清理data下数据的线程数量
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
# segment文件保留的最长时间,超时将被删除
log.retention.hours=168
#滚动生成新的segment文件的较大时间
log.roll.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=hdp08:2181,hdp09:2181,hdp10:2181
# 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.
4) 分发安装包
[hadoop@hdp08 apps]$ scp -r kafka hadoop@hdp09:/home/hadoop/apps
[hadoop@hdp08 apps]$ scp -r kafka hadoop@hdp10:/home/hadoop/apps
依次修改各服务器上配置文件的的broker.id,分别是1,2,3不得重复。
bin/kafka-server-start.sh config/server.properties
bin/kafka-topics.sh --list --zookeeper hdp08:2181
创建topic
bin/kafka-topics.sh --create --zookeeper hdp08:2181 --replication-factor 1 --partitions 3 --topic first
删除topic
bin/kafka-topics.sh --delete --zookeeper hdp08:2181 --topic first
需要server.properties中设置delete.topic.enable=true否则只是标记删除或者直接重启。
通过shell命令发送消息
bin/kafka-console-producer.sh --broker-list hdp08:9092 --topic first
通过shell消费消息
bin/kafka-console-consumer.sh --zookeeper hdp08:2181 --from-beginning --topic first
查看消费位置
bin/kafka-run-class.sh kafka.tools.ConsumerOffsetChecker --zookeeper hdp08:2181 -- group testGroup
查看某个Topic的详情
bin/kafka-topics.sh --topic first --describe --zookeeper hdp08:2181
上一篇: {大数据}Kafka Java API
下一篇: {大数据}Spark Streaming