环境配置
| 名称 | 版本 | 下载地址 |
|---|---|---|
| Centos 7.0 | 64x | 百度 |
| Zookeeper | 3.4.5 | |
| Flume | 1.6.0 | |
| Kafka | 2.1.0 |
配置Flume
这里就不介绍了零基础出门右转看Flume的文章
直接贴配置文件
[root@zero239 kafka_2.10-0.10.1.1]# cat /opt/hadoop/apache-flume-1.6.0-bin/conf/kafka-conf.properties
# The configuration file needs to define the sources,
# the channels and the sinks.
# Sources, channels and sinks are defined per agent,
# in this case called 'agent'
agent.sources = r1
agent.channels = c1
agent.sinks = s1
# For each one of the sources, the type is defined
#agent.sources.r1.type = spooldir
#agent.sources.r1.command = /opt/test/logs/data
#agent.sources.r1.fileHeader = true
#agent.sources.r1.channels = c1
agent.sources.r1.type = spooldir
agent.sources.r1.spoolDir = /opt/test/logs/data
agent.sources.r1.fileHeader = true
# Each sink's type must be defined
#agent.sinks.s1.type = logger
agent.sinks.s1.type = org.apache.flume.sink.kafka.KafkaSink
agent.sinks.s1.topic = logstest
agent.sinks.s1.brokerList = zero230:9092
agent.sinks.s1.requiredAcks = 1
agent.sinks.s1.batchSize = 2
# Each channel's type is defined.
agent.channels.c1.type = memory
agent.channels.c1.capacity = 100
agent.sources.r1.channels = c1
agent.sinks.s1.channel = c1
配置Kafka
# 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=2
# 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 = security_protocol://host_name:port
# EXAMPLE:
# listeners = PLAINTEXT://your.host.name:9092
#listeners=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
# The number of threads handling network requests
num.network.threads=3
# 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=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=/opt/hadoop/kafka_2.10-0.10.1.1/logs/tmp
# 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
############################# 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
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=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=zero230:2181,zero231:2181,zero239:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
我已经配置了集群Zookeeper所以在这里我指定是我配置的Zookeeper地址如果你没有配置的话可以直接使用Kafka内置的Zokeeper
启动Kafka验证是否成功
- 启动Zookeeper
如果没有配置集群的这一步跳过 启动Kafka内置Zookeeper
bin/zookeeper-server-start.sh config/zookeeper.properties
3.启动Kafka
server1.properties 为刚刚自己编辑的名称
bin/kafka-server-start.sh config/server1.properties
4.创建一个名为logstest的topic
./bin/kafka-topics.sh --create --zookeeper zero230:2181 --replication-factor 1 --partitions 1 --topic logstest
5.查看Topic是否创建成功
./bin/kafka-topics.sh --list --zookeeper localhost:2181
6.创建一个生产端(相当于是一个已经数据产生的用户吧)这样容易理解
bin/kafka-console-producer.sh --broker-list zero230:9092 --topic logstest
7.创建一个消费端(意思就是可以看到生产者意思就是生产出来的数据可以看到输出)
bin/kafka-console-consumer.sh --zookeeper zero230:2181 --topic logstest --from-beginning
启动验证Flume是否能与Kafka对接
[root@zero239 apache-flume-1.6.0-bin]# ./bin/flume-ng agent --conf conf -f ./conf/kafka-conf.properties -n agent -Dflume.root.logger=INFO,console
对接成功截图
各位同学可以看到在Flumesinks配置中我设置的是Kafka意思就是输出到Kafka中
agent.sinks.s1.type = org.apache.flume.sink.kafka.KafkaSink
agent.sinks.s1.topic = logstest 刚刚创建的Topic名称
agent.sinks.s1.brokerList = zero230:9092 创建生产的机
在这里Flume与Kafka已经整合完毕了。
下节剧透
JAVA实现Kafka读取