大数据-Flume的负载均衡
大数据-Flume的负载均衡
cwl_java
发布于 2019-12-26 16:08:40
发布于 2019-12-26 16:08:40
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4. Flume 的负载均衡
负载均衡是用于解决一台机器(一个进程)无法解决所有请求而产生的一种算法。Load balancing Sink Processor 能够实现 load balance 功能，如下图Agent1 是一个路由节点，负责将 Channel 暂存的 Event 均衡到对应的多个 Sink组件上，而每个 Sink 组件分别连接到一个独立的 Agent 上，示例配置， 如下所示：
在此处我们通过三台机器来进行模拟flume的负载均衡 三台机器规划如下：
- node01：采集数据，发送到node02和node03机器上去
- node02：接收node01的部分数据
- node03：接收node01的部分数据.
第一步：开发node01服务器的flume配置
node01服务器配置：
cd /export/servers/apache-flume-1.8.0-bin/conf
vim load_banlancer_client.conf# agent name
<p class="mume-header " id="agent-name"></p>
a1.channels = c1
a1.sources = r1
a1.sinks = k1 k2
# set gruop
<p class="mume-header " id="set-gruop"></p>
a1.sinkgroups = g1
# set channel
<p class="mume-header " id="set-channel"></p>
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
a1.sources.r1.channels = c1
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /export/servers/taillogs/access_log
# set sink1
<p class="mume-header " id="set-sink1"></p>
a1.sinks.k1.channel = c1
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = node02
a1.sinks.k1.port = 52020
# set sink2
<p class="mume-header " id="set-sink2"></p>
a1.sinks.k2.channel = c1
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = node03
a1.sinks.k2.port = 52020
# set sink group
<p class="mume-header " id="set-sink-group"></p>
a1.sinkgroups.g1.sinks = k1 k2
# set failover
<p class="mume-header " id="set-failover"></p>
a1.sinkgroups.g1.processor.type = load_balance
a1.sinkgroups.g1.processor.backoff = true
a1.sinkgroups.g1.processor.selector = round_robin
a1.sinkgroups.g1.processor.selector.maxTimeOut=10000第二步：开发node02服务器的flume配置
cd /export/servers/apache-flume-1.8.0-bin/conf
vim load_banlancer_server.conf# Name the components on this agent
<p class="mume-header " id="name-the-components-on-this-agent"></p>
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# Describe/configure the source
<p class="mume-header " id="describeconfigure-the-source"></p>
a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind = node02
a1.sources.r1.port = 52020
# Describe the sink
<p class="mume-header " id="describe-the-sink"></p>
a1.sinks.k1.type = logger
# Use a channel which buffers events in memory
<p class="mume-header " id="use-a-channel-which-buffers-events-in-memory"></p>
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
# Bind the source and sink to the channel
<p class="mume-header " id="bind-the-source-and-sink-to-the-channel"></p>
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1第三步：开发node03服务器flume配置
node03服务器配置
cd /export/servers/apache-flume-1.8.0-bin/conf
vim load_banlancer_server.conf# Name the components on this agent
<p class="mume-header " id="name-the-components-on-this-agent-1"></p>
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# Describe/configure the source
<p class="mume-header " id="describeconfigure-the-source-1"></p>
a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind = node03
a1.sources.r1.port = 52020
# Describe the sink
<p class="mume-header " id="describe-the-sink-1"></p>
a1.sinks.k1.type = logger
# Use a channel which buffers events in memory
<p class="mume-header " id="use-a-channel-which-buffers-events-in-memory-1"></p>
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
# Bind the source and sink to the channel
<p class="mume-header " id="bind-the-source-and-sink-to-the-channel-1"></p>
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1第四步：准备启动flume服务
启动node03的flume服务
cd /export/servers/apache-flume-1.8.0-bin bin/flume-ng agent -n a1 -c conf -f conf/load_banlancer_server.conf -Dflume.root.logger启动node02的flume服务
cd /export/servers/apache-flume-1.8.0-bin bin/flume-ng agent -n a1 -c conf -f conf/load_banlancer_server.conf -Dflume.root.logger启动node01的flume服务
cd /export/servers/apache-flume-1.8.0-bin bin/flume-ng agent -n a1 -c conf -f conf/load_banlancer_client.conf -Dflume.root.logger第五步：node01服务器运行脚本产生数据
cd /export/servers/shells
sh tail-file.sh本文参与 腾讯云自媒体同步曝光计划，分享自作者个人站点/博客。
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