在centos上实现hbase的高可用性,可以遵循以下步骤:
首先,确保你已经在CentOS上安装了HBase。你可以从Apache HBase官方网站下载并按照官方文档进行安装。
为了实现高可用性,你需要配置HBase集群。以下是一些关键配置:
<<span>configuration></span>
<<span>property></span>
<<span>name></span>hbase.rootdir</<span>name></span>
<<span>value></span>hdfs://namenode:8020/hbase</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.cluster.distributed</<span>name></span>
<<span>value></span>true</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.zookeeper.quorum</<span>name></span>
<<span>value></span>zookeeper1,zookeeper2,zookeeper3</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.zookeeper.property.dataDir</<span>name></span>
<<span>value></span>/var/lib/zookeeper</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.handler.count</<span>name></span>
<<span>value></span>100</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.wal.codec</<span>name></span>
<<span>value></span>org.apache.hadoop.hbase.regionserver.wal.IndexedWALEditCodec</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.writer.impl</<span>name></span>
<<span>value></span>org.apache.hadoop.hbase.regionserver.wal.HLogWriterImpl</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.syncer.count</<span>name></span>
<<span>value></span>1</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.blocksize</<span>name></span>
<<span>value></span>64M</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.period</<span>name></span>
<<span>value></span>300000</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.size</<span>name></span>
<<span>value></span>1073741824</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.jitter</<span>name></span>
<<span>value></span>0</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.writer.impl</<span>name></span>
<<span>value></span>org.apache.hadoop.hbase.regionserver.wal.HLogWriterImpl</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.syncer.count</<span>name></span>
<<span>value></span>1</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.blocksize</<span>name></span>
<<span>value></span>64M</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.period</<span>name></span>
<<span>value></span>300000</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.size</<span>name></span>
<<span>value></span>1073741824</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.jitter</<span>name></span>
<<span>value></span>0</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.writer.impl</<span>name></span>
<<span>value></span>org.apache.hadoop.hbase.regionserver.wal.HLogWriterImpl</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.syncer.count</<span>name></span>
<<span>value></span>1</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.blocksize</<span>name></span>
<<span>value></span>64M</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.period</<span>name></span>
<<span>value></span>300000</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.size</<span>name></span>
<<span>value></span>1073741824</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.jitter</<span>name></span>
<<span>value></span>0</<span>value></span>
</<span>property></span>
</<span>configuration></span>
export HBASE_MANAGES_ZK=true
HBase依赖Zookeeper进行集群管理和协调。确保你已经安装并配置了Zookeeper集群。
tickTime=2000 dataDir=/var/lib/zookeeper clientPort=2181 initLimit=5 syncLimit=2 server.1=zookeeper1:2888:3888 server.2=zookeeper2:2888:3888 server.3=zookeeper3:2888:3888
启动HBase集群之前,确保所有节点都已经正确配置并且Zookeeper集群已经启动。
start-hbase.sh
为了实现HBase Master的高可用性,可以使用HBase自带的HA机制。
bee餐饮点餐外卖小程序是针对餐饮行业推出的一套完整的餐饮解决方案,实现了用户在线点餐下单、外卖、叫号排队、支付、配送等功能,完美的使餐饮行业更高效便捷!功能演示:1、桌号管理登录后台,左侧菜单 “桌号管理”,添加并管理你的桌号信息,添加以后在列表你将可以看到 ID 和 密钥,这两个数据用来生成桌子的二维码2、生成桌子二维码例如上面的ID为 308,密钥为 d3PiIY,那么现在去左侧菜单微信设置
1
<<span>property></span>
<<span>name></span>hbase.master</<span>name></span>
<<span>value></span>master1,master2,master3</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.master.info.port</<span>name></span>
<<span>value></span>16000</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.master.info.bindAddress</<span>name></span>
<<span>value></span>0.0.0.0</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.writer.impl</<span>name></span>
<<span>value></span>org.apache.hadoop.hbase.regionserver.wal.HLogWriterImpl</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.syncer.count</<span>name></span>
<<span>value></span>1</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.blocksize</<span>name></span>
<<span>value></span>64M</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.period</<span>name></span>
<<span>value></span>300000</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.size</<span>name></span>
<<span>value></span>1073741824</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.hlog.roll.jitter</<span>name></span>
<<span>value></span>0</<span>value></span>
</<span>property></span>
确保每个RegionServer都有多个副本,并且配置了自动故障转移。
<<span>property></span>
<<span>name></span>hbase.regionserver.replication</<span>name></span>
<<span>value></span>true</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.replication.endpoint</<span>name></span>
<<span>value></span>replication</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.replication.interval</<span>name></span>
<<span>value></span>30000</<span>value></span>
</<span>property></span>
<<span>property></span>
<<span>name></span>hbase.regionserver.replication.max.log.size</<span>name></span>
<<span>value></span>1073741824</<span>value></span>
</<span>property></span>
配置监控和日志系统,以便及时发现和解决问题。可以使用Prometheus、Grafana等工具进行监控。
最后,进行全面的测试和验证,确保HBase集群的高可用性配置正确并且能够正常工作。
通过以上步骤,你可以在CentOS上实现HBase的高可用性。
以上就是CentOS如何实现HBase的高可用性的详细内容,更多请关注php中文网其它相关文章!
每个人都需要一台速度更快、更稳定的 PC。随着时间的推移,垃圾文件、旧注册表数据和不必要的后台进程会占用资源并降低性能。幸运的是,许多工具可以让 Windows 保持平稳运行。
Copyright 2014-2025 https://www.php.cn/ All Rights Reserved | php.cn | 湘ICP备2023035733号