- 版本 hbase 1.2.0
- 依赖zookeeper
hbase搭建一个单机版集群
datanode-1 数据节点，负责存储实际数据
hmaster-1 hbase主节点
namenode-1 它负责管理文件系统名称空间和bai控制外部客户机du的访问
regionserver-1 主要负责响应用户的请求，向 HDFS 读写数据。RegionServer 运行在 DataNode 服务器上，实现数据的本地性
zookeeper-1 主要用于实现高可靠性（High Availability, HA），包括 HDFS 的 NameNode 和 YARN 的 ResourceManager 的 HA
regionserver-1.vnet hmaster-1.vnet namenode-1.vnet datanode-1.vnet 这些dns需要在本地host进行映射
正常输出是这样的
/opt/hbase/bin/hbase org.apache.hadoop.hbase.util.CompressionTest /root/anaconda-ks.cfg snappy
2020-07-20 08:29:10,204 INFO [main] Configuration.deprecation: hadoop.native.lib is deprecated. Instead, use io.native.lib.available
2020-07-20 08:29:12,100 INFO [main] hfile.CacheConfig: CacheConfig:disabled
2020-07-20 08:29:12,489 INFO [main] compress.CodecPool: Got brand-new compressor [.snappy]
2020-07-20 08:29:12,496 INFO [main] compress.CodecPool: Got brand-new compressor [.snappy]
2020-07-20 08:29:13,391 INFO [main] hfile.CacheConfig: CacheConfig:disabled
2020-07-20 08:29:13,417 INFO [main] compress.CodecPool: Got brand-new decompressor [.snappy]
SUCCESS
异常情况
hbase org.apache.hadoop.hbase.util.CompressionTest ./README.txt snappy
2020-07-20 08:32:58,814 WARN [main] util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2020-07-20 08:32:59,048 INFO [main] hfile.CacheConfig: Created cacheConfig: CacheConfig:disabled
Exception in thread "main" java.lang.UnsatisfiedLinkError: org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()Z
at org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy(Native Method)
at org.apache.hadoop.io.compress.SnappyCodec.checkNativeCodeLoaded(SnappyCodec.java:63)
at org.apache.hadoop.io.compress.SnappyCodec.getCompressorType(SnappyCodec.java:132)
at org.apache.hadoop.io.compress.CodecPool.getCompressor(CodecPool.java:148)
at org.apache.hadoop.io.compress.CodecPool.getCompressor(CodecPool.java:163)
at org.apache.hadoop.hbase.io.compress.Compression$Algorithm.getCompressor(Compression.java:330)
at org.apache.hadoop.hbase.io.encoding.HFileBlockDefaultEncodingContext.<init>(HFileBlockDefaultEncodingContext.java:90)
at org.apache.hadoop.hbase.io.hfile.HFileBlock$Writer.<init>(HFileBlock.java:879)
at org.apache.hadoop.hbase.io.hfile.HFileWriterV2.finishInit(HFileWriterV2.java:126)
at org.apache.hadoop.hbase.io.hfile.HFileWriterV2.<init>(HFileWriterV2.java:118)
at org.apache.hadoop.hbase.io.hfile.HFileWriterV3.<init>(HFileWriterV3.java:67)
at org.apache.hadoop.hbase.io.hfile.HFileWriterV3$WriterFactoryV3.createWriter(HFileWriterV3.java:59)
at org.apache.hadoop.hbase.io.hfile.HFile$WriterFactory.create(HFile.java:309)
at org.apache.hadoop.hbase.util.CompressionTest.doSmokeTest(CompressionTest.java:124)
at org.apache.hadoop.hbase.util.CompressionTest.main(CompressionTest.java:160)
HBase Shell相关命令
hbase shell命令 描述
create 创建表 < create ‘表名’, ‘列族名’, ‘列族名2’,‘列族名N’ >
list 查看所有表 < list all >
describe 显示表详细信息 < describe ‘表名’ >
exists 判断表是否存在 < exists ‘表名’ >
enable 使表有效 < enable ‘表名’ >
disable 使表无效 < disable ‘表名’ >
is_enabled 判断是否启动表 < is_enabled ‘表名’ >
is_disabled 判断是否禁用表 < is_disabled ‘表名’ >
count 统计表中行的数量 < count ‘表名’ >
put 添加记录 < put ‘表名’, ‘row key’, ‘列族1 : 列’, ‘值’ >
get 获取记录(row key下所有) < get ‘表名’, ‘row key’>
get 获取记录(某个列族) < get ‘表名’, ‘row key’, ‘列族’>
get 获取记录(某个列) < get ‘表名’,‘row key’,‘列族:列’ >
delete 删除记录 < delete ‘表名’, ‘row key’, ‘列族:列’ >
deleteall 删除一行 < deleteall ‘表名’,‘row key’>
drop 删除表 <disable ‘表名’> < drop ‘表名’>
alter 修改列族（column family）
incr 增加指定表，行或列的值
truncate 清空表 逻辑为先删除后创建 <truncate ‘表明’>
scan 通过对表的扫描来获取对用的值 <scan ‘表名’>
tools 列出hbase所支持的工具
status 返回hbase集群的状态信息
version 返回hbase版本信息
exit 退出hbase shell
shutdown 关闭hbase集群(与exit不同)
-
查看表有那些rowkey
count "member",INTERVAL=>1
put 'member','mb1','info:id','3' put 'member','mb1','info:age','11' put 'member','mb1','address:city','shangh2ai' put 'member','mb1','address:contry','china' put 'member','mb2','info:id','4' put 'member','mb2','info:age','32' put 'member','mb2','address:city','beijin2g' put 'member','mb2','address:contry','chi2na'
put 'member','mb3','info:id','5' put 'member','mb3','info:age','11' put 'member','mb3','address:city','shangh2ai' put 'member','mb4','address:contry','china' put 'member','mb2','info:id','6' put 'member','mb2','info:age','32' put 'member','mb2','address:city','beijin2g' put 'member','mb2','address:contry','chi2na'
["pma_compressor","pma_deviation","pma_optimization","pma_performance","segment_db0_kafka","value_db0_kafka"],
scan "pma_compressor" scan "pma_deviation" scan "pma_optimization" scan "pma_performance" scan "segment_db0_kafka" scan "value_db0_kafka"
count "pma_compressor_86",INTERVAL=>1
count "pma_compressor",INTERVAL=>1
hbase(main):005:0> get "pma_compressor","d3d9446802a44259755d38e6d163e820_9223370444531575807"
COLUMN CELL
result:compressorConvertEff timestamp=1593655620053, value=?\xEC\xB7\x0A\x17\xDB\xE9\xCB
result:compressorConvertFlow timestamp=1593655620053, value=?\xB4\x8F\xBB\x1Ey\x92\xBE
result:compressorConvertRate timestamp=1593655620053, value=@eF\xB9\xF00\xFF\xFD
result:compressorPressRate timestamp=1593655620053, value=@%yw\xD6\xFC%\xAB
count "pma_deviation",INTERVAL=>1
hbase(main):007:0> get "pma_deviation","ff49740c0bfe60aaea7fa8c8fc362c36_9223370441542975807"
COLUMN CELL
result:287 timestamp=1595312472694, value=\x00\x00\x00\x00\x00\x00\x00\x00
result:368 timestamp=1595312472694, value=\x00\x00\x00\x00\x00\x00\x00\x00
result:881 timestamp=1595312472694, value=\x00\x00\x00\x00\x00\x00\x00\x00
result:dataSet timestamp=1595312472694, value=@$\x00\x00\x00\x00\x00\x00
count "pma_optimization",INTERVAL=>1
hbase(main):002:0> get "pma_optimization","fe771a932abc05affa9d11cb0e2e1d4d_9223370441646775807"
COLUMN CELL
result:615:after timestamp=1595208007555, value=A\x1A\x18\xBD\xEC\x99t\xFE
result:615:before timestamp=1595208007555, value=A\x19\xF0\xA0\x00\x00\x00\x00
result:616:after timestamp=1595208007555, value=A\x1A5$Uh\xE1N
result:616:before timestamp=1595208007555, value=A\x19\xF0\xA0\x00\x00\x00\x00
result:618:after timestamp=1595208007555, value=A\x04*\x80\x00\x00\x00\x00
result:618:before timestamp=1595208007555, value=A\x04*\x80\x00\x00\x00\x00
count "pma_performance",INTERVAL=>1
get "pma_performance","d3d9446802a44259755d38e6d163e820_9223370451184375807"
result:32789 timestamp=1595162393381, value=?\x93\xCE\xE9\xDD~\xCB\xB8
result:32790 timestamp=1595162393397, value=@_\xD0\x00\x00\x00\x00\x00
result:32791 timestamp=1595162393381, value=@e{\xD7\x0A=p\xA4
result:32792 timestamp=1595162393381, value=@\x82\xD333333
result:32793 timestamp=1595162393381, value=@\xAB\xE533333
result:32794 timestamp=1595162393381, value=@\x1Am\xE0\x0D\x1Bqv
result:32795 timestamp=1595162393381, value=?\x96\x18\x04\xD9\x83\x94u
result:32796 timestamp=1595162393397, value=@_\xD0\x00\x00\x00\x00\x00
result:dataSet timestamp=1595162393397, value=@$\x00\x00\x00\x00\x00\x00
result:status timestamp=1595162393397, value=\x00\x00\x00\x00\x00\x00\x00\x00