Hbase简介及Hbase部署、原理和使用介绍，Phoenix使用
Hbase简介及Hbase部署、原理和使用介绍(+phoenix使用)
HBase概述
HBase定义
HBase是一种分布式、可扩展、支持海量数据存储的NoSQL数据库。就像Bigtable利用了Google文件系统（File System）所提供的分布式数据存储一样，HBase在Hadoop之上提供了类似于Bigtable的能力。HBase是Apache的Hadoop项目的子项目。HBase不同于一般的关系数据库，它是一个适合于非结构化数据存储的数据库。另一个不同的是HBase基于列的而不是基于行的模式。
· 是一种面向列簇存储的非关系型数据库。
· 用于存储结构化和非结构化的数据，适用于单表非关系型数据的存储，不适合做关联查询，类似JOIN等操作。
· 基于HDFS，数据持久化存储的体现形式是HFile，存放于DataNode中，被ResionServer以region的形式进行管理。
· 延迟较低，接入在线业务使用，面对大量的企业数据，HBase可以实现单表大量数据的存储，同时提供了高效的数据访问速度。
HBase数据模型
逻辑上，HBase的数据模型同关系型数据库很类似，数据存储在一张表中，有行有列。但从HBase的底层物理存储结构（K-V）来看，HBase更像是一个multi-dimensional map。
HBase数据模型
1. Name Space
命名空间，类似于关系型数据库的DatabBase概念，每个命名空间下有多个表。HBase有两个自带的命名空间，分别是hbase和default，hbase中存放的是HBase内置的表，default表是用户默认使用的命名空间。
2.Region
类似于关系型数据库的表概念。不同的是，HBase定义表时只需要声明列族即可，不需要声明具体的列。这意味着，往HBase写入数据时，字段可以动态、按需指定。因此，和关系型数据库相比，HBase能够轻松应对字段变更的场景。
3.Row
HBase表中的每行数据都由一个RowKey和多个Column（列）组成，数据是按照RowKey的字典顺序存储的，并且查询数据时只能根据RowKey进行检索，所以RowKey的设计十分重要。
Row Key
Rowkey 的概念和 mysql 中的主键类似，Hbase 使用 Rowkey 来唯一的区分某一行的数据。Hbase只支持3种查询方式： 1、基于Rowkey的单行查询，2、基于Rowkey的范围扫描 ，3、全表扫描
因此，Rowkey对Hbase的性能影响非常大。设计的时候要兼顾基于Rowkey的单行查询也要键入Rowkey的范围扫描。
4.Column
HBase中的每个列都由Column Family(列族)和Column Qualifier（列限定符）进行限定，例如info：name，info：age。建表时，只需指明列族，而列限定符无需预先定义。
Column Family（列簇）
Hbase 通过列簇划分数据的存储，列簇下面可以包含任意多的列，实现灵活的数据存取。列簇是由一个一个的列组成（任意多），在列数据为空的情况下，不会占用存储空间。
Hbase 创建表的时候必须指定列簇。就像关系型数据库创建的时候必须指定具体的列是一样的。
Hbase的列簇不是越多越好，官方推荐的是列簇最好小于或者等于3。一般是1个列簇。
新的列簇成员（列）可以随后动态加入，Family下面可以有多个Qualifier，所以可以简单的理解为，HBase中的列是二级列，也就是说Family是第一级列，Qualifier是第二级列。
5.Time Stamp
用于标识数据的不同版本（version），每条数据写入时，如果不指定时间戳，系统会自动为其加上该字段，其值为写入HBase的时间。
6.Cell
由{rowkey, column Family：column Qualifier, time Stamp} 唯一确定的单元。cell中的数据是没有类型的，全部是字节数组形式存贮。
HBase逻辑存储
HBase物理存储
HBase入门架构
【注意】：
这里先简单了解一下大致思路即可，后续部署完毕和简单的操作体验后，再对照架构图梳理原理和思路，对架构认知才会清晰，所以这里看个概念，了解一下有些什么组件。
1.Region Server
Region Server为 Region的管理者，其实现类为HRegionServer，主要作用如下:
对于数据的操作：get, put, delete；
对于Region的操作：splitRegion、compactRegion。
2.Master
Master是所有Region Server的管理者，其实现类为HMaster，主要作用如下：
对于表的操作：create, delete, alter
对于RegionServer的操作：分配regions到每个RegionServer，监控每个RegionServer的状态，负载均衡和故障转移。
3.Zookeeper
HBase通过Zookeeper来做Master的高可用、RegionServer的监控、元数据的入口以及集群配置的维护等工作。
4.HDFS
HDFS为HBase提供最终的底层数据存储服务，同时为HBase提供高可用的支持。
HBase安装部署
HBase安装准备
安装部署前，需要已经具备如下环境
-
java环境 # 必备
-
/etc/hosts 主机解析 # 把相关几台服务器的主机名和ip解析
11.8.37.50 ops01
11.8.36.63 ops02
11.8.36.76 ops03
11.8.38.86 ops04 -
Zookeeper # 存储元数据的入口以及集群配置的维护
Zookeeper 相关介绍部署连接：https://blog.csdn.net/wt334502157/article/details/115213645
-
Hadoop # 利用hdfs存储数据
Hadoop 相关介绍部署连接：https://blog.csdn.net/wt334502157/article/details/114916871
-
上传安装包
hbase官网：http://hbase.apache.org/
hbase所有版本官网下载：http://archive.apache.org/dist/hbase/
本次部署实验版本为2.0.5：http://archive.apache.org/dist/hbase/2.0.5/hbase-2.0.5-bin.tar.gz
phoenix下载地址：http://archive.apache.org/dist/phoenix/
(phoenix 提前下载，工具后续需要用到，Phoenix是HBase的开源SQL皮肤工具)
phoenix本次部署实验版本5.0.0：http://archive.apache.org/dist/phoenix/apache-phoenix-5.0.0-HBase-2.0/bin/apache-phoenix-5.0.0-HBase-2.0-bin.tar.gz
环境检查：
# 相关服务器java环境
wangting@ops01:/home/wangting >java -version
openjdk version "1.8.0_232"
OpenJDK Runtime Environment (build 1.8.0_232-b09)
OpenJDK 64-Bit Server VM (build 25.232-b09, mixed mode)
# 相关服务器均配置hosts解析
wangting@ops01:/home/wangting >cat /etc/hosts
127.0.0.1 ydt-cisp-ops01
127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4
::1 localhost localhost.localdomain localhost6 localhost6.localdomain6
11.16.0.176 rancher.mydomain.com
11.8.38.123 www.tongtongcf.com
# ops集群
11.8.37.50 ops01
11.8.36.63 ops02
11.8.36.76 ops03
11.8.38.86 ops04
# 检查集群的zookeeper状态
wangting@ops01:/home/wangting >for i in ops01 ops02 ops03 ; do echo ===== $i ===== && ssh $i netstat -tnlpu | grep -E "2181|2888|3888";done
===== ops01 ===== # follow
tcp6 0 0 11.8.37.50:3888 :::* LISTEN 41773/java
tcp6 0 0 :::2181 :::* LISTEN 41773/java
===== ops02 ===== # leader
tcp6 0 0 11.8.36.63:3888 :::* LISTEN 33012/java
tcp6 0 0 :::2181 :::* LISTEN 33012/java
tcp6 0 0 11.8.36.63:2888 :::* LISTEN 33012/java
===== ops03 ===== # follow
tcp6 0 0 11.8.36.76:3888 :::* LISTEN 102422/java
tcp6 0 0 :::2181 :::* LISTEN 102422/java
wangting@ops01:/home/wangting >
# 查看集群已经启动的java应用，如果脚本在几个服务器逐个执行 [wangting@ops01:/home/wangting >jps ]命令即可
wangting@ops01:/home/wangting >jpsall.sh # hadoop相关服务都正常运行着
============= ops01 =============
42305 Kafka
70611 DataNode
70437 NameNode
110869 JobHistoryServer
72582 RunJar
117864 Jps
71290 NodeManager
76269 RunJar
41773 QuorumPeerMain
72319 RunJar
============= ops02 =============
33012 QuorumPeerMain
66996 Jps
40603 NodeManager
40476 ResourceManager
33518 Kafka
85150 DataNode
============= ops03 =============
52849 DataNode
121382 NodeManager
102886 Kafka
102422 QuorumPeerMain
52969 SecondaryNameNode
7486 Jps
============= ops04 =============
103152 Jps
11914 DataNode
12171 NodeManager
=====================================
正常配置:
ops01 : NameNode | DataNode / NodeManager
ops02 : DataNode / ResourceManager | NodeManager
ops03 : SecondaryNameNode | DataNode / NodeManager
ops04 : NodeManager / DataNode
# 查看一下hdfs集群信息状态，当前4台服务器ops01|ops02|ops03|ops04 (实验3台机器即可)
wangting@ops01:/home/wangting >hadoop dfsadmin -report
WARNING: Use of this script to execute dfsadmin is deprecated.
WARNING: Attempting to execute replacement "hdfs dfsadmin" instead.
2021-05-09 16:09:15,947 INFO [main] Configuration.deprecation (Configuration.java:logDeprecation(1395)) - No unit for dfs.client.datanode-restart.timeout(30) assuming SECONDS
Configured Capacity: 348732002304 (324.78 GB)
Present Capacity: 260076236800 (242.21 GB)
DFS Remaining: 258633764864 (240.87 GB)
DFS Used: 1442471936 (1.34 GB)
DFS Used%: 0.55%
Replicated Blocks:
Under replicated blocks: 0
Blocks with corrupt replicas: 0
Missing blocks: 0
Missing blocks (with replication factor 1): 0
Low redundancy blocks with highest priority to recover: 0
Pending deletion blocks: 0
Erasure Coded Block Groups:
Low redundancy block groups: 0
Block groups with corrupt internal blocks: 0
Missing block groups: 0
Low redundancy blocks with highest priority to recover: 0
Pending deletion blocks: 0
-------------------------------------------------
Live datanodes (4):
Name: 11.8.36.63:9866 (ops02)
Hostname: ops02
Decommission Status : Normal
Configured Capacity: 47549591552 (44.28 GB)
DFS Used: 462950400 (441.50 MB)
Non DFS Used: 10877906944 (10.13 GB)
DFS Remaining: 33769746432 (31.45 GB)
DFS Used%: 0.97%
DFS Remaining%: 71.02%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Sun May 09 16:09:15 CST 2021
Last Block Report: Sun May 09 12:30:23 CST 2021
Num of Blocks: 113
Name: 11.8.36.76:9866 (ops03)
Hostname: ops03
Decommission Status : Normal
Configured Capacity: 47549591552 (44.28 GB)
DFS Used: 465338368 (443.78 MB)
Non DFS Used: 7783776256 (7.25 GB)
DFS Remaining: 36861489152 (34.33 GB)
DFS Used%: 0.98%
DFS Remaining%: 77.52%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Sun May 09 16:09:14 CST 2021
Last Block Report: Sun May 09 11:46:50 CST 2021
Num of Blocks: 123
Name: 11.8.37.50:9866 (ops01)
Hostname: ops01
Decommission Status : Normal
Configured Capacity: 206083227648 (191.93 GB)
DFS Used: 480792576 (458.52 MB)
Non DFS Used: 49684766720 (46.27 GB)
DFS Remaining: 147036725248 (136.94 GB)
DFS Used%: 0.23%
DFS Remaining%: 71.35%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Sun May 09 16:09:14 CST 2021
Last Block Report: Sun May 09 16:00:38 CST 2021
Num of Blocks: 175
Name: 11.8.38.86:9866 (ops04)
Hostname: ops04
Decommission Status : Normal
Configured Capacity: 47549591552 (44.28 GB)
DFS Used: 33390592 (31.84 MB)
Non DFS Used: 4111409152 (3.83 GB)
DFS Remaining: 40965804032 (38.15 GB)
DFS Used%: 0.07%
DFS Remaining%: 86.15%
Configured Cache Capacity: 0 (0 B)
Cache Used: 0 (0 B)
Cache Remaining: 0 (0 B)
Cache Used%: 100.00%
Cache Remaining%: 0.00%
Xceivers: 1
Last contact: Sun May 09 16:09:14 CST 2021
Last Block Report: Sun May 09 14:57:26 CST 2021
Num of Blocks: 117
HBase安装
# 准备使用的安装包
wangting@ops01:/opt/software >ll | grep -E "hbase|phoenix"
-rw-r--r-- 1 wangting wangting 436868323 May 9 17:11 apache-phoenix-5.0.0-HBase-2.0-bin.tar.gz
-rw-r--r-- 1 wangting wangting 132569269 May 9 16:27 hbase-2.0.5-bin.tar.gz
wangting@ops01:/opt/software >
# 解压目录至/opt/module/
wangting@ops01:/opt/software >tar -zxvf hbase-2.0.5-bin.tar.gz -C /opt/module/
wangting@ops01:/opt/software >
wangting@ops01:/opt/software >cd /opt/module/hbase-2.0.5/conf/
# 修改hbase-env.sh,打开HBASE_MANAGES_ZK的注释,并修改为false
wangting@ops01:/opt/module/hbase-2.0.5/conf >vim hbase-env.sh
export HBASE_MANAGES_ZK=false
# [注意:]设置HBASE_MANAGES_ZK=false,功能为表示禁止使用HBase自带的Zookeeper,用自建的zk集群
# 修改配置文件hbase-site.xml ，引入必要配置功能
wangting@ops01:/opt/module/hbase-2.0.5/conf >vim hbase-site.xml
<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>hbase.rootdir</name>
<value>hdfs://ops01:8020/hbase</value>
</property>
<property>
<name>hbase.cluster.distributed</name>
<value>true</value>
</property>
<property>
<name>hbase.zookeeper.quorum</name>
<value>ops01,ops02,ops03</value>
</property>
<property>
<name>hbase.unsafe.stream.capability.enforce</name>
<value>false</value>
</property>
<property>
<name>hbase.wal.provider</name>
<value>filesystem</value>
</property>
<property>
<name>hbase.master.maxclockskew</name>
<value>180000</value>
</property>
</configuration>
wangting@ops01:/opt/module/hbase-2.0.5/conf >
# 修改regionservers，配置集群区域主机信息，切记已经配置了hosts文件中的解析，否则服务和zk都会连接不上
wangting@ops01:/opt/module/hbase-2.0.5/conf >vim regionservers
ops01
ops02
ops03
wangting@ops01:/opt/module/hbase-2.0.5/conf >
# 将hbase安装目录改名，切换目录方便
wangting@ops01:/opt/module/hbase-2.0.5/conf >cd /opt/module/
wangting@ops01:/opt/module >mv hbase-2.0.5/ hbase
# 将hadoop相关配置文件软链至hbase的配置目录下
wangting@ops01:/opt/module/hbase-2.0.5/conf >ls /opt/module/hadoop-3.1.3/etc/hadoop/core-site.xml
/opt/module/hadoop-3.1.3/etc/hadoop/core-site.xml
wangting@ops01:/opt/module >ln -s /opt/module/hadoop-3.1.3/etc/hadoop/core-site.xml /opt/module/hbase/conf/core-site.xml
wangting@ops01:/opt/module >ls /opt/module/hadoop-3.1.3/etc/hadoop/hdfs-site.xml
/opt/module/hadoop-3.1.3/etc/hadoop/hdfs-site.xml
wangting@ops01:/opt/module >ln -s /opt/module/hadoop-3.1.3/etc/hadoop/hdfs-site.xml /opt/module/hbase/conf/hdfs-site.xml
wangting@ops01:/opt/module >cd /opt/module/hbase/conf/
wangting@ops01:/opt/module/hbase/conf >ll
total 40
lrwxrwxrwx 1 wangting wangting 49 May 10 11:43 core-site.xml -> /opt/module/hadoop-3.1.3/etc/hadoop/core-site.xml
-rw-r--r-- 1 wangting wangting 1811 Mar 18 2019 hadoop-metrics2-hbase.properties
-rw-r--r-- 1 wangting wangting 4271 Mar 18 2019 hbase-env.cmd
-rw-r--r-- 1 wangting wangting 7236 May 10 11:36 hbase-env.sh
-rw-r--r-- 1 wangting wangting 2257 Mar 18 2019 hbase-policy.xml
-rw-r--r-- 1 wangting wangting 1434 May 10 11:39 hbase-site.xml
lrwxrwxrwx 1 wangting wangting 49 May 10 11:44 hdfs-site.xml -> /opt/module/hadoop-3.1.3/etc/hadoop/hdfs-site.xml
-rw-r--r-- 1 wangting wangting 4977 Mar 18 2019 log4j.properties
-rw-r--r-- 1 wangting wangting 19 May 10 11:40 regionservers
wangting@ops01:/opt/module/hbase/conf >
# 修改环境变量/etc/profile，增加hbase信息
wangting@ops01:/opt/module/hbase/conf >sudo vim /etc/profile
#hbase
export HBASE_HOME=/opt/module/hbase
export PATH=$PATH:$HBASE_HOME/bin
wangting@ops01:/opt/module/hbase/conf >source /etc/profile
wangting@ops01:/opt/module/hbase/conf >
# 将配置好的hbase安装目录分发至其它服务器
wangting@ops01:/opt/module/hbase/conf >scp -r /opt/module/hbase ops02:/opt/module/
wangting@ops01:/opt/module/hbase/conf >scp -r /opt/module/hbase ops03:/opt/module/
# 配置ops02的环境变量
wangting@ops02:/opt/module >sudo vim /etc/profile
[sudo] password for wangting:
wangting@ops02:/opt/module >source /etc/profile
wangting@ops02:/opt/module >
# 配置ops03的环境变量
wangting@ops03:/opt/module >sudo vim /etc/profile
[sudo] password for wangting:
wangting@ops03:/opt/module >source /etc/profile
wangting@ops03:/opt/module >
# 启动服务前查看服务器时间是否异常，不同步需要同步时间
wangting@ops01:/opt/module/hbase >for i in ops01 ops02 ops03; do echo $i && ssh $i date|awk -F" " '{print $4}' ;done
ops01
11:53:25
ops02
11:53:25
ops03
11:53:25
wangting@ops01:/opt/module/hbase >
# 启动服务
wangting@ops01:/opt/module/hbase >start-hbase.sh
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/hbase/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
running master, logging to /opt/module/hbase/logs/hbase-wangting-master-ops01.out
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/hbase/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
ops03: +======================================================================+
ops03: | Error: JAVA_HOME is not set |
ops03: +----------------------------------------------------------------------+
ops03: | Please download the latest Sun JDK from the Sun Java web site |
ops03: | > http://www.oracle.com/technetwork/java/javase/downloads |
ops03: | |
ops03: | HBase requires Java 1.8 or later. |
ops03: +======================================================================+
ops01: +======================================================================+
ops01: | Error: JAVA_HOME is not set |
ops01: +----------------------------------------------------------------------+
ops01: | Please download the latest Sun JDK from the Sun Java web site |
ops01: | > http://www.oracle.com/technetwork/java/javase/downloads |
ops01: | |
ops01: | HBase requires Java 1.8 or later. |
ops01: +======================================================================+
ops02: +======================================================================+
ops02: | Error: JAVA_HOME is not set |
ops02: +----------------------------------------------------------------------+
ops02: | Please download the latest Sun JDK from the Sun Java web site |
ops02: | > http://www.oracle.com/technetwork/java/javase/downloads |
ops02: | |
ops02: | HBase requires Java 1.8 or later. |
ops02: +======================================================================+
# 服务启动发现有JAVA_HOME识别不到的情况
wangting@ops01:/opt/module/hbase >
# 停止hbase服务，解决问题
wangting@ops01:/opt/module/hbase >stop-hbase.sh
stopping hbase...
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/hbase/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
wangting@ops01:/opt/module/hbase >
# 找不到JAVA_HOME ,需要修改一下hbase-env.sh 3台服务器都需要操作
# 增加真实的JAVA_HOME路径保存
wangting@ops01:/opt/module/hbase/conf >tail -4 hbase-env.sh
# java
export JAVA_HOME=/usr/jdk1.8.0_131/
# 再次启动服务
wangting@ops01:/opt/module/hbase/conf >start-hbase.sh
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/hbase/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
running master, logging to /opt/module/hbase/logs/hbase-wangting-master-ops01.out
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/hbase/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
ops01: running regionserver, logging to /opt/module/hbase/bin/../logs/hbase-wangting-regionserver-ops01.out
ops03: running regionserver, logging to /opt/module/hbase/bin/../logs/hbase-wangting-regionserver-ops03.out
ops02: running regionserver, logging to /opt/module/hbase/bin/../logs/hbase-wangting-regionserver-ops02.out
服务start启动后，先大致浏览一下运行环境
官方文档手册：http://hbase.apache.org/book.html
从官方文档手册查阅端口介绍：
- hbase.master.port 16000
- hbase.master.info.port 16010
- hbase.regionserver.port 16020
- hbase.regionserver.info.port 16030
# 查看一下相关端口是否都已经成功开启
wangting@ops01:/opt/module/hbase/conf >for i in ops01 ops02 ops03; do echo === $i === && ssh $i netstat -tnlpu|grep -E "16000|16010|16020|16030" ;done
=== ops01 ===
tcp6 0 0 11.8.37.50:16020 :::* LISTEN 66421/java
tcp6 0 0 :::16030 :::* LISTEN 66421/java
tcp6 0 0 11.8.37.50:16000 :::* LISTEN 66222/java
tcp6 0 0 :::16010 :::* LISTEN 66222/java
=== ops02 ===
tcp6 0 0 11.8.37.50:16020 :::* LISTEN 66421/java
tcp6 0 0 :::16030 :::* LISTEN 66421/java
tcp6 0 0 11.8.37.50:16000 :::* LISTEN 66222/java
tcp6 0 0 :::16010 :::* LISTEN 66222/java
=== ops03 ===
tcp6 0 0 11.8.37.50:16020 :::* LISTEN 66421/java
tcp6 0 0 :::16030 :::* LISTEN 66421/java
tcp6 0 0 11.8.37.50:16000 :::* LISTEN 66222/java
tcp6 0 0 :::16010 :::* LISTEN 66222/java
打开浏览器访问验证一下效果（windows没有配置域名解析，这里需要直接输入ip地址加端口）：
到此，服务安装部署完毕
HBase简单操作入门
# 进入HBase客户端命令行,命令行操作仅仅为了熟悉一些常用功能有哪些，真实场景大多都是用工具来操作
wangting@ops01:/opt/module/hbase/conf >hbase shell
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/hbase/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
HBase Shell
Use "help" to get list of supported commands.
Use "exit" to quit this interactive shell.
For Reference, please visit: http://hbase.apache.org/2.0/book.html#shell
Version 2.0.5, r76458dd074df17520ad451ded198cd832138e929, Mon Mar 18 00:41:49 UTC 2019
Took 0.0036 seconds
hbase(main):001:0>
# 查看命令行帮助，大致熟悉一下有哪些类型的操作命令
hbase(main):002:0* help
# 查看当前数据库中有哪些表，相当于sql的show tables
hbase(main):004:0* list
TABLE
0 row(s)
Took 0.4673 seconds
=> []
# 创建表，注意创建表的时候只需要表名和列族，因为column是可随意增加的，建表无需考虑
hbase(main):006:0* create 'ZTbigdata','info'
Created table ZTbigdata
Took 1.3820 seconds
=> Hbase::Table - ZTbigdata
# 向表中插入数据，类似sql的insert
hbase(main):007:0>
hbase(main):008:0* put 'ZTbigdata','1001','info:company','caitong'
Took 0.1842 seconds
hbase(main):009:0> put 'ZTbigdata','1001','info:usercode','00100000001'
Took 0.0075 seconds
hbase(main):010:0> put 'ZTbigdata','1002','info:name','dongbei'
Took 0.0063 seconds
hbase(main):011:0> put 'ZTbigdata','1002','info:type','quanshang'
Took 0.0061 seconds
hbase(main):012:0> put 'ZTbigdata','1002','info:usercode','002002002'
Took 0.0069 seconds
hbase(main):013:0>
# 查看表中数据，ROW中的类似于主键，查对应的ROW能查到对应行的信息
hbase(main):030:0> scan 'ZTbigdata'
ROW COLUMN+CELL
1001 column=info:company, timestamp=1620636573247, value=caitong
1001 column=info:usercode, timestamp=1620636580325, value=00100000001
1002 column=info:name, timestamp=1620636587121, value=dongbei
1002 column=info:type, timestamp=1620636593149, value=quanshang
1002 column=info:usercode, timestamp=1620636600145, value=002002002
2 row(s)
Took 0.9372 seconds
# 条件查询
hbase(main):031:0> scan 'ZTbigdata',{
STARTROW => '1001', STOPROW => '1001'}
ROW COLUMN+CELL
1001 column=info:company, timestamp=1620636573247, value=caitong
1001 column=info:usercode, timestamp=1620636580325, value=00100000001
1 row(s)
Took 0.0213 seconds
hbase(main):032:0> scan 'ZTbigdata',{
STARTROW => '1001'}
ROW COLUMN+CELL
1001 column=info:company, timestamp=1620636573247, value=caitong
1001 column=info:usercode, timestamp=1620636580325, value=00100000001
1002 column=info:name, timestamp=1620636587121, value=dongbei
1002 column=info:type, timestamp=1620636593149, value=quanshang
1002 column=info:usercode, timestamp=1620636600145, value=002002002
2 row(s)
Took 0.0129 seconds
# 查看表结构
hbase(main):034:0> describe 'ZTbigdata'
Table ZTbigdata is ENABLED
ZTbigdata
COLUMN FAMILIES DESCRIPTION
{
NAME => 'info', VERSIONS => '1', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_WRITE => 'false', DATA_BLOCK_ENCODING => 'NONE', TTL => 'FOREVER', MIN_VERSIONS => '0', RE
PLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_BLOOMS_ON_WRITE => 'false', PREFETCH_BLOCKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE => 'true', BLOCKSIZE => '65536'
}
1 row(s)
Took 0.0584 seconds
# 更新指定字段的数据
hbase(main):035:0> put 'ZTbigdata','1001','info:company','caitongnew'
Took 0.0816 seconds
hbase(main):036:0> put 'ZTbigdata','1001','info:usercode','00100000002'
Took 0.0071 seconds
hbase(main):037:0> scan 'ZTbigdata'
ROW COLUMN+CELL
1001 column=info:company, timestamp=1620637070160, value=caitongnew
1001 column=info:usercode, timestamp=1620637077504, value=00100000002
1002 column=info:name, timestamp=1620636587121, value=dongbei
1002 column=info:type, timestamp=1620636593149, value=quanshang
1002 column=info:usercode, timestamp=1620636600145, value=002002002
2 row(s)
Took 0.0219 seconds
# 查看“指定行”或“指定列族:列”的数据
hbase(main):038:0> get 'ZTbigdata','1001'
COLUMN CELL
info:company timestamp=1620637070160, value=caitongnew
info:usercode timestamp=1620637077504, value=00100000002
1 row(s)
Took 0.0309 seconds
hbase(main):039:0> get 'ZTbigdata','1001','info:company'
COLUMN CELL
info:company timestamp=1620637070160, value=caitongnew
1 row(s)
Took 0.0145 seconds
# 统计表数据行数
hbase(main):040:0> count 'ZTbigdata'
2 row(s)
Took 0.0449 seconds
=> 2
# 删除数据 [ 删除某rowkey的全部数据 ]
hbase(main):041:0> deleteall 'ZTbigdata','1001'
Took 0.0091 seconds
# 删除数据 [ 删除某rowkey的某一列数据 ]
hbase(main):042:0> delete 'ZTbigdata','1002','info:usercode'
Took 0.0081 seconds
# 清空表数据
hbase(main):043:0> truncate 'ZTbigdata'
Truncating 'ZTbigdata' table (it may take a while):
Disabling table...
Truncating table...
Took 2.0349 seconds
# [注意:] 清空表的操作顺序为先disable，然后再truncate
# 删除表 - 第一步:让该表为disable状态
hbase(main):044:0> disable 'ZTbigdata'
Took 0.7933 seconds
# 删除表 - 第二步:drop这个表
hbase(main):045:0> drop 'ZTbigdata'
Took 0.2539 seconds
# 再次查看表，此时ZTbigdata表已经没了
hbase(main):046:0> list
TABLE
0 row(s)
Took 0.0064 seconds
=> []
# 再次创建表，尝试直接drop表查看返回结果
hbase(main):047:0> create 'ZTbigdata','info'
Created table ZTbigdata
Took 0.7455 seconds
=> Hbase::Table - ZTbigdata
hbase(main):048:0> list
TABLE
ZTbigdata
1 row(s)
Took 0.0085 seconds
=> ["ZTbigdata"]
# 如果不先更改disable状态直接drop，会抛出ERROR
hbase(main):049:0> drop 'ZTbigdata'
ERROR: Table ZTbigdata is enabled. Disable it first.
Drop the named table. Table must first be disabled:
hbase> drop 't1'
hbase> drop 'ns1:t1'
Took 0.0203 seconds
借助图形界面上信息，验证操作记录
创建的表能在界面上查看
System Tables中能查看到所有表的meta元数据存储信息
【注意1】:
在hbase shell命令行操作时，如果出现操作行不是0> 结尾， 是*结尾，这时候可以输入2个 ‘ ’ 来恢复
hbase(main):044:0*
hbase(main):045:0* ‘’
=> ""
hbase(main):046:0> # 回到这种状态可以正常交互命令
【注意2】：
在我们启动hbase集群服务时，start-hbase.sh 在集群的哪台执行均可，但是在哪台执行，就意味着哪台就是master，浏览器中访问时，用master加16010端口访问
【注意3】：
start-hbase.sh是集群启动方式，也可以通过
hbase-daemon.sh start master
hbase-daemon.sh start regionserver
来逐个服务器启动master和regionserver
HBase进阶和原理解析
架构原理
- StoreFile
保存实际数据的物理文件，StoreFile以HFile的形式存储在HDFS上。每个Store会有一个或多个StoreFile（HFile），数据在每个StoreFile中都是有序的。 - MemStore
写缓存，由于HFile中的数据要求是有序的，所以数据是先存储在MemStore中，排好序后，等到达刷写时机才会刷写到HFile，每次刷写都会形成一个新的HFile。 - WAL
由于数据要经MemStore排序后才能刷写到HFile，但把数据保存在内存中会有很高的概率导致数据丢失，为了解决这个问题，数据会先写在一个叫做Write-Ahead logfile的文件中，然后再写入MemStore中。所以在系统出现故障的时候，数据可以通过这个日志文件重建。
数据写流程
写流程：
-
Client查看缓存，是否有Meta的cache；没有时则先访问zookeeper，获取hbase:meta表位于哪个Region Server。zookeeper返回meta表的元数据信息其中包含存储位置，例如meta表存储在Region Server: ops01上
-
访问对应的Region Server: ops01，从而获取hbase:meta表数据，根据读请求的namespace:table/rowkey，查询出目标数据位于哪个Region Server中的哪个Region中。并将该table的region信息以及meta表的位置信息缓存在客户端的meta cache，方便下次访问。
-
与目标Region Server进行通讯；
-
将数据顺序写入（追加）到WAL；
-
将数据写入对应的MemStore，数据会在MemStore进行排序；
-
向客户端发送ack；
-
等达到MemStore的刷写时机后，将数据刷写到HFile。
MemStore Flush
MemStore刷写时机：
- 当某个memstroe的大小达到了hbase.hregion.memstore.flush.size（默认值128M），其所在region的所有memstore都会刷写。
当memstore的大小达到了
hbase.hregion.memstore.flush.size（默认值128M）
hbase.hregion.memstore.block.multiplier（默认值4）
时，会阻止继续往该memstore写数据。 - 当region server中memstore的总大小达到
java_heapsize
hbase.regionserver.global.memstore.size（默认值0.4）
hbase.regionserver.global.memstore.size.upper.limit（默认值0.95），
region会按照其所有memstore的大小顺序（由大到小）依次进行刷写。直到region server中所有memstore的总大小减小到hbase.regionserver.global.memstore.size.lower.limit以下。
当region server中memstore的总大小达到
java_heapsize*hbase.regionserver.global.memstore.size（默认值0.4）
时，会阻止继续往所有的memstore写数据。 - 到达自动刷写的时间，也会触发memstore flush。自动刷新的时间间隔由该属性进行配置hbase.regionserver.optionalcacheflushinterval（默认1小时）。
- 当WAL文件的数量超过hbase.regionserver.max.logs，region会按照时间顺序依次进行刷写，直到WAL文件数量减小到hbase.regionserver.max.log以下
数据读流程
读流程:
- Client先访问zookeeper，获取hbase:meta表位于哪个Region Server。
- 访问对应的Region Server，获取hbase:meta表，根据读请求的namespace:table/rowkey，查询出目标数据位于哪个Region Server中的哪个Region中。并将该table的region信息以及meta表的位置信息缓存在客户端的meta cache，方便下次访问。
- 与目标Region Server进行通讯；
- 分别在Block Cache（读缓存），MemStore和Store File（HFile）中查询目标数据，并将查到的所有数据进行合并。此处所有数据是指同一条数据的不同版本（time stamp）或者不同的类型（Put/Delete）。
- 将从文件中查询到的数据块（Block，HFile数据存储单元，默认大小为64KB）缓存到Block Cache。
- 将合并后的最终结果返回给客户端。
StoreFile Compaction
由于memstore每次刷写都会生成一个新的HFile，且同一个字段的不同版本（timestamp）和不同类型（Put/Delete）有可能会分布在不同的HFile中，因此查询时需要遍历所有的HFile。为了减少HFile的个数，以及清理掉过期和删除的数据，会进行StoreFile Compaction。
Compaction分为两种，分别是Minor Compaction和Major Compaction。Minor Compaction会将临近的若干个较小的HFile合并成一个较大的HFile，但不会清理过期和删除的数据。Major Compaction会将一个Store下的所有的HFile合并成一个大HFile，并且会清理掉过期和删除的数据。
Region Split
默认情况下，每个Table起初只有一个Region，随着数据的不断写入，Region会自动进行拆分。刚拆分时，两个子Region都位于当前的Region Server，但处于负载均衡的考虑，HMaster有可能会将某个Region转移给其他的Region Server。
Region Split时机：
1)当1个region中的某个Store下所有StoreFile的总大小超过hbase.hregion.max.filesize，该Region就会进行拆分（0.94版本之前）。
2)当1个region中的某个Store下所有StoreFile的总大小超过Min(R^2 * “hbase.hregion.memstore.flush.size”,hbase.hregion.max.filesize")，该Region就会进行拆分，其中R为当前Region Server中属于该Table的个数（0.94版本之后）。
HBase整合Phoenix使用
Phoenix简介
Phoenix定义
Phoenix是HBase的开源SQL皮肤。可以使用标准JDBC API代替HBase客户端API来创建表，插入数据和查询HBase数据。
Phoenix特点
1） 容易集成：如Spark，Hive，Pig，Flume和Map Reduce；
2） 操作简单：DML命令以及通过DDL命令创建和操作表和版本化增量更改；
3） 支持HBase二级索引创建。
Phoenix架构
Phoenix安装部署
# 安装包
wangting@ops01:/home/wangting >cd /opt/software/
wangting@ops01:/opt/software >ll | grep phoenix
-rw-r--r-- 1 wangting wangting 436868323 May 9 17:11 apache-phoenix-5.0.0-HBase-2.0-bin.tar.gz
# 解压
wangting@ops01:/opt/software >tar -zxvf apache-phoenix-5.0.0-HBase-2.0-bin.tar.gz -C /opt/module/
wangting@ops01:/opt/software >cd /opt/module/
wangting@ops01:/opt/module >ll
total 44
drwxr-xr-x 5 wangting wangting 4096 Jun 27 2018 apache-phoenix-5.0.0-HBase-2.0-bin
drwxrwxr-x 2 wangting wangting 4096 Apr 4 11:01 datas
drwxr-xr-x 12 wangting wangting 4096 Apr 24 16:37 flume
-rw-rw-r-- 1 wangting wangting 30 Apr 25 11:33 group.log
drwxr-xr-x 12 wangting wangting 4096 Mar 12 11:38 hadoop-3.1.3
drwxrwxr-x 8 wangting wangting 4096 May 10 11:55 hbase
drwxrwxr-x 11 wangting wangting 4096 Apr 2 15:14 hive
drwxr-xr-x 7 wangting wangting 4096 Apr 29 11:07 kafka
drwxrwxr-x 3 wangting wangting 4096 Apr 10 16:25 tez
drwxrwxr-x 5 wangting wangting 4096 Apr 2 15:03 tez-0.9.2_bak0410
drwxr-xr-x 8 wangting wangting 4096 Mar 25 11:02 zookeeper-3.5.7
# 改名
wangting@ops01:/opt/module >mv apache-phoenix-5.0.0-HBase-2.0-bin phoenix
wangting@ops01:/opt/module >cd phoenix/
wangting@ops01:/opt/module/phoenix >
# 复制server包和client包到hbase集群各节点的lib目录下
wangting@ops01:/opt/module/phoenix >cp phoenix-5.0.0-HBase-2.0-server.jar /opt/module/hbase/lib/
wangting@ops01:/opt/module/phoenix >scp phoenix-5.0.0-HBase-2.0-server.jar ops02:/opt/module/hbase/lib/
phoenix-5.0.0-HBase-2.0-server.jar 100% 40MB 112.8MB/s 00:00
wangting@ops01:/opt/module/phoenix >scp phoenix-5.0.0-HBase-2.0-server.jar ops03:/opt/module/hbase/lib/
phoenix-5.0.0-HBase-2.0-server.jar 100% 40MB 117.3MB/s 00:00
wangting@ops01:/opt/module/phoenix >cp phoenix-5.0.0-HBase-2.0-client.jar /opt/module/hbase/lib/
wangting@ops01:/opt/module/phoenix >scp phoenix-5.0.0-HBase-2.0-client.jar ops02:/opt/module/hbase/lib/
phoenix-5.0.0-HBase-2.0-client.jar 100% 129MB 115.3MB/s 00:01
wangting@ops01:/opt/module/phoenix >scp phoenix-5.0.0-HBase-2.0-client.jar ops03:/opt/module/hbase/lib/
phoenix-5.0.0-HBase-2.0-client.jar 100% 129MB 117.0MB/s 00:01
wangting@ops01:/opt/module/phoenix >
# 添加环境变量
wangting@ops01:/opt/module/phoenix >sudo vim /etc/profile
#phoenix
export PHOENIX_HOME=/opt/module/phoenix
export PATH=$PATH:$PHOENIX_HOME/bin
wangting@ops01:/opt/module/phoenix >source /etc/profile
# 检查一下zookeeper的2181端口运行状态
wangting@ops01:/opt/module/phoenix >for i in ops01 ops02 ops03 ;do ssh $i netstat -tnlpu|grep 2181;done
tcp6 0 0 :::2181 :::* LISTEN 41773/java
tcp6 0 0 :::2181 :::* LISTEN 41914/java
tcp6 0 0 :::2181 :::* LISTEN 52733/java
# 重启hbase集群
wangting@ops01:/opt/module/phoenix >stop-hbase.sh
stopping hbase.........
wangting@ops01:/opt/module/phoenix >start-hbase.sh
# 启动Phoenix 指定zookeeper集群
wangting@ops01:/opt/module/phoenix >sqlline.py ops01,ops02,ops03:2181
Setting property: [incremental, false]
Setting property: [isolation, TRANSACTION_READ_COMMITTED]
issuing: !connect jdbc:phoenix:ops01,ops02,ops03:2181 none none org.apache.phoenix.jdbc.PhoenixDriver
Connecting to jdbc:phoenix:ops01,ops02,ops03:2181
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/module/phoenix/phoenix-5.0.0-HBase-2.0-client.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/module/hadoop-3.1.3/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
21/05/13 15:32:18 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Connected to: Phoenix (version 5.0)
Driver: PhoenixEmbeddedDriver (version 5.0)
Autocommit status: true
Transaction isolation: TRANSACTION_READ_COMMITTED
Building list of tables and columns for tab-completion (set fastconnect to true to skip)...
133/133 (100%) Done
Done
sqlline version 1.2.0
0: jdbc:phoenix:ops01,ops02,ops03:2181>
# Phoenix和hive使用方式一样，部署一个节点则使用一个节点，实验一个节点即可，如果多个服务器部署，分发一下
wangting@ops01:/opt/module/phoenix >scp -r /opt/module/phoenix ops02:/opt/module/
wangting@ops01:/opt/module/phoenix >scp -r /opt/module/phoenix ops03:/opt/module/
wangting@ops01:/opt/module/phoenix >scp -r /opt/module/phoenix ops04:/opt/module/
##############
wangting@ops02:/opt/module/phoenix >sudo vim /etc/profile
wangting@ops02:/opt/module/phoenix >source /etc/profile
wangting@ops02:/opt/module/phoenix >
##############
wangting@ops03:/opt/module/phoenix >sudo vim /etc/profile
wangting@ops03:/opt/module/phoenix >source /etc/profile
wangting@ops03:/opt/module/phoenix >
##############
wangting@ops04:/opt/module/phoenix >sudo vim /etc/profile
wangting@ops04:/opt/module/phoenix >source /etc/profile
wangting@ops04:/opt/module/phoenix >
Phoenix Shell操作
-- 查询表
0: jdbc:phoenix:ops01,ops02,ops03:2181> !table
+------------+--------------+-------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+---------+
| TABLE_CAT | TABLE_SCHEM | TABLE_NAME | TABLE_TYPE | REMARKS | TYPE_NAME | SELF_REFERENCING_COL_NAME | REF_GENERATION | INDEX_STATE | IMMUTABLE_ROWS | SALT_BUCKETS | MULTI_TENANT | VIEW_STATEMENT | VIEW_TYPE | INDEX_T |
+------------+--------------+-------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+---------+
| | SYSTEM | CATALOG | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | FUNCTION | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | LOG | SYSTEM TABLE | | | | | | true | 32 | false | | | |
| | SYSTEM | SEQUENCE | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | STATS | SYSTEM TABLE | | | | | | false | null | false | | | |
+------------+--------------+-------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+---------+
0: jdbc:phoenix:ops01,ops02,ops03:2181>
-- 创建表
0: jdbc:phoenix:ops01,ops02,ops03:2181> CREATE TABLE IF NOT EXISTS ztdata(id VARCHAR primary key,name VARCHAR);
No rows affected (1.324 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181> CREATE TABLE IF NOT EXISTS us_population (
. . . . . . . . . . . . . . . . . . . > State CHAR(2) NOT NULL,
. . . . . . . . . . . . . . . . . . . > City VARCHAR NOT NULL,
. . . . . . . . . . . . . . . . . . . > Population BIGINT
. . . . . . . . . . . . . . . . . . . > CONSTRAINT my_pk PRIMARY KEY (state, city));
No rows affected (1.3 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181>
-- 向表内插入数据
0: jdbc:phoenix:ops01,ops02,ops03:2181> upsert into ztdata values('1001','caitong');
1 row affected (0.107 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181> upsert into ztdata values('1002','guangfa');
1 row affected (0.012 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181> upsert into ztdata values('1003','fangzheng');
1 row affected (0.009 seconds)
-- 查询表中数据
0: jdbc:phoenix:ops01,ops02,ops03:2181> select * from ztdata;
+-------+------------+
| ID | NAME |
+-------+------------+
| 1001 | caitong |
| 1002 | guangfa |
| 1003 | fangzheng |
+-------+------------+
3 rows selected (0.051 seconds)
-- 条件查询
0: jdbc:phoenix:ops01,ops02,ops03:2181> select * from ztdata where id='1001';
+-------+----------+
| ID | NAME |
+-------+----------+
| 1001 | caitong |
+-------+----------+
1 row selected (0.021 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181> select * from ztdata where id='1002';
+-------+----------+
| ID | NAME |
+-------+----------+
| 1002 | guangfa |
+-------+----------+
1 row selected (0.02 seconds)
-- 删除数据条目
0: jdbc:phoenix:ops01,ops02,ops03:2181> delete from ztdata where id='1001';
1 row affected (0.016 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181> select * from ztdata;
+-------+------------+
| ID | NAME |
+-------+------------+
| 1002 | guangfa |
| 1003 | fangzheng |
+-------+------------+
2 rows selected (0.023 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181>
-- 删表
0: jdbc:phoenix:ops01,ops02,ops03:2181> !table
+------------+--------------+----------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+------+
| TABLE_CAT | TABLE_SCHEM | TABLE_NAME | TABLE_TYPE | REMARKS | TYPE_NAME | SELF_REFERENCING_COL_NAME | REF_GENERATION | INDEX_STATE | IMMUTABLE_ROWS | SALT_BUCKETS | MULTI_TENANT | VIEW_STATEMENT | VIEW_TYPE | INDE |
+------------+--------------+----------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+------+
| | SYSTEM | CATALOG | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | FUNCTION | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | LOG | SYSTEM TABLE | | | | | | true | 32 | false | | | |
| | SYSTEM | SEQUENCE | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | STATS | SYSTEM TABLE | | | | | | false | null | false | | | |
| | | US_POPULATION | TABLE | | | | | | false | null | false | | | |
| | | ZTDATA | TABLE | | | | | | false | null | false | | | |
+------------+--------------+----------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+------+
0: jdbc:phoenix:ops01,ops02,ops03:2181> drop table ztdata;
No rows affected (1.415 seconds)
0: jdbc:phoenix:ops01,ops02,ops03:2181> !table
+------------+--------------+----------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+------+
| TABLE_CAT | TABLE_SCHEM | TABLE_NAME | TABLE_TYPE | REMARKS | TYPE_NAME | SELF_REFERENCING_COL_NAME | REF_GENERATION | INDEX_STATE | IMMUTABLE_ROWS | SALT_BUCKETS | MULTI_TENANT | VIEW_STATEMENT | VIEW_TYPE | INDE |
+------------+--------------+----------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+------+
| | SYSTEM | CATALOG | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | FUNCTION | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | LOG | SYSTEM TABLE | | | | | | true | 32 | false | | | |
| | SYSTEM | SEQUENCE | SYSTEM TABLE | | | | | | false | null | false | | | |
| | SYSTEM | STATS | SYSTEM TABLE | | | | | | false | null | false | | | |
| | | US_POPULATION | TABLE | | | | | | false | null | false | | | |
+------------+--------------+----------------+---------------+----------+------------+----------------------------+-----------------+--------------+-----------------+---------------+---------------+-----------------+------------+------+
0: jdbc:phoenix:ops01,ops02,ops03:2181>
-- 退出命令行
0: jdbc:phoenix:ops01,ops02,ops03:2181> !quit
Closing: org.apache.phoenix.jdbc.PhoenixConnection
wangting@ops01:/opt/module/phoenix >