格式调整

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luoxiang 2019-05-27 22:40:46 +08:00
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1. [分布式文件存储系统——HDFS](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-HDFS.md) 1. [分布式文件存储系统——HDFS](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-HDFS.md)
2. [分布式计算框架——MapReduce](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-MapReduce.md) 2. [分布式计算框架——MapReduce](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-MapReduce.md)
3. [集群资源管理器——YARN](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-YARN.md) 3. [集群资源管理器——YARN](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hadoop-YARN.md)
4. [Hadoop单机伪集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/hadoop%E5%8D%95%E6%9C%BA%E7%89%88%E6%9C%AC%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) 4. [Hadoop单机伪集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/hadoop单机版本环境搭建.md)
5. [HDFS常用Shell命令](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HDFS常用Shell命令.md) 5. [HDFS常用Shell命令](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HDFS常用Shell命令.md)
6. [HDFS Java API的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HDFS-Java-API.md) 6. [HDFS Java API的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HDFS-Java-API.md)
## 二、Hive ## 二、Hive
1. [数据仓库Hive简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hive.md) 1. [数据仓库Hive简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hive.md)
2. [Linux环境下Hive的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux%E7%8E%AF%E5%A2%83%E4%B8%8BHive%E7%9A%84%E5%AE%89%E8%A3%85%E9%83%A8%E7%BD%B2.md) 2. [Linux环境下Hive的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux环境下Hive的安装部署.md)
4. [Hive CLI和Beeline命令行的基本使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HiveCLI和Beeline命令行的基本使用.md) 4. [Hive CLI和Beeline命令行的基本使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/HiveCLI和Beeline命令行的基本使用.md)
5. [Hive 核心概念讲解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hive核心概念讲解.md) 5. [Hive 核心概念讲解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hive核心概念讲解.md)
6. [Hive 常用DDL操作](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hive常用DDL操作.md) 6. [Hive 常用DDL操作](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hive常用DDL操作.md)
@ -94,53 +94,35 @@
3. [Spark Streaming 整合 Flume](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Spark_Streaming整合Flume.md) 3. [Spark Streaming 整合 Flume](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Spark_Streaming整合Flume.md)
4. [Spark Streaming 整合 Kafka](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Spark_Streaming整合Kafka.md) 4. [Spark Streaming 整合 Kafka](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Spark_Streaming整合Kafka.md)
## 四、Flink ## 四、Storm
TODO
## 五、Storm
1. [Storm和流处理简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm和流处理简介.md) 1. [Storm和流处理简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm和流处理简介.md)
2. [Storm核心概念详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm核心概念详解.md) 2. [Storm核心概念详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm核心概念详解.md)
3. [Storm单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Storm%E5%8D%95%E6%9C%BA%E7%89%88%E6%9C%AC%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) 3. [Storm单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Storm单机版本环境搭建.md)
4. [Storm编程模型详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm编程模型详解.md) 4. [Storm编程模型详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm编程模型详解.md)
5. [Storm项目三种打包方式对比分析](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm三种打包方式对比分析.md) 5. [Storm项目三种打包方式对比分析](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm三种打包方式对比分析.md)
6. [Storm集成Redis详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm集成Redis详解.md) 6. [Storm集成Redis详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm集成Redis详解.md)
7. [Storm集成HDFS/HBase](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm集成HBase和HDFS.md) 7. [Storm集成HDFS/HBase](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm集成HBase和HDFS.md)
8. [Storm集成Kafka](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm集成Kakfa.md) 8. [Storm集成Kafka](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Storm集成Kakfa.md)
## 六、Flume ## 五、Flink
1. [Flume简介及基本使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Flume简介及基本使用.md) TODO
2. [Linux环境下Flume的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux%E4%B8%8BFlume%E7%9A%84%E5%AE%89%E8%A3%85.md)
3. [Flume整合Kafka](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Flume整合Kafka.md)
## 七、Sqoop ## 六、HBase
1. [Sqoop简介与安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Sqoop简介与安装.md)
2. [Sqoop的基本使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Sqoop基本使用.md)
## 八、Azkaban
1. [Azkaban简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Azkaban简介.md)
2. [Azkaban3.x 编译及部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Azkaban%203.x%20%E7%BC%96%E8%AF%91%E5%8F%8A%E9%83%A8%E7%BD%B2.md)
3. [Azkaban Flow 1.0 的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Azkaban%20Flow%201.0%20%E7%9A%84%E4%BD%BF%E7%94%A8.md)
4. [Azkaban Flow 2.0 的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Azkaban%20Flow%202.0%20%E7%9A%84%E4%BD%BF%E7%94%A8.md)
## 九、HBase
1. [Hbase 简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase简介.md) 1. [Hbase 简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase简介.md)
2. [HBase系统架构及数据结构](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase%E7%B3%BB%E7%BB%9F%E6%9E%B6%E6%9E%84%E5%8F%8A%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84.md) 2. [HBase系统架构及数据结构](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase系统架构及数据结构.md)
3. [HBase基本环境搭建Standalone /pseudo-distributed mode](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Hbase%E5%9F%BA%E6%9C%AC%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) 3. [HBase基本环境搭建Standalone /pseudo-distributed mode](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Hbase基本环境搭建.md)
4. [HBase常用Shell命令](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase%20Shell.md) 4. [HBase常用Shell命令](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase_Shell.md)
5. [HBase Java API](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase%20Java%20API.md) 5. [HBase Java API](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase_Java_API.md)
6. [Hbase 过滤器详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase过滤器详解.md) 6. [Hbase 过滤器详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase过滤器详解.md)
7. [HBase 协处理器详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase协处理器详解.md) 7. [HBase 协处理器详解](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase协处理器详解.md)
8. [HBase 容灾与备份](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase%E5%AE%B9%E7%81%BE%E4%B8%8E%E5%A4%87%E4%BB%BD.md) 8. [HBase 容灾与备份](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase容灾与备份.md)
9. [HBase的SQL中间层——Phoenix](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase%E7%9A%84SQL%E5%B1%82%E2%80%94%E2%80%94Phoenix.md) 9. [HBase的SQL中间层——Phoenix](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Hbase的SQL中间层_Phoenix.md)
10. [Spring/Spring Boot 整合 Mybatis + Phoenix](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Spring%2BMybtais%2BPhoenix%E6%95%B4%E5%90%88.md) 10. [Spring/Spring Boot 整合 Mybatis + Phoenix](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Spring+Mybtais+Phoenix整合.md)
## 十、Kafka
## 七、Kafka
1. [Kafka 核心概念介绍](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Kafka核心概念介绍.md) 1. [Kafka 核心概念介绍](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Kafka核心概念介绍.md)
2. [基于Zookeeper搭建Kafka高可用集群](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/基于Zookeeper搭建Kafka高可用集群.md) 2. [基于Zookeeper搭建Kafka高可用集群](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/基于Zookeeper搭建Kafka高可用集群.md)
@ -149,7 +131,7 @@ TODO
5. Kafka 副本机制以及选举原理剖析 5. Kafka 副本机制以及选举原理剖析
6. Kafka的数据可靠性 6. Kafka的数据可靠性
## 十一、Zookeeper ## 、Zookeeper
1. [Zookeeper 简介及核心概念](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Zookeeper简介及核心概念.md) 1. [Zookeeper 简介及核心概念](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Zookeeper简介及核心概念.md)
2. [Zookeeper单机环境和集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Zookeeper单机环境和集群环境搭建.md) 2. [Zookeeper单机环境和集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Zookeeper单机环境和集群环境搭建.md)
@ -157,6 +139,25 @@ TODO
4. [Zookeeper Java 客户端——Apache Curator](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Zookeeper_Java客户端Curator.md) 4. [Zookeeper Java 客户端——Apache Curator](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Zookeeper_Java客户端Curator.md)
5. [Zookeeper ACL权限控制](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Zookeeper_ACL权限控制.md) 5. [Zookeeper ACL权限控制](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Zookeeper_ACL权限控制.md)
## 九、Flume
1. [Flume简介及基本使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Flume简介及基本使用.md)
2. [Linux环境下Flume的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下Flume的安装.md)
3. [Flume整合Kafka](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Flume整合Kafka.md)
## 十、Sqoop
1. [Sqoop简介与安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Sqoop简介与安装.md)
2. [Sqoop的基本使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Sqoop基本使用.md)
## 十一、Azkaban
1. [Azkaban简介](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Azkaban简介.md)
2. [Azkaban3.x 编译及部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Azkaban_3.x_编译及部署.md)
3. [Azkaban Flow 1.0 的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Azkaban_Flow_1.0_的使用.md)
4. [Azkaban Flow 2.0 的使用](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Azkaban_Flow_2.0_的使用.md)
## 十二、Scala ## 十二、Scala
1. [Scala简介及开发环境配置](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Scala简介及开发环境配置.md) 1. [Scala简介及开发环境配置](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Scala简介及开发环境配置.md)
@ -174,8 +175,10 @@ TODO
13. [隐式转换和隐式参数](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Scala隐式转换和隐式参数.md) 13. [隐式转换和隐式参数](https://github.com/heibaiying/BigData-Notes/blob/master/notes/Scala隐式转换和隐式参数.md)
## 十三、公共内容 ## 十三、公共内容
1. [大数据应用常用打包方式](https://github.com/heibaiying/BigData-Notes/blob/master/notes/大数据应用常用打包方式.md) 1. [大数据应用常用打包方式](https://github.com/heibaiying/BigData-Notes/blob/master/notes/大数据应用常用打包方式.md)
<br>
## 后记:bookmark_tabs:

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# Hbase的SQL中间层——Phoenix # Hbase的SQL中间层——Phoenix
<nav> <nav>
<a href="#一Phoenix简介">一、Phoenix简介</a><br/> <a href="#一Phoenix简介">一、Phoenix简介</a><br/>
<a href="#二Phoenix安装">二、Phoenix安装</a><br/> <a href="#二Phoenix安装">二、Phoenix安装</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#21-下载并解压">2.1 下载并解压</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#21-下载并解压">2.1 下载并解压</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#22-拷贝Jar包">2.2 拷贝Jar包</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#22-拷贝Jar包">2.2 拷贝Jar包</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#23-重启-Region-Servers">2.3 重启 Region Servers</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#23-重启-Region-Servers">2.3 重启 Region Servers</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#24-启动Phoenix">2.4 启动Phoenix</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#24-启动Phoenix">2.4 启动Phoenix</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#25-启动结果">2.5 启动结果</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#25-启动结果">2.5 启动结果</a><br/>
<a href="#三Phoenix-简单使用">三、Phoenix 简单使用</a><br/> <a href="#三Phoenix-简单使用">三、Phoenix 简单使用</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#31-创建表">3.1 创建表</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#31-创建表">3.1 创建表</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#32-插入数据">3.2 插入数据</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#32-插入数据">3.2 插入数据</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#33-修改数据">3.3 修改数据</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#33-修改数据">3.3 修改数据</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#34-删除数据">3.4 删除数据</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#34-删除数据">3.4 删除数据</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#35-查询数据">3.5 查询数据</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#35-查询数据">3.5 查询数据</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#36-退出命令">3.6 退出命令</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#36-退出命令">3.6 退出命令</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#37-扩展">3.7 扩展</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#37-扩展">3.7 扩展</a><br/>
<a href="#四Phoenix-Java-API">四、Phoenix Java API</a><br/> <a href="#四Phoenix-Java-API">四、Phoenix Java API</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#41-引入Phoenix-core-JAR包">4.1 引入Phoenix core JAR包</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#41-引入Phoenix-core-JAR包">4.1 引入Phoenix core JAR包</a><br/>
&nbsp;&nbsp;&nbsp;&nbsp;<a href="#42-简单的Java-API实例">4.2 简单的Java API实例</a><br/> &nbsp;&nbsp;&nbsp;&nbsp;<a href="#42-简单的Java-API实例">4.2 简单的Java API实例</a><br/>
</nav> </nav>
## 一、Phoenix简介 ## 一、Phoenix简介
Phoenix是HBase的开源SQL层。使得您可以使用标准JDBC API而不是常规HBase客户端API来操作Hbases上的数据。 Phoenix是HBase的开源SQL层。使得您可以使用标准JDBC API而不是常规HBase客户端API来操作Hbases上的数据。
Phoenix完全使用Java编写作为HBase内嵌的JDBC驱动。Phoenix查询引擎会将SQL查询转换为一个或多个HBase scan并编排并行执行以生成标准的JDBC结果集同时Phoenix还拥有二级索引等Hbase不具备的特性这使得Phoenix具有极好的性能表现。 Phoenix完全使用Java编写作为HBase内嵌的JDBC驱动。Phoenix查询引擎会将SQL查询转换为一个或多个HBase scan并编排并行执行以生成标准的JDBC结果集同时Phoenix还拥有二级索引等Hbase不具备的特性这使得Phoenix具有极好的性能表现。
<div align="center"> <img width="600px" src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-hadoop.png"/> </div> <div align="center"> <img width="600px" src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-hadoop.png"/> </div>
## 二、Phoenix安装 ## 二、Phoenix安装
> 我们可以按照官方安装说明进行安装,官方说明如下: > 我们可以按照官方安装说明进行安装,官方说明如下:
> >
> - download and expand our installation tar > - download and expand our installation tar
> - copy the phoenix server jar that is compatible with your HBase installation into the lib directory of every region server > - copy the phoenix server jar that is compatible with your HBase installation into the lib directory of every region server
> - restart the region servers > - restart the region servers
> - add the phoenix client jar to the classpath of your HBase client > - add the phoenix client jar to the classpath of your HBase client
> - download and setup SQuirrel as your SQL client so you can issue adhoc SQL against your HBase cluster > - download and setup SQuirrel as your SQL client so you can issue adhoc SQL against your HBase cluster
### 2.1 下载并解压 ### 2.1 下载并解压
官方下载地址: http://phoenix.apache.org/download.html 官方下载地址: http://phoenix.apache.org/download.html
官方针对Apache版本和CDH版本的HBase均提供了安装包按需下载即可。这里我们下载的版本为`4.14.0-cdh5.14.2` 官方针对Apache版本和CDH版本的HBase均提供了安装包按需下载即可。这里我们下载的版本为`4.14.0-cdh5.14.2`
```shell ```shell
# 下载 # 下载
wget http://mirror.bit.edu.cn/apache/phoenix/apache-phoenix-4.14.0-cdh5.14.2/bin/apache-phoenix-4.14.0-cdh5.14.2-bin.tar.gz wget http://mirror.bit.edu.cn/apache/phoenix/apache-phoenix-4.14.0-cdh5.14.2/bin/apache-phoenix-4.14.0-cdh5.14.2-bin.tar.gz
# 解压 # 解压
tar tar apache-phoenix-4.14.0-cdh5.14.2-bin.tar.gz tar tar apache-phoenix-4.14.0-cdh5.14.2-bin.tar.gz
``` ```
### 2.2 拷贝Jar包 ### 2.2 拷贝Jar包
按照官方文档的说明需要将phoenix server jar 添加到所有 Region Servers上 Hbase 安装目录的 lib目录下。 按照官方文档的说明需要将phoenix server jar 添加到所有 Region Servers上 Hbase 安装目录的 lib目录下。
这里由于我搭建的是Hbase伪集群所以只需要拷贝到当前机器的HBase的lib目录下。如果是真实集群则使用scp命令分发到所有Region Servers机器上。 这里由于我搭建的是Hbase伪集群所以只需要拷贝到当前机器的HBase的lib目录下。如果是真实集群则使用scp命令分发到所有Region Servers机器上。
```shell ```shell
cp /usr/app/apache-phoenix-4.14.0-cdh5.14.2-bin/phoenix-4.14.0-cdh5.14.2-server.jar /usr/app/hbase-1.2.0-cdh5.15.2/lib cp /usr/app/apache-phoenix-4.14.0-cdh5.14.2-bin/phoenix-4.14.0-cdh5.14.2-server.jar /usr/app/hbase-1.2.0-cdh5.15.2/lib
``` ```
### 2.3 重启 Region Servers ### 2.3 重启 Region Servers
```shell ```shell
# 停止Hbase # 停止Hbase
stop-hbase.sh stop-hbase.sh
# 启动Hbase # 启动Hbase
start-hbase.sh start-hbase.sh
``` ```
### 2.4 启动Phoenix ### 2.4 启动Phoenix
在Phoenix解压目录下的`bin`目录下执行如下命令需要指定Zookeeper的地址: 在Phoenix解压目录下的`bin`目录下执行如下命令需要指定Zookeeper的地址:
+ 如果HBase采用Standalone模式或者伪集群模式搭建则采用内置的 Zookeeper默认端口为2181 + 如果HBase采用Standalone模式或者伪集群模式搭建则采用内置的 Zookeeper默认端口为2181
+ 如果是HBase是集群模式并采用自己搭建的Zookeeper集群则按照自己的实际情况指定端口 + 如果是HBase是集群模式并采用自己搭建的Zookeeper集群则按照自己的实际情况指定端口
```shell ```shell
# ./sqlline.py hadoop001:2181 # ./sqlline.py hadoop001:2181
``` ```
### 2.5 启动结果 ### 2.5 启动结果
启动后则进入了Phoenix交互式SQL命令行可以使用`!table``!tables`查看当前所有表的信息 启动后则进入了Phoenix交互式SQL命令行可以使用`!table``!tables`查看当前所有表的信息
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/phoenix-shell.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/phoenix-shell.png"/> </div>
## 三、Phoenix 简单使用 ## 三、Phoenix 简单使用
### 3.1 创建表 ### 3.1 创建表
```sql ```sql
CREATE TABLE IF NOT EXISTS us_population ( CREATE TABLE IF NOT EXISTS us_population (
state CHAR(2) NOT NULL, state CHAR(2) NOT NULL,
city VARCHAR NOT NULL, city VARCHAR NOT NULL,
population BIGINT population BIGINT
CONSTRAINT my_pk PRIMARY KEY (state, city)); CONSTRAINT my_pk PRIMARY KEY (state, city));
``` ```
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-create-table.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-create-table.png"/> </div>
新建的表会按照特定的规则转换为Hbase上的表关于表的信息可以通过Hbase Web UI 进行查看: 新建的表会按照特定的规则转换为Hbase上的表关于表的信息可以通过Hbase Web UI 进行查看:
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/hbase-web-ui-phoenix.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/hbase-web-ui-phoenix.png"/> </div>
### 3.2 插入数据 ### 3.2 插入数据
Phoenix 中插入数据采用的是`UPSERT`而不是`INSERT`,因为Phoenix并没有更新操作插入相同主键的数据就视为更新所以`UPSERT`就相当于`UPDATE`+`INSERT` Phoenix 中插入数据采用的是`UPSERT`而不是`INSERT`,因为Phoenix并没有更新操作插入相同主键的数据就视为更新所以`UPSERT`就相当于`UPDATE`+`INSERT`
```shell ```shell
UPSERT INTO us_population VALUES('NY','New York',8143197); UPSERT INTO us_population VALUES('NY','New York',8143197);
UPSERT INTO us_population VALUES('CA','Los Angeles',3844829); UPSERT INTO us_population VALUES('CA','Los Angeles',3844829);
UPSERT INTO us_population VALUES('IL','Chicago',2842518); UPSERT INTO us_population VALUES('IL','Chicago',2842518);
UPSERT INTO us_population VALUES('TX','Houston',2016582); UPSERT INTO us_population VALUES('TX','Houston',2016582);
UPSERT INTO us_population VALUES('PA','Philadelphia',1463281); UPSERT INTO us_population VALUES('PA','Philadelphia',1463281);
UPSERT INTO us_population VALUES('AZ','Phoenix',1461575); UPSERT INTO us_population VALUES('AZ','Phoenix',1461575);
UPSERT INTO us_population VALUES('TX','San Antonio',1256509); UPSERT INTO us_population VALUES('TX','San Antonio',1256509);
UPSERT INTO us_population VALUES('CA','San Diego',1255540); UPSERT INTO us_population VALUES('CA','San Diego',1255540);
UPSERT INTO us_population VALUES('TX','Dallas',1213825); UPSERT INTO us_population VALUES('TX','Dallas',1213825);
UPSERT INTO us_population VALUES('CA','San Jose',912332); UPSERT INTO us_population VALUES('CA','San Jose',912332);
``` ```
### 3.3 修改数据 ### 3.3 修改数据
```sql ```sql
-- 插入主键相同的数据就视为更新 -- 插入主键相同的数据就视为更新
UPSERT INTO us_population VALUES('NY','New York',999999); UPSERT INTO us_population VALUES('NY','New York',999999);
``` ```
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-update.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-update.png"/> </div>
### 3.4 删除数据 ### 3.4 删除数据
```sql ```sql
DELETE FROM us_population WHERE city='Dallas'; DELETE FROM us_population WHERE city='Dallas';
``` ```
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-delete.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-delete.png"/> </div>
### 3.5 查询数据 ### 3.5 查询数据
```sql ```sql
SELECT state as "州",count(city) as "市",sum(population) as "热度" SELECT state as "州",count(city) as "市",sum(population) as "热度"
FROM us_population FROM us_population
GROUP BY state GROUP BY state
ORDER BY sum(population) DESC; ORDER BY sum(population) DESC;
``` ```
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-select.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-select.png"/> </div>
### 3.6 退出命令 ### 3.6 退出命令
```sql ```sql
!quit !quit
``` ```
### 3.7 扩展 ### 3.7 扩展
从上面的简单操作中我们可以看出Phoenix 查询语句与我们正常使用的SQL是基本相同的关于Phoenix 支持的语句、数据类型、函数、序列和Oracle中序列类似因为涵盖内容很广可以参考其官方文档官方上有详尽的配图说明的 从上面的简单操作中我们可以看出Phoenix 查询语句与我们正常使用的SQL是基本相同的关于Phoenix 支持的语句、数据类型、函数、序列和Oracle中序列类似因为涵盖内容很广可以参考其官方文档官方上有详尽的配图说明的
+ 语法Grammarhttps://phoenix.apache.org/language/index.html + 语法Grammarhttps://phoenix.apache.org/language/index.html
+ 函数Functionshttp://phoenix.apache.org/language/functions.html + 函数Functionshttp://phoenix.apache.org/language/functions.html
+ 数据类型Datatypeshttp://phoenix.apache.org/language/datatypes.html + 数据类型Datatypeshttp://phoenix.apache.org/language/datatypes.html
+ 序列Sequences:http://phoenix.apache.org/sequences.html + 序列Sequences:http://phoenix.apache.org/sequences.html
+ 联结查询Joinshttp://phoenix.apache.org/joins.html + 联结查询Joinshttp://phoenix.apache.org/joins.html
## 四、Phoenix Java API ## 四、Phoenix Java API
因为Phoenix遵循JDBC规范并提供了对应的数据库驱动PhoenixDriver这使采用Java对其进行操作的时候就如同对其他关系型数据库例如 MySQL操作一样。 因为Phoenix遵循JDBC规范并提供了对应的数据库驱动PhoenixDriver这使采用Java对其进行操作的时候就如同对其他关系型数据库例如 MySQL操作一样。
因为在实际的开发中我们通常都是采用第三方框架比如mybatis,Hibernate,Spring Data 等很少使用原生Java API操作关系型数据库所以这里只给出一个简单的查询作为示例并在下一篇文章中给出Spring boot + mybatis + Phoenix 的整合用例。 因为在实际的开发中我们通常都是采用第三方框架比如mybatis,Hibernate,Spring Data 等很少使用原生Java API操作关系型数据库所以这里只给出一个简单的查询作为示例并在下一篇文章中给出Spring boot + mybatis + Phoenix 的整合用例。
### 4.1 引入Phoenix core JAR包 ### 4.1 引入Phoenix core JAR包
如果是maven项目直接在maven中央仓库找到对应的版本导入依赖即可 如果是maven项目直接在maven中央仓库找到对应的版本导入依赖即可
```xml ```xml
<!-- https://mvnrepository.com/artifact/org.apache.phoenix/phoenix-core --> <!-- https://mvnrepository.com/artifact/org.apache.phoenix/phoenix-core -->
<dependency> <dependency>
<groupId>org.apache.phoenix</groupId> <groupId>org.apache.phoenix</groupId>
<artifactId>phoenix-core</artifactId> <artifactId>phoenix-core</artifactId>
<version>4.14.0-cdh5.14.2</version> <version>4.14.0-cdh5.14.2</version>
</dependency> </dependency>
``` ```
如果是普通项目则可以从Phoenix 解压目录下找到对应的JAR包然后手动引入 如果是普通项目则可以从Phoenix 解压目录下找到对应的JAR包然后手动引入
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/phoenix-core-jar.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/phoenix-core-jar.png"/> </div>
### 4.2 简单的Java API实例 ### 4.2 简单的Java API实例
```java ```java
import java.sql.Connection; import java.sql.Connection;
import java.sql.DriverManager; import java.sql.DriverManager;
import java.sql.PreparedStatement; import java.sql.PreparedStatement;
import java.sql.ResultSet; import java.sql.ResultSet;
public class PhoenixJavaApi { public class PhoenixJavaApi {
public static void main(String[] args) throws Exception { public static void main(String[] args) throws Exception {
// 加载数据库驱动 // 加载数据库驱动
Class.forName("org.apache.phoenix.jdbc.PhoenixDriver"); Class.forName("org.apache.phoenix.jdbc.PhoenixDriver");
/* /*
* 指定数据库地址,格式为 jdbc:phoenix:Zookeeper地址 * 指定数据库地址,格式为 jdbc:phoenix:Zookeeper地址
* 如果HBase采用Standalone模式或者伪集群模式搭建则HBase默认使用内置的Zookeeper默认端口为2181 * 如果HBase采用Standalone模式或者伪集群模式搭建则HBase默认使用内置的Zookeeper默认端口为2181
*/ */
Connection connection = DriverManager.getConnection("jdbc:phoenix:192.168.200.226:2181"); Connection connection = DriverManager.getConnection("jdbc:phoenix:192.168.200.226:2181");
PreparedStatement statement = connection.prepareStatement("SELECT * FROM us_population"); PreparedStatement statement = connection.prepareStatement("SELECT * FROM us_population");
ResultSet resultSet = statement.executeQuery(); ResultSet resultSet = statement.executeQuery();
while (resultSet.next()) { while (resultSet.next()) {
System.out.println(resultSet.getString("city") + " " System.out.println(resultSet.getString("city") + " "
+ resultSet.getInt("population")); + resultSet.getInt("population"));
} }
statement.close(); statement.close();
connection.close(); connection.close();
} }
} }
``` ```
结果如下: 结果如下:
<div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-java-api-result.png"/> </div> <div align="center"> <img src="https://github.com/heibaiying/BigData-Notes/blob/master/pictures/Phoenix-java-api-result.png"/> </div>
# 参考资料 # 参考资料
1. http://phoenix.apache.org/ 1. http://phoenix.apache.org/

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@ -5,56 +5,47 @@
1. [Linux环境下JDK安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下JDK安装.md) 1. [Linux环境下JDK安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下JDK安装.md)
2. [Linux环境下Python安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下Python安装.md) 2. [Linux环境下Python安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下Python安装.md)
### 二、Hadoop ### 二、Hadoop
1. [Hadoop单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/hadoop%E5%8D%95%E6%9C%BA%E7%89%88%E6%9C%AC%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) 1. [Hadoop单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/hadoop单机版本环境搭建.md)
2. Hadoop集群环境搭建
3. 基于Zookeeper搭建Hadoop的HA集群
### 三、Spark ### 三、Spark
1. [Spark单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Spark单机版本环境搭建.md) 1. [Spark单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Spark单机版本环境搭建.md)
2. Spark集群环境搭建
### 四、Storm ### 四、Storm
1. [Storm单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Storm单机版本环境搭建.md) 1. [Storm单机版本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Storm单机版本环境搭建.md)
2. Storm集群环境搭建
### 五、Hbase ### 五、Hbase
1. [Hbase基本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Hbase%E5%9F%BA%E6%9C%AC%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA.md) 1. [Hbase基本环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Hbase基本环境搭建.md)
2. Hbase集群环境搭建
### 六、Flume ### 六、Flume
1. [Linux环境下Flume的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux%E4%B8%8BFlume%E7%9A%84%E5%AE%89%E8%A3%85.md) 1. [Linux环境下Flume的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下Flume的安装.md)
### 七、Azkaban ### 七、Azkaban
1. [Azkaban3.x编译及部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Azkaban%203.x%20%E7%BC%96%E8%AF%91%E5%8F%8A%E9%83%A8%E7%BD%B2.md) 1. [Azkaban3.x编译及部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Azkaban_3.x_编译及部署.md)
### 八、Hive ### 八、Hive
1. [Linux环境下Hive的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux%E7%8E%AF%E5%A2%83%E4%B8%8BHive%E7%9A%84%E5%AE%89%E8%A3%85%E9%83%A8%E7%BD%B2.md) 1. [Linux环境下Hive的安装部署](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux环境下Hive的安装部署.md)
### 九、Zookeeper ### 九、Zookeeper
1. [Zookeeper单机环境和集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Zookeeper单机环境和集群环境搭建.md) 1. [Zookeeper单机环境和集群环境搭建](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Zookeeper单机环境和集群环境搭建.md)
### 十、Kafka ### 十、Kafka
1. [基于Zookeeper搭建Kafka高可用集群](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/基于Zookeeper搭建Kafka高可用集群.md) 1. [基于Zookeeper搭建Kafka高可用集群](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/基于Zookeeper搭建Kafka高可用集群.md)