From 7e4605f82dbdb18ed96d92989becb5a7100bdc65 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E7=BD=97=E7=A5=A5?= <1366971433@qq.com>
Date: Thu, 4 Apr 2019 16:02:51 +0800
Subject: [PATCH] =?UTF-8?q?phoenix=E7=AE=80=E5=8D=95=E4=BD=BF=E7=94=A8?=
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---
README.md | 18 +-
notes/Hbase Shell.md | 2 +
notes/Hbase的SQL层——Phoenix.md | 251 ++++++++++++++++++
notes/Hbase系统架构及数据结构.md | 16 +-
notes/installation/Hbase基本环境搭建.md | 24 +-
pictures/Phoenix-create-table.png | Bin 0 -> 33410 bytes
pictures/Phoenix-delete.png | Bin 0 -> 16148 bytes
pictures/Phoenix-hadoop.png | Bin 0 -> 82841 bytes
pictures/Phoenix-java-api-result.png | Bin 0 -> 25302 bytes
pictures/Phoenix-select.png | Bin 0 -> 14144 bytes
pictures/Phoenix-update.png | Bin 0 -> 19530 bytes
pictures/hbase-web-ui-phoenix.png | Bin 0 -> 93518 bytes
pictures/phoenix-core-jar.png | Bin 0 -> 45905 bytes
pictures/phoenix-shell.png | Bin 0 -> 51807 bytes
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create mode 100644 notes/Hbase的SQL层——Phoenix.md
create mode 100644 pictures/Phoenix-create-table.png
create mode 100644 pictures/Phoenix-delete.png
create mode 100644 pictures/Phoenix-hadoop.png
create mode 100644 pictures/Phoenix-java-api-result.png
create mode 100644 pictures/Phoenix-select.png
create mode 100644 pictures/Phoenix-update.png
create mode 100644 pictures/hbase-web-ui-phoenix.png
create mode 100644 pictures/phoenix-core-jar.png
create mode 100644 pictures/phoenix-shell.png
diff --git a/README.md b/README.md
index 34f53d8..4221e59 100644
--- a/README.md
+++ b/README.md
@@ -36,7 +36,7 @@
Oozie Sqoop Azkaban Hbase HBase Kafka Zookeeper Scala 4.5 条件过滤
+一、Phoenix简介 二、Phoenix安装 2.1 下载并解压 2.2 拷贝Jar包 2.3 重启 Region Servers 2.4 启动Phoenix 2.5 启动结果 三、Phoenix 简单使用 3.1 创建表 3.2 插入数据 3.3 修改数据 3.4 删除数据 3.5 查询数据 3.6 退出命令 3.7 扩展 四、Phoenix Java API 4.1 引入Phoenix core JAR包 4.2 简单的Java API实例
+
+## 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。
+
+
+
+
+
+## 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：
+>
+> - 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
+> - restart the region servers
+> - 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
+
+### 2.1 下载并解压
+
+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`
+
+```shell
+# 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
+# 解压
+tar tar apache-phoenix-4.14.0-cdh5.14.2-bin.tar.gz
+```
+
+### 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。
+
+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
+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
+
+```shell
+# 停止Hbase
+stop-hbase.sh
+# 启动Hbase
+start-hbase.sh
+```
+
+### 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:
+
++ 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
+
+```shell
+# ./sqlline.py hadoop001:2181
+```
+
+### 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`或`!tables`查看当前所有表的信息
+
+
+
+
+
+## 三、Phoenix 简单使用
+
+### 3.1 创建表
+
+```sql
+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));
+```
+
+
+
+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：
+
+
+
+### 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`
+
+```shell
+UPSERT INTO us_population VALUES('NY','New York',8143197);
+UPSERT INTO us_population VALUES('CA','Los Angeles',3844829);
+UPSERT INTO us_population VALUES('IL','Chicago',2842518);
+UPSERT INTO us_population VALUES('TX','Houston',2016582);
+UPSERT INTO us_population VALUES('PA','Philadelphia',1463281);
+UPSERT INTO us_population VALUES('AZ','Phoenix',1461575);
+UPSERT INTO us_population VALUES('TX','San Antonio',1256509);
+UPSERT INTO us_population VALUES('CA','San Diego',1255540);
+UPSERT INTO us_population VALUES('TX','Dallas',1213825);
+UPSERT INTO us_population VALUES('CA','San Jose',912332);
+```
+
+### 3.3 修改数据
+
+```sql
+-- 插入主键相同的数据就视为更新
+UPSERT INTO us_population VALUES('NY','New York',999999);
+```
+
+
+
+### 3.4 删除数据
+
+```sql
+DELETE FROM us_population WHERE city='Dallas';
+```
+
+
+
+### 3.5 查询数据
+
+```sql
+SELECT state as "州",count(city) as "市",sum(population) as "热度"
+FROM us_population
+GROUP BY state
+ORDER BY sum(population) DESC;
+```
+
+
+
+
+
+### 3.6 退出命令
+
+```sql
+!quit
+```
+
+
+
+### 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：
+
++ 语法（Grammar）：https://phoenix.apache.org/language/index.html
+
++ 函数（Functions）：http://phoenix.apache.org/language/functions.html
+
++ 数据类型（Datatypes）：http://phoenix.apache.org/language/datatypes.html
+
++ 序列（Sequences）:http://phoenix.apache.org/sequences.html
+
++ 联结查询（Joins）：http://phoenix.apache.org/joins.html
+
+
+
+## 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
+
+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
+
+
+ org.apache.phoenix
+ phoenix-core
+ 4.14.0-cdh5.14.2
+
+```
+
+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
+
+
+
+### 4.2 简单的Java API实例
+
+```java
+import java.sql.Connection;
+import java.sql.DriverManager;
+import java.sql.PreparedStatement;
+import java.sql.ResultSet;
+
+
+public class PhoenixJavaApi {
+
+ public static void main(String[] args) throws Exception {
+
+ // 加载数据库驱动
+ Class.forName("org.apache.phoenix.jdbc.PhoenixDriver");
+
+ /*
+ * 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
+ */
+ Connection connection = DriverManager.getConnection("jdbc:phoenix:192.168.200.226:2181");
+
+ PreparedStatement statement = connection.prepareStatement("SELECT * FROM us_population");
+
+ ResultSet resultSet = statement.executeQuery();
+
+ while (resultSet.next()) {
+ System.out.println(resultSet.getString("city") + " "
+ + resultSet.getInt("population"));
+ }
+
+ statement.close();
+ connection.close();
+ }
+}
+```
+
+结果如下：
+
+
+
+
+
+# 参考资料
+
+1. http://phoenix.apache.org/
\ No newline at end of file
diff --git a/notes/Hbase系统架构及数据结构.md b/notes/Hbase系统架构及数据结构.md
index 84e28da..c82ee66 100644
--- a/notes/Hbase系统架构及数据结构.md
+++ b/notes/Hbase系统架构及数据结构.md
@@ -27,7 +27,7 @@
### 2.1 Row Key (行键)
-Row Key是用来检索记录的主键。访问Hbase Table中的行，只有三种方式：
+Row Key是用来检索记录的主键。访问HBase Table中的行，只有三种方式：
+ 通过单个Row Key访问
@@ -35,7 +35,7 @@ Row Key是用来检索记录的主键。访问Hbase Table中的行，只有三
+ 全表扫描
-Row Key (行键)可以是任意字符串(最大长度是 64KB，实际应用中长度一般为 10-100bytes)，在Hbase内部，Row Key保存为字节数组。存储时，数据按照Row Key的字典序(byte order)排序存储。设计key时，要充分排序存储这个特性，将经常一起读取的行存储放到一起(位置相关性)。
+Row Key (行键)可以是任意字符串(最大长度是 64KB，实际应用中长度一般为 10-100bytes)，在HBase内部，Row Key保存为字节数组。存储时，数据按照Row Key的字典序(byte order)排序存储。设计key时，要充分排序存储这个特性，将经常一起读取的行存储放到一起(位置相关性)。
需要注意以下两点：
@@ -47,7 +47,7 @@ Row Key (行键)可以是任意字符串(最大长度是 64KB，实际应用中
### 2.2 Column Family（列族）
-hbase表中的每个列（Column），都归属与某个列族。列族是表的schema的一部分(列不是)，必须在使用表之前定义。列名都以列族作为前缀。例如`courses:history`，`courses:math`都属于`courses `这个列族。
+HBase表中的每个列（Column），都归属与某个列族。列族是表的schema的一部分(列不是)，必须在使用表之前定义。列名都以列族作为前缀。例如`courses:history`，`courses:math`都属于`courses `这个列族。
@@ -71,7 +71,7 @@ Cell是行，列族和列限定符的组合，并包含值和时间戳。
### 2.6 Timestamp(时间戳)
-HBase 中通过`row`和`columns`确定的为一个存储单元称为Cell。每个Cell都保存着同一份数据的多个版本。版本通过时间戳来索引。时间戳的类型是 64位整型。时间戳可以由hbase(在数据写入时自动 )赋值，此时时间戳是精确到毫秒的当前系统时间。时间戳也可以由客户显式赋值。如果应用程序要避免数据版本冲突，就必须自己生成具有唯一性的时间戳。每个Cell中，不同版本的数据按照时间倒序排序，即最新的数据排在最前面。
+HBase 中通过`row`和`columns`确定的为一个存储单元称为Cell。每个Cell都保存着同一份数据的多个版本。版本通过时间戳来索引。时间戳的类型是 64位整型。时间戳可以由HBase(在数据写入时自动 )赋值，此时时间戳是精确到毫秒的当前系统时间。时间戳也可以由客户显式赋值。如果应用程序要避免数据版本冲突，就必须自己生成具有唯一性的时间戳。每个Cell中，不同版本的数据按照时间倒序排序，即最新的数据排在最前面。
@@ -79,7 +79,7 @@ HBase 中通过`row`和`columns`确定的为一个存储单元称为Cell。每
### 2.1 Regions
-Hbase Table中的所有行都按照Row Key的字典序排列。HBase Tables 通过行键的范围（row key range）被水平切分成多个Region, 一个Region包含了在start key 和 end key之间的所有行。
+HBase Table中的所有行都按照Row Key的字典序排列。HBase Tables 通过行键的范围（row key range）被水平切分成多个Region, 一个Region包含了在start key 和 end key之间的所有行。
@@ -87,7 +87,7 @@ Hbase Table中的所有行都按照Row Key的字典序排列。HBase Tables 通
-Region是Hbase中**分布式存储和负载均衡的最小单元**。最小单元就表示不同的Region可以分布在不同的Region Server上。但一个Region是不会拆分到多个server上的。
+Region是HBase中**分布式存储和负载均衡的最小单元**。最小单元就表示不同的Region可以分布在不同的Region Server上。但一个Region是不会拆分到多个server上的。
@@ -122,7 +122,7 @@ HBase系统遵循Master/Salve架构，由三种不同类型的组件组成。
3. 实时监控Region Server的状态，将Region server的上线和下线信息实时通知给Master
-4. 存储Hbase的schema,包括有哪些Table，每个Table有哪些Column Family
+4. 存储HBase的schema,包括有哪些Table，每个Table有哪些Column Family
**Master**
@@ -192,7 +192,7 @@ HBase系统遵循Master/Salve架构，由三种不同类型的组件组成。
如果再次读取，客户端将使用缓存来获取META 的位置及之前的行键。这样时间久了，客户端不需要查询META表，除非Region移动所导致的缓存失效，这样的话，则将会重新查询更新缓存。
-注：META 表是Hbase中一张特殊的表，它保存了Hbase中所有数据表的Region位置信息，ZooKeeper存储着META 表的位置。
+注：META 表是HBase中一张特殊的表，它保存了HBase中所有数据表的Region位置信息，ZooKeeper存储着META 表的位置。
diff --git a/notes/installation/Hbase基本环境搭建.md b/notes/installation/Hbase基本环境搭建.md
index 67bdaf0..9ae75d0 100644
--- a/notes/installation/Hbase基本环境搭建.md
+++ b/notes/installation/Hbase基本环境搭建.md
@@ -10,7 +10,7 @@
### 1.1 JDK版本说明
-Hbase 需要依赖JDK环境，同时Hbase 2.0+ 以上版本不再支持JDK 1.7 ，需要安装JDK 1.8+ 。JDK 安装方式见本仓库：
+HBase 需要依赖JDK环境，同时HBase 2.0+ 以上版本不再支持JDK 1.7 ，需要安装JDK 1.8+ 。JDK 安装方式见本仓库：
> [Linux环境下JDK安装](https://github.com/heibaiying/BigData-Notes/blob/master/notes/installation/Linux下JDK安装.md)
@@ -52,7 +52,7 @@ export PATH=$HBASE_HOME/bin:$PATH
# source /etc/profile
```
-### 2.3 进行Hbase相关配置
+### 2.3 进行HBase相关配置
修改安装目录下的`conf/hbase-env.sh`,指定JDK的安装路径：
@@ -86,9 +86,9 @@ export JAVA_HOME=/usr/java/jdk1.8.0_201
`hbase.unsafe.stream.capability.enforce`: 使用本地文件系统存储，不使用HDFS的情况下需要禁用此配置，设置为false。
-### 2.4 启动Hbase
+### 2.4 启动HBase
-由于已经将Hbase的bin目录配置到环境变量，直接使用以下命令启动
+由于已经将HBase的bin目录配置到环境变量，直接使用以下命令启动
```shell
# start-hbase.sh
@@ -104,7 +104,7 @@ export JAVA_HOME=/usr/java/jdk1.8.0_201
15500 HMaster
```
-验证方式二：访问Hbase Web UI 页面，默认端口为`16010`
+验证方式二：访问HBaseWeb UI 页面，默认端口为`16010`
@@ -120,13 +120,13 @@ export JAVA_HOME=/usr/java/jdk1.8.0_201
### 3.2 Hbase版本选择
-Hbase的版本必须要与Hadoop的版本兼容，不然会发生各种Jar包冲突。
+HBase的版本必须要与Hadoop的版本兼容，不然会发生各种Jar包冲突。
-由于我们Hadoop采用的版本为`hadoop-2.6.0-cdh5.15.2`,所以这里保持CDH版本一致，我们选择的Hbase版本为`hbase-1.2.0-cdh5.15.2` ，Hbase 1.2 的安装需要依赖JDK 1.7+ 。所有软件版本如下：
+由于我们Hadoop采用的版本为`hadoop-2.6.0-cdh5.15.2`,所以这里保持CDH版本一致，我们选择的HBase版本为`hbase-1.2.0-cdh5.15.2` ，HBase 1.2 的安装需要依赖JDK 1.7+ 。所有软件版本如下：
-+ hadoop 版本： hadoop-2.6.0-cdh5.15.2
++ Hadoop 版本： hadoop-2.6.0-cdh5.15.2
-+ hbase 版本： hbase-1.2.0-cdh5.15.2
++ HBase 版本： hbase-1.2.0-cdh5.15.2
+ JDK 版本：JDK 1.8
@@ -163,7 +163,7 @@ export PATH=$HBASE_HOME/bin:$PATH
-### 3.5 进行Hbase相关配置
+### 3.5 进行HBase相关配置
1.修改安装目录下的`conf/hbase-env.sh`,指定JDK的安装路径：
@@ -204,7 +204,7 @@ hadoop001
### 3.6 验证启动是否成功
-验证方式一：JPS 查看进程，其中HMaster,HRegionServer,HQuorumPeer三个进程是Hbase的进程（其中HQuorumPeer是Hbase内置的Zookeeper的进程），其余的为HDFS和YARN的进程。
+验证方式一：JPS 查看进程，其中HMaster,HRegionServer,HQuorumPeer三个进程是HBase的进程（其中HQuorumPeer是Hbase内置的Zookeeper的进程），其余的为HDFS和YARN的进程。
```shell
[root@hadoop001 conf]# jps
@@ -221,6 +221,6 @@ hadoop001
21933 HMaster
```
-验证方式二：访问Hbase Web UI 界面，需要注意的是1.2 版本的Hbase的访问端口为`60010`
+验证方式二：访问HBase Web UI 界面，需要注意的是1.2 版本的HBase的访问端口为`60010`
diff --git a/pictures/Phoenix-create-table.png b/pictures/Phoenix-create-table.png
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