一、什么是hive元数据? hive元数据就是hive的一些基本的元素,主要包括hive表的基本属性,如下 (1)hive表的数据库名、表名、字段名称与类型、分区字段与类型 (2)表的分区,分区的属性location等 (3)serdeproperties, tblproperties等等 可以通过 desc
一、什么是hive元数据? hive元数据就是hive的一些基本的元素,主要包括hive表的基本属性,如下 (1)hive表的数据库名、表名、字段名称与类型、分区字段与类型 (2)表的分区,分区的属性location等 (3)serdeproperties, tblproperties等等 可以通过 desc formatted tablename 查看表有哪些属性 二、hive默认元数据库Derby(嵌入模式) hive-default.xml通过如下配置设置<name>javax.jdo.option.ConnectionURL</name> <value>jdbc:derby:;databaseName=metastore_db;create=true</value> <description>JDBC connect string for a JDBC metastore</description> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>org.apache.derby.jdbc.EmbeddedDriver</value> <description>Driver class name for a JDBC metastore</description>
property> Apache Derby非常小巧,核心部分derby.jar只有2M,所以既可以做为单独的数据库服务器使用,也可以内嵌在应用程序中使用。所以hive采用了Derby作为一个内嵌的元数据库,可以完成hive安装的简单测试。 hive安装完成之后,就可以在hive shell中执行一些基本的操作,创建表、查询等等。如果你细心的话,就会发现一个问题: 当在某个目录下启动终端,进入hive shell时,hive默认会在当前目录下生成一个derby文件和一个metastore_db目录,这两个文件主要保存刚刚在shell中操作的一些sql的结果,比如新建的表、添加的分区等等 这种存储方式的带来弊端 1.在同一个目录下同时只能有一个hive客户端能使用数据库 2.切换目录启动新的shell,无法查看之前创建的表,不能实现表数据的共享 三、使用mysql作为元数据库 由于使用默认的元数据库有些弊端,所以采用mysql保存hive元数据解决上面的问题。hive所有的元数据都保存在同一个库里,这样不同开发者创建的表可以实现共享。
mysql配置又分为几种情况: (1)mysql部署在hive服务器,使用本地服务(测试、学习使用)

(2)mysql部署在其他机器,hive服务器开启metadata服务,在hive服务器上操作hive

(3)mysql部署在其他机器,hive服务器开启metadata服务,在hive客户端访问hive的metadata服务

配置mysql: 配置mysql时,首先要把mysql-jdbc-driver.jar拷贝到$HIVE_HOME/lib目录下,修改hive-default.xml名字为hive-site.xml 第一种情况,hive-site.xml配置如下
<property> <name>hive.metastore.local</name> <value>true</value> </property> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://localhost/hive?createDatabaseIfNotExist=true</value> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>hive</value> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>password</value> </property> 第二种情况,hive-site.xml配置 <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://192.168.0.1:3306/hive?createDatabaseIfNotExist=true</value> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>hive</value> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>password</value> </property> <property> <name>hive.metastore.local</name> <value>false</value> </property> <property> <name>hive.metastore.uris</name> <value>thrift://192.168.0.101:9083</value> </property> 第三种情况,hive-site.xml配置 1、 服务端配置 <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://192.168.1.214:3306/hive?createDatabaseIfNotExist=true</value> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>hive</value> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>password</value> </property> 2、客户端配置 <property> <name>hive.metastore.local</name> <value>false</value> </property> <property> <name>hive.metastore.uris</name> <value>thrift://192.168.0.101:9083</value> </property> 在使用hive开始前,如果mysql是部署在远端且 hive.metastore.local=false 则需要启动hive的metadata服务 $ hive --service metastore 客户端使用hive命令即可 root@local:~$ hive hive> show tables; OK Time taken: 0.7 seconds hive>

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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