新建用户和用户组
groupadd mysql
useradd -g mysql mysql
下载:
bison-2.5.tar.gz
cmake-2.8.4.tar.gz
m4-1.4.9.tar.gz
make-3.82.tar.gz
mysql-5.5.9.tar.gz
ncurses-devel-5.7-3.20090208.el6.i686.rpm
解压:
tar -zxvf bison-2.5.tar.gz
cd bison-2.5
./configure
make
make install
tar -zxvf cmake-2.8.4.tar.gz
cd cmake-2.8.4
./configure
make
make install
tar -zxvf m4-1.4.9.tar.gz
cd m4-1.4.9
./configure
make
make install
tar -zxvf make-3.82.tar.gz
cd make-3.82
./configure
make
make install
tar -zxvf mysql-5.5.9.tar.gz
进入mysql目录:
cd mysql-5.5.9
执行:
cmake . /
-DCMAKE_INSTALL_PREFIX=/usr/local/xiaorui/mysql/mysql-5.5.9 /
-DMYSQL_DATADIR=/usr/local/mysql/data /
-DMYSQL_UNIX_ADDR=/usr/local/mysql/data/mysqld.sock /
-DDEFAULT_CHARSET=utf8 /
-DDEFAULT_COLLATION=utf8_general_ci /
-DEXTRA_CHARSETS=all /
-DENABLED_LOCAL_INFILE=1
注意:如果/tmp/mysqld.sock存在,就cp到/usr/local/mysql/data中.
报错(如无报错直接make & make install 即可):
CMake Error at cmake/readline.cmake:82 (MESSAGE):
Curses library not found. Please install appropriate package,
remove CMakeCache.txt and rerun cmake.On Debian/Ubuntu, package name is libncurses5-dev, on RedHat and derivates it is ncurses-devel.
Call Stack (most recent call first):
cmake/readline.cmake:126 (FIND_CURSES)
cmake/readline.cmake:216 (MYSQL_USE_BUNDLED_LIBEDIT)
CMakeLists.txt:256 (MYSQL_CHECK_READLINE)
-- Configuring incomplete, errors occurred
安装:
rpm -ivh ncurses-devel-5.7-3.20090208.el6.i686.rpm
rm -f CMakeCache.txt
cmake . /
-DCMAKE_INSTALL_PREFIX=/usr/local/xiaorui/mysql/mysql-5.5.9 /
-DMYSQL_DATADIR=/usr/local/mysql/data /
-DMYSQL_UNIX_ADDR=/usr/local/mysql/data/mysqld.sock /
-DDEFAULT_CHARSET=utf8 /
-DDEFAULT_COLLATION=utf8_general_ci /
-DEXTRA_CHARSETS=all /
-DENABLED_LOCAL_INFILE=1
make
make install
cd mysql-5.5.9
cp support-files/my-huge.cnf /etc/my.cnf
增加权限:
chown mysql:mysql /etc/my.cnf
chown -R mysql:mysql /usr/local/mysql/data
chown -R mysql:mysql /usr/local/xiaorui/mysql/mysql-5.5.9
chown -R mysql:mysql /usr/local/
切换用户:
su mysql
进入mysql目录
cd mysql-5.5.9/scripts
初始化mysql:
增加执行权限:
chmod a+x mysql_install_db
执行:
./mysql_install_db --user=mysql --basedir=/usr/local/xiaorui/mysql/mysql-5.5.9 --ldata=/usr/local/mysql/data &
开启:
cd mysql-5.5.9/bin
执行:
./mysqld_safe --user=mysql --datadir=/usr/local/mysql/data/ &
查看是否开启:
ps -ef | grep mysql
如果有信息:
root 26502 26379 1 10:51 pts/2 00:00:00 /bin/sh ./mysqld_safe --user=mysql --datadir=/usr/local/mysql/data/
mysql 26766 26502 5 10:51 pts/2 00:00:00 /usr/local/xiaorui/mysql/mysql-5.5.9/bin/mysqld --basedir=/usr/local/xiaorui/mysql/mysql-5.5.9 --datadir=/usr/local/mysql/data/ --plugin-dir=/usr/local/xiaorui/mysql/mysql-5.5.9/lib/plugin --user=mysql --log-error=/usr/local/mysql/data//hadoop2.err --pid-file=/usr/local/mysql/data//hadoop2.pid --socket=/tmp/mysql.sock --port=3306
查看:
--socket=/tmp/mysql.sock
查看tmp目录下是否有mysql.sock文件.
如果有就正常.
如果没有就杀掉进程重新执行初始化mysql:
kill -9 26502
kill -9 26766
重新初始化mysql:
cd mysql-5.5.9/scripts
./mysql_install_db --user=mysql --basedir=/usr/local/xiaorui/mysql/mysql-5.5.9 --ldata=/usr/local/mysql/data &
配置环境变量:
cd $HOME
vim .bash_profile
添加:
export MYSQL_HOME=/usr/local/xiaorui/mysql/mysql-5.5.9
PATH=$MYSQL_HOME/bin:$PATH
export PATH
use mysql;
进入mysql:
./mysql -uroot -p
初始化root密码:
update user set password=PASSWORD('123456') where User='root';
mysqladmin -u root password 'mysql321'
mysqladmin -u root -h hadoop1 password 'mysql321'
mysqladmin -u root -h localhost password 'mysql321'
mysql -u root --password='mysql321'
create database hivedb;
GRANT ALL PRIVILEGES ON hivedb.* TO 'hiveusr'@'%' IDENTIFIED BY 'hiveusr321' WITH GRANT OPTION;
GRANT ALL PRIVILEGES ON hivedb.* TO 'hiveusr'@'localhost' IDENTIFIED BY 'hiveusr321' WITH GRANT OPTION;
GRANT ALL PRIVILEGES ON hivedb.* TO 'hiveusr'@'hadoop1' IDENTIFIED BY 'hiveusr321' WITH GRANT OPTION;
FLUSH PRIVILEGES;
注意:
hivedb:hive元数据库
hiveusr:数据库用户
如果mysql.sock在其他位置:
创建链接:
ln -s /var/lib/mysql/mysql.sock /tmp/mysql.sock
保护mysql.sock文件:
chmod +t /tmp/mysql.sock

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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