服务器快速部署--使用Docker部署MySQL

最近使用Dokcer部署各种服务端所需的环境,目的是为了后面的服务器集群、负载均衡、数据库集群做铺垫,以便准备好服务器高并发、数据库高并发提供测试环境。这里记录一下Docker部署MySQL的过程,为下一步的数据库读写分离、垂直拆分、水平拆分、数据库集群等提供测试环境。
本次是在虚拟机安装的CentOS上进行的部署,首先安装Docker

yum -y install docker

安装完毕后启动docker

systemctl start docker

添加开机启动项

systemctl enable docker

到这里,docker的安装就算是完成了,并且会随系统重启开机启动。接下来部署MySQL。首先,拉取MySQL镜像,这里拉取的是5.7版本的mysql

docker pull mysql:5.7

跟之前部署nginx不同,这次先不启动,而是在虚拟机创建一个mysql的映射文件夹,以便后面映射本地配置文件、数据目录、日志目录到docker容器中,首先在CentOS根目录里面创建1个mysql文件夹

mkdir mysql

然后进入mysql文件夹并创建三个额外的文件夹

cd mysql
mkdir conf
mkdir data
mkdir log

好了,切回根目录,进入到conf文件夹创建mysql的配置文件my.cnf

cd /  #切换到根目录
cd /mysql/conf
vi my.cnf

接下来,输入以下配置文件

配置文件中需要修改的只有两部分内容,我已经标注出来了,一个是指定server-id,一个是修改缓存池的大小,建议为内存的70%即可


[client]
port    = 3306
socket  = /var/run/mysqld/mysqld.sock

[mysql]
prompt="\u@mysqldb \R:\m:\s [\d]> "
no-auto-rehash

[mysqld]
##########################################NEED SET#################################################
#主数据库的id必须小于从数据库的id
server-id = 1
###########################################SET END################################################
user    = mysql
port    = 3306
basedir = /usr
datadir = /var/lib/mysql/
socket  = /var/run/mysqld/mysqld.sock
pid-file = mysqldb.pid
character-set-server = utf8mb4
skip_name_resolve = 1

#若你的MySQL数据库主要运行在境外,请务必根据实际情况调整本参数
default_time_zone = "+8:00"

open_files_limit    = 65535
back_log = 1024
max_connections = 512
max_connect_errors = 1000000
table_open_cache = 1024
table_definition_cache = 1024
table_open_cache_instances = 64
thread_stack = 512K
external-locking = FALSE
max_allowed_packet = 32M
sort_buffer_size = 4M
join_buffer_size = 4M
thread_cache_size = 768
interactive_timeout = 600
wait_timeout = 600
tmp_table_size = 32M
max_heap_table_size = 32M
slow_query_log = 1
log_timestamps = SYSTEM
slow_query_log_file = /var/lib/mysql/slow.log
log-error = /var/lib/mysql/error.log
long_query_time = 0.1
log_queries_not_using_indexes =1
log_throttle_queries_not_using_indexes = 60
min_examined_row_limit = 100
log_slow_admin_statements = 1
log_slow_slave_statements = 1
server-id = 3306
log-bin = /var/lib/mysql/mybinlog
sync_binlog = 1
binlog_cache_size = 4M
max_binlog_cache_size = 2G
max_binlog_size = 1G

#注意:MySQL 8.0开始,binlog_expire_logs_seconds选项也存在的话,会忽略expire_logs_days选项
#expire_logs_days = 7

master_info_repository = TABLE
relay_log_info_repository = TABLE
gtid_mode = on
enforce_gtid_consistency = 1
log_slave_updates
slave-rows-search-algorithms = 'INDEX_SCAN,HASH_SCAN'
binlog_format = row
binlog_checksum = 1
relay_log_recovery = 1
relay-log-purge = 1
key_buffer_size = 32M
read_buffer_size = 8M
read_rnd_buffer_size = 4M
bulk_insert_buffer_size = 64M
myisam_sort_buffer_size = 128M
myisam_max_sort_file_size = 10G
myisam_repair_threads = 1
lock_wait_timeout = 3600
explicit_defaults_for_timestamp = 1
innodb_thread_concurrency = 0
innodb_sync_spin_loops = 100
innodb_spin_wait_delay = 30

transaction_isolation = REPEATABLE-READ
#innodb_additional_mem_pool_size = 16M
##########################################NEED SET#################################################
#其他全部使用默认,这个地方的大小设置为内存的70%即可
innodb_buffer_pool_size = 350M
###########################################SET END################################################
innodb_buffer_pool_instances = 4
innodb_buffer_pool_load_at_startup = 1
innodb_buffer_pool_dump_at_shutdown = 1
innodb_data_file_path = ibdata1:1G:autoextend
innodb_flush_log_at_trx_commit = 1
innodb_log_buffer_size = 32M
innodb_log_file_size = 2G
innodb_log_files_in_group = 2
innodb_max_undo_log_size = 4G
innodb_undo_directory = /var/lib/mysql/undolog
innodb_undo_tablespaces = 95

# 根据您的服务器IOPS能力适当调整
# 一般配普通SSD盘的话,可以调整到 10000 - 20000
# 配置高端PCIe SSD卡的话,则可以调整的更高,比如 50000 - 80000
innodb_io_capacity = 4000
innodb_io_capacity_max = 8000
innodb_flush_sync = 0
innodb_flush_neighbors = 0
innodb_write_io_threads = 8
innodb_read_io_threads = 8
innodb_purge_threads = 4
innodb_page_cleaners = 4
innodb_open_files = 65535
innodb_max_dirty_pages_pct = 50
innodb_flush_method = O_DIRECT
innodb_lru_scan_depth = 4000
innodb_checksum_algorithm = crc32
innodb_lock_wait_timeout = 10
innodb_rollback_on_timeout = 1
innodb_print_all_deadlocks = 1
innodb_file_per_table = 1
innodb_online_alter_log_max_size = 4G
innodb_stats_on_metadata = 0

#注意:MySQL 8.0.16开始删除该选项
internal_tmp_disk_storage_engine = InnoDB

# some var for MySQL 5.7
innodb_checksums = 1
#innodb_file_format = Barracuda
#innodb_file_format_max = Barracuda
query_cache_size = 0
query_cache_type = 0
innodb_undo_logs = 128

innodb_status_file = 1
#注意: 开启 innodb_status_output & innodb_status_output_locks 后, 可能会导致log-error文件增长较快
innodb_status_output = 0
innodb_status_output_locks = 0

#performance_schema
performance_schema = 1
performance_schema_instrument = '%memory%=on'
performance_schema_instrument = '%lock%=on'

#innodb monitor
innodb_monitor_enable="module_innodb"
innodb_monitor_enable="module_server"
innodb_monitor_enable="module_dml"
innodb_monitor_enable="module_ddl"
innodb_monitor_enable="module_trx"
innodb_monitor_enable="module_os"
innodb_monitor_enable="module_purge"
innodb_monitor_enable="module_log"
innodb_monitor_enable="module_lock"
innodb_monitor_enable="module_buffer"
innodb_monitor_enable="module_index"
innodb_monitor_enable="module_ibuf_system"
innodb_monitor_enable="module_buffer_page"
innodb_monitor_enable="module_adaptive_hash"

[mysqldump]
quick
max_allowed_packet = 32M

保存退出,接下来,我们需要把虚拟机中的/mysql/conf映射到容器中的/etc/mysql/conf.d中,以使mysql启动的时候可以加载到我们刚刚创建的my.cnf配置。
现在我们来启动一个新的容器,并且映射我们创建的文件到容器中

docker run -p 3306:3306 --name felix-mysql \
-v /mysql/conf:/etc/mysql/conf.d \
-v /mysql/data:/var/lib/mysql \
-e MYSQL_ROOT_PASSWORD=123456 \
-d mysql:5.7

OK,此时,查看正在运行的容器

docker ps

结果如下(忽略我的5.6,实际上是5.7)



有些可能会发现没有运行成功,这是可以查看下log信息

docker logs xxx

失败的话有可能是三个原因

虚拟机的/mysql没有权限

chomod -R 777 /mysql
chomod 644 /mysql/conf/my.cnf

没有关闭selinux

vi /etc/selinux/config
#然后设置SELINUX=disabled保存后退出
reboot

没有关闭防火墙

systemctl stop firewalld
systemctl disable firewalld
reboot

现在使用workbench测试下我们的数据库


然后在数据库中创建两个测试数据库user,testdb1,然后在虚拟机的/mysql/data中查看是否数据库文件是保存在映射的文件夹内的

一切正常。现在我们已经成功使用Docker部署了MySQL,其实也可以使用dockerfile来简化过程,不过为了尽快做好测试环境,所以本文就不介绍了。

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