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Server version: 8.0.17 Source distribution
编译安装脚本
yum -y install gcc gcc-c++ ncurses-devel libtirpc-devel libaio-devel openssl openssl-devel 增加mysql用户 groupadd -g 1101 mysql ; useradd -u 1101 -g mysql mysql ; mkdir -p /opt/mysql mkdir -p /data/mysqldata mkdir -p /log/mysql chown -R mysql.mysql /opt/mysql chown -R mysql.mysql /data/mysqldata chown -R mysql.mysql /log/mysql 下载mysql和rpcsvc cd /tmp wget https://github.com/thkukuk/rpcsvc-proto/releases/download/v1.4/rpcsvc-proto-1.4.tar.gz tar zxvf rpcsvc-proto-1.4.tar.gz cd rpcsvc-proto-1.4 ./configure make make install cd /tmp wget https://cdn.mysql.com//Downloads/MySQL-8.0/mysql-boost-8.0.17.tar.gz 安装mysql tar zxvf mysql-boost-8.0.17.tar.gz cd mysql-8.0.17 cmake -DCMAKE_INSTALL_PREFIX=/opt/mysql \ -DINSTALL_PLUGINDIR=/opt/mysql/lib/plugin \ -DMYSQL_DATADIR=/data/mysqldata \ -DWITH_MYISAM_STORAGE_ENGINE=1 \ -DWITH_INNOBASE_STORAGE_ENGINE=1 \ -DDEFAULT_CHARSET=utf8mb4 \ -DDEFAULT_COLLATION=utf8mb4_general_ci \ -DBUILD_CONFIG=mysql_release \ -DWITH_SSL=system \ -DWITH_ZLIB=system \ -DCMAKE_BUILD_TYPE=RelWithDebInfo \ -DWITH_BOOST=/tmp/mysql-8.0.17/boost/boost_1_69_0 \ -DFORCE_INSOURCE_BUILD=1 make -j 4 make install 设置配置文件 mkdir -p /opt/mysql/etc cat >/opt/mysql/etc/my.cnf <<EOF [client] port = 3306 socket = /data/mysqldata/mysql.sock [mysqld] port = 3306 socket = /data/mysqldata/mysql.sock datadir=/data/mysqldata/ basedir=/opt/mysql mysqlx=0 #innodb innodb_data_home_dir = /data/mysqldata innodb_data_file_path = ibdata1:128M:autoextend innodb_buffer_pool_size = 1000M innodb_buffer_pool_instances=1 innodb_file_per_table=on #innodb log innodb_log_group_home_dir = /data/mysqldata innodb_log_file_size = 256M innodb_log_buffer_size = 64M innodb_log_files_in_group=4 #innodb zero data lost variables innodb_flush_log_at_trx_commit = 1 innodb_doublewrite=on sync_binlog=1 master-info-repository=table relay-log-info-repository=table #tx commit action is heavy action autocommit=on transaction_isolation=READ-COMMITTED lower_case_table_names=1 bind-address = 0.0.0.0 #character init_connect = 'SET NAMES utf8mb4' character_set_server=utf8mb4 #collation_server=utf8mb4_general_ci open_files_limit = 65535 #gtid server_id=791 gtid_mode=on enforce_gtid_consistency=on master_info_repository=table relay_log_info_repository=table #connect max_connections = 2000 max_connect_errors=9999999 #sql_mode='STRICT_TRANS_TABLES,NO_ZERO_IN_DATE,NO_ZERO_DATE,ERROR_FOR_DIVISION_BY_ZERO,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION' #memory #query_cache_size = 0M #query_cache_type=0 #mysql log binlog_format=row log_bin = binlog log_timestamps=system log_output='file,table' log_error=/log/mysql/error.log general_log=off general_log_file=/log/mysql/general_.log relay_log = /log/mysql/mysql-relay-bin.log relay_log_purge =off max_binlog_size = 256M log_slave_updates=on binlog_expire_logs_seconds = 604800 slow_query_log_file=/log/mysql/slow.log slow_query_log=on long_query_time=1 skip_name_resolve=on #slave #skip_slave_start slave-skip-errors=1062 replicate_ignore_db=mysql replicate_wild_ignore_table=mysql.% #resource max_allowed_packet = 128M innodb_lock_wait_timeout = 50 #use audit binlog_rows_query_log_events=on EOF 修改目录权限和初始化mysql chown -R mysql.mysql /opt/mysql chown -R mysql.mysql /data/mysqldata chown -R mysql.mysql /log/mysql /opt/mysql/bin/mysqld --defaults-file=/opt/mysql/etc/my.cnf --initialize --user=mysql 将mysql设置为开机自动启动 cp /opt/mysql/support-files/mysql.server /etc/init.d/mysqld chmod +x /etc/init.d/mysqld systemctl enable mysqld.service #chkconfig --add mysqld 重启mysql systemctl restart mysqld.service
使用了mysql的分区，觉得最不爽的是mysql partition 限制：
A UNIQUE INDEX must include all columns in the table's partitioning function
A PRIMARY KEY must include all columns in the table's partitioning function
意思就是：用于分区的column 必须是主键列，或者主键的其中几个列，或者是唯一键列。无论创建何种类型的分区，如果表中存在主键或唯一索引时，分区列必须是唯一索引的一个组成部分。也不清楚作者这样设计的初衷是什么。比如以下的写法就是有语法错误：
CREATE TABLE t1 ( col1 INT NOT NULL, col2 DATE NOT NULL, col3 INT NOT NULL, col4 INT NOT NULL, UNIQUE KEY (col1, col2) ) PARTITION BY HASH(col3) PARTITIONS 4; CREATE TABLE t2 ( col1 INT NOT NULL, col2 DATE NOT NULL, col3 INT NOT NULL, col4 INT NOT NULL, UNIQUE KEY (col1), UNIQUE KEY (col3) ) PARTITION BY HASH(col1 + col3) PARTITIONS 4;
这样会大大限制mysql分区使用范围。
1.range 分区，频繁使用。 基于属于一个给定连续区间的列值，把多行分配给分区。
CREATE TABLE employees ( id INT NOT NULL, fname VARCHAR(30), lname VARCHAR(30), hired DATE NOT NULL DEFAULT '1970-01-01', separated DATE NOT NULL DEFAULT '9999-12-31', job_code INT NOT NULL, store_id INT NOT NULL ) PARTITION BY RANGE (store_id) ( PARTITION p0 VALUES LESS THAN (6), PARTITION p1 VALUES LESS THAN (11), PARTITION p2 VALUES LESS THAN (16), PARTITION p3 VALUES LESS THAN (21) );
2. list 分区，比较少使用。类似于按RANGE分区，区别在于LIST分区是基于列值匹配一个离散值集合中的某个值来进行选择。
CREATE TABLE employees ( id INT NOT NULL, fname VARCHAR(30), lname VARCHAR(30), hired DATE NOT NULL DEFAULT '1970-01-01', separated DATE NOT NULL DEFAULT '9999-12-31', job_code INT, store_id INT ) PARTITION BY LIST(store_id) ( PARTITION pNorth VALUES IN (3,5,6,9,17), PARTITION pEast VALUES IN (1,2,10,11,19,20), PARTITION pWest VALUES IN (4,12,13,14,18), PARTITION pCentral VALUES IN (7,8,15,16) );
注意看上面，都是没有主键，没有唯一键的。
3.HASH分区，频繁使用：基于用户定义的表达式的返回值来进行选择的分区，该表达式使用将要插入到表中的这些行的列值进行计算。这个函数可以包含MySQL 中有效的、产生非负整数值的任何表达式。
CREATE TABLE employees ( id INT NOT NULL, fname VARCHAR(30), lname VARCHAR(30), hired DATE NOT NULL DEFAULT '1970-01-01', separated DATE NOT NULL DEFAULT '9999-12-31', job_code INT, store_id INT ) PARTITION BY HASH( YEAR(hired) ) PARTITIONS 4;
4.KEY分区：类似于按HASH分区，区别在于KEY分区只支持计算一列或多列，且MySQL服务器提供其自身的哈希函数。必须有一列或多列包含整数值。
CREATE TABLE k1 ( id INT NOT NULL PRIMARY KEY, name VARCHAR(20) ) PARTITION BY KEY() PARTITIONS 2; CREATE TABLE k1 ( id INT NOT NULL, name VARCHAR(20), UNIQUE KEY (id) )PARTITION BY KEY() PARTITIONS 2;
上面两个例子你会觉得很奇怪，都没有指定分区列。mysql默认就使用了唯一键来做了分区。
1）当数据量很大(过T)时，肯定不能把数据再如到内存中，这样查询一个或一定范围的item是很耗时。另外一般这情况下，历史数据或不常访问的数据占很大部分，最新或热点数据占的比例不是很大。这时可以根据有些条件进行表分区。
2）分区表的更易管理，比如删除过去某一时间的历史数据，直接执行truncate，或者狠点drop整个分区，这比detele删除效率更高
3）当数据量很大，或者将来很大的，但单块磁盘的容量不够，或者想提升IO效率的时候，可以把没分区中的子分区挂载到不同的磁盘上。
4）使用分区表可避免某些特殊的瓶颈，例如Innodb的单个索引的互斥访问..
5）单个分区表的备份很恢复会更有效率，在某些场景下
6）涉及到例如SUM()和COUNT()这样聚合函数的查询，可以很容易地进行并行处理。
这种查询的一个简单例子如
“SELECT salesperson_id, COUNT (orders) as order_total FROM sales GROUP BY salesperson_id；”。
通过“并行”，这意味着该查询可以在每个分区上同时进行，最终结果只需通过总计所有分区得到的结果。
表分区了，查询where必须带上分区键，否则使用不到分区的好处了。我们来看下例子：
CREATE TABLE part_tab
(c1 int default NULL, c2 varchar(30) default NULL, c3 date not null)
PARTITION BY RANGE(year(c3))
(PARTITION p0 VALUES LESS THAN (1995),
PARTITION p1 VALUES LESS THAN (1996) ,
PARTITION p2 VALUES LESS THAN (1997) ,
PARTITION p3 VALUES LESS THAN (1998) ,
PARTITION p4 VALUES LESS THAN (1999) ,
PARTITION p5 VALUES LESS THAN (2000) ,
PARTITION p6 VALUES LESS THAN (2001) ,
PARTITION p7 VALUES LESS THAN (2002) ,
PARTITION p8 VALUES LESS THAN (2003) ,
PARTITION p9 VALUES LESS THAN (2004) ,
PARTITION p10 VALUES LESS THAN (2010),
PARTITION p11 VALUES LESS THAN (MAXVALUE) );
CREATE TABLE no_part_tab(c1 int default NULL, c2 varchar(30) default NULL, c3 date not null);
drop procedure load_part_tab;
delimiter $$
CREATE PROCEDURE load_part_tab()
begin
declare v int default 0;
while v < 8000000
do
insert into part_tab
values (v,'testingpartitions',adddate('1995-01-01',(rand(v)*36520)mod 3652));
set v = v + 1;
end while;
end;$$
delimiter ;
call load_part_tab();
//从 part_tab 导入数据到 no_part_tab
insert into no_part_tab select * from part_tab;
创建了2个表，数据都是800万。
一个表no_part_tab的大小是428M。在这里另外
mysql> explain select count(*) from part_tab where c3 > date '1995-01-01'and c3 < date '1995-12-31'; +----+-------------+----------+------------+------+---------------+------+---------+------+--------+----------+-------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+----------+------------+------+---------------+------+---------+------+--------+----------+-------------+ | 1 | SIMPLE | part_tab | p1 | ALL | NULL | NULL | NULL | NULL | 796215 | 11.11 | Using where | +----+-------------+----------+------------+------+---------------+------+---------+------+--------+----------+-------------+ 1 row in set, 1 warning (0.00 sec) mysql> explain select count(*) from no_part_tab where c3 > date '1995-01-01'and c3 < date '1995-12-31'; +----+-------------+-------------+------------+------+---------------+------+---------+------+---------+----------+-------------+ | id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra | +----+-------------+-------------+------------+------+---------------+------+---------+------+---------+----------+-------------+ | 1 | SIMPLE | no_part_tab | NULL | ALL | NULL | NULL | NULL | NULL | 7773613 | 11.11 | Using where | +----+-------------+-------------+------------+------+---------------+------+---------+------+---------+----------+-------------+ 1 row in set, 1 warning (0.01 sec) mysql> select count(*) from part_tab where c3 > date '1995-01-01'and c3 < date '1995-12-31'; +----------+ | count(*) | +----------+ | 795181 | +----------+ 1 row in set (0.39 sec) mysql> select count(*) from no_part_tab where c3 > date '1995-01-01'and c3 < date '1995-12-31'; +----------+ | count(*) | +----------+ | 795181 | +----------+ 1 row in set (2.94 sec)
查询时间和扫描的行数，高下可判。
| 序号 | 常见操作 | 举例 | 备注 |
| 1 | 删除分区 | 1) aher table emp drop partition p1;
2) 一次性删除各个区：alter table emp drop partition p1,p2; 3) 删除表的所有分区:Alter table emp remove partitioning; |
1)不可以删除hash或者kev分区。
2)删除分区会删除数据，但是删除表的所有分区--不会丢失数据（验证ok) |
| 2 | 增加分区 | alter table emp add partition (partition p1 values less than (24));
alter table emp add partition partition p3 values in (40)); |
1)增加分区的值只能增加，不能比现在所拥有的分区值低 |
| 3 | 分解分区 | alter table emp reorganize partition p2 into
(partition p1 values less than (6), partition p2 values less than (16)); |
reorganize partition关键字可以对表的部分分区或全部分区进行修
改，并且不会丢失数据。分解前后分区的整体范围应该一致。 |
| 4 | 合并分区 | alter table emp reorganize partition p1,p3 into (partition p1 values less than (1000)); | 不会丢失数据 |
| 5 | 重新定义分区 | 重新定义Hash分区：Alter table emp partition by hash(salary) partitions 7;
重新定义Range分区： Alter table emp partition by range(id) (partition p1 values less than (2000), partition p2 values less than (4000)); |
相当于删除重建。 |
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