Oracle公司从版本12c以后实际上引入了类似于SQL Server的以年份为版本号的版本风格。Oracle 12c以后的已release版本为18c,19c,21c，2020年由于全球疫情的问题未发布大版本号。
其大版本的释放周期大大缩短了，实际上大版本的释放频率已经覆盖了过去Patch Set补丁集的作用。
对于先进企业选择Oracle数据库版本而言，建议可以考虑对当前年份-2/3的算法。
即如果当前是2021年，则考虑使用(2021-2 or 3) 18c或19c；并打上最新的RU(Release Update)和RUR(Release Update Revision)。
在使用Dgg实现Oracle跨库数据同步后，可以使用Dgg的数据校验功能来验证数据是否一致。
请首先参考《使用Dgg 全量同步/初始化Initial Load Oracle数据》 https://www.askmac.cn/archives/datagogo-initial-load-oracle-database.html
选中 树形图最上方的用户名，右击 Compare:
DataGoGo中存在三种 表数据的比较粒度：
测试 90万行 24列的表， 比较约耗时 2分钟。
比较结果如下：
Compare start date: 2021-06-07 14:58:54
Comparing SCOTT.T_XT_SYNCPERSONLOG and EAS.T_XT_SYNCPERSONLOG:
SCOTT.T_XT_SYNCPERSONLOG full table checksum: 235801620123
EAS.T_XT_SYNCPERSONLOG full table checksum: 235801620123
Full table checksum is the same.
End date: 2021-06-07 15:00:31
UDEV RELOAD是否会影响oracle ASM?
回答： 如果频繁 reload 显然会影响Oracle ASM ，甚至导致ASM Diskgroup OFFLINE。
如果只是一次很快速的reload，那么影响的概率较小。
参考链接：
‘udev’ rules continuously being reloaded resulted in Oracle ASM diskgroup outage
https://access.redhat.com/solutions/1465913
multipath.conf
# This is a basic configuration file with some examples, for device mapper
# multipath.
#
# For a complete list of the default configuration values, run either
# multipath -t
# or
# multipathd show config
#
# For a list of configuration options with descriptions, see the multipath.conf
# man page
## By default, devices with vendor = "IBM" and product = "S/390.*" are
## blacklisted. To enable mulitpathing on these devies, uncomment the
## following lines.
#blacklist_exceptions {
# device {
# vendor "IBM"
# product "S/390.*"
# }
#}
## Use user friendly names, instead of using WWIDs as names.
defaults {
user_friendly_names yes
find_multipaths yes
}
##
## Here is an example of how to configure some standard options.
##
#
#defaults {
# polling_interval 10
# path_selector "round-robin 0"
# path_grouping_policy multibus
# uid_attribute ID_SERIAL
# prio alua
# path_checker readsector0
# rr_min_io 100
# max_fds 8192
# rr_weight priorities
# failback immediate
# no_path_retry fail
# user_friendly_names yes
#}
##
## The wwid line in the following blacklist section is shown as an example
## of how to blacklist devices by wwid. The 2 devnode lines are the
## compiled in default blacklist. If you want to blacklist entire types
## of devices, such as all scsi devices, you should use a devnode line.
## However, if you want to blacklist specific devices, you should use
## a wwid line. Since there is no guarantee that a specific device will
## not change names on reboot (from /dev/sda to /dev/sdb for example)
## devnode lines are not recommended for blacklisting specific devices.
##
#blacklist {
# wwid 26353900f02796769
# devnode "^(ram|raw|loop|fd|md|dm-|sr|scd|st)[0-9]*"
# devnode "^hd[a-z]"
#}
#multipaths {
# {
# device {
# vendor "COMPAQ "
# product "HSV110 (C)COMPAQ"
# path_grouping_policy multibus
# path_checker readsector0
# path_selector "round-robin 0"
# hardware_handler "0"
# failback 15
# rr_weight priorities
# no_path_retry queue
# }
# device {
# vendor "COMPAQ "
# product "MSA1000 "
# path_grouping_policy multibus
# }
#}
# wwid 3600508b4000156d700012000000b0000
# alias yellow
# path_grouping_policy multibus
# path_selector "round-robin 0"
# failback manual
#devices {
# device {
# vendor "COMPAQ "
# product "HSV110 (C)COMPAQ"
# path_grouping_policy multibus
# path_checker readsector0
# path_selector "round-robin 0"
# hardware_handler "0"
# failback 15
# rr_weight priorities
# no_path_retry queue
# }
# device {
# vendor "COMPAQ "
# product "MSA1000 "
# path_grouping_policy multibus
# }
#}
# rr_weight priorities
# no_path_retry 5
# }
# multipath {
# wwid 1DEC_____321816758474
# alias red
# }
#
multipaths {
multipath {
wwid 360050764008103127000000000000067
alias disk30001
}
multipath {
wwid 360050764008103127000000000000068
alias disk30002
}
multipath {
wwid 360050764008103127000000000000069
alias disk30003
}
multipath {
wwid 360050764008103127000000000000064
alias disk31001
}
multipath {
wwid 360050764008103127000000000000065
alias disk31002
}
multipath {
wwid 36005076400810312700000000000005f
alias disk32001
}
multipath {
wwid 360050764008103127000000000000060
alias disk32002
}
multipath {
wwid 360050764008103127000000000000061
alias disk32003
}
multipath {
wwid 360050764008103127000000000000062
alias disk32004
}
multipath {
wwid 360050764008103127000000000000063
alias disk32005
}
multipath {
wwid 360050764008103127000000000000066
alias disk33001
}
}
12-dm-permissions.rules
ENV{DM_NAME}=="disk30001",NAME="asmdisk30001", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk30002",NAME="asmdisk30002", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk30003",NAME="asmdisk30003", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk31001",NAME="asmdisk31001", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk31002",NAME="asmdisk31002", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk32001",NAME="asmdisk32001", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk32002",NAME="asmdisk32002", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk32003",NAME="asmdisk32003", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk32004",NAME="asmdisk32004", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk32005",NAME="asmdisk32005", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
ENV{DM_NAME}=="disk33001",NAME="asmdisk33001", OWNER:="grid", GROUP:="asmadmin", MODE:="660"
99-oracle-asmdevices.rules
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000067", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000068", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000069", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000064", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000065", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="36005076400810312700000000000005f", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000060", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000061", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000062", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000063", OWNER="grid", GROUP="asmadmin", MODE="0660"
KERNEL=="sd*", SUBSYSTEM=="block", ENV{DEVTYPE}=="disk", ENV{ID_SERIAL}=="360050764008103127000000000000066", OWNER="grid", GROUP="asmadmin", MODE="0660"
现有2套MySQL服务器，需要将一台上的服务器上的数据同步到另一台。可以使用Dgg数据同步校准软件实现数据初始化同步的目的。
打开Dgg软件，点击开始 => 打开， 创建2个MySQL session:
选择源端 并点击下一步，选择目标端 并点击 连接：
可以在两侧的对象树上看到相关的表 , 点中用户 右键 => Transfer:
初始化同步后，若对表数据的一致性存在疑问，可以通过Compare功能比对，在左侧树形种点中你要比对的表，右键Compare:
校验分成几种：
其中行数对比校验 ，仅对比2个表的行数是否一致；即只比较count(1)
主键比对，只比对主键信息是否一致，支持联合主键
全表校验，比对全表数据信息（会排除TEXT LONGTEXT等长字段列）是否一致
对于小表而言（一般来说小于10万行），全表校验的速度也较快，其时间可接受。对于大表而言，除非是一致性要求极高的账目表，否则建议使用主键比对或行数比对。
Oracle 相比 mysql 的优势在哪里 原帖子在这里： https://v2ex.com/t/773654?p=1
目前的项目用的 mysql，支撑几十亿数据没问题（分库分表），偶尔慢 sql 也能优化索引解决，至于复杂查询通过搜索引擎实现，听说 Oracle 超级贵，那 Oracle 具体有什么优势呢，哪些场景下是 oracle only 的？
看完了回复，oracle 能单表支撑几十亿数据还是很强的，因为目前因为分表键导致很多需求无法实现，只能同步一个表用另一个分表键。
我再问下，如果是同时涉及几十个字段的复杂搜索，oracle 可以支持吗，目前用的搜索引擎实现也非常贵。
有一说一，单表支撑几十亿数据，听着有点玄乎，真的假的啊
我的回复：
oracle 的优化器 CBO optimizer 目前应该是所有 RDBMS 里最复杂的（不说是最先进的）。MYSQL 至少在优化器上还处于比较初级的阶段，虽然 MySQL 的目标可能并不希望实现非常复杂的优化器算法。其他一些东西 例如 undo 的实现等等 可能优势并不明显， 这里就不提了。
举一个例子， 都不使用索引的情况下，NO INDEX ! NO INDEX | NO INDEX !
以下数据量是一样的，机器是同一台。 Oracle 11.2.0.4 MySQL 8.0.14
都没有索引的情况下：oracle 使用 0.04 秒， MySQL 等了 10 分钟也没运行完
对于简单的 SQL 而言，差别不会有那么大。对于复杂的 SQL 而言， 能明显体现出优化器的优势。
对于拔高某个技术，没有兴趣。 所以 MYSQL 死忠请勿拍。
Oracle :
SQL> set timing on;
SQL> SELECT c.cust_city,
2 t.calendar_quarter_desc,
3 SUM(s.amount_sold) sales_amount
4 FROM sh.sales s, sh.times t, sh.customers c, sh.channels ch
5 WHERE s.time_id = t.time_id
6 AND s.cust_id = c.cust_id
7 AND s.channel_id = ch.channel_id
8 AND c.cust_state_province = 'FL'
9 AND ch.channel_desc = 'Direct Sales'
10 AND t.calendar_quarter_desc IN ('2000-01', '2000-02','1999-12')
11 GROUP BY c.cust_city, t.calendar_quarter_desc;
CUST_CITY CALENDA SALES_AMOUNT
------------------------------ ------- ------------
Cypress Gardens 2000-01 3545.82
Candler 2000-01 4166.32
Sanibel 2000-02 17908.67
Ocala 2000-02 7081.73
Molino 2000-01 18765.25
Ocala 2000-01 7146.73
Palmdale 2000-02 25829.24
Palmdale 2000-01 37793.44
Molino 2000-02 17144.7
Saint Marks 2000-01 55781.37
Noma 2000-01 33572.55
Evinston 2000-02 62657.21
Candler 2000-02 6493.94
Winter Springs 2000-02 20
Sugarloaf Key 2000-01 12027.66
Saint Marks 2000-02 48858.7
Blountstown 2000-02 38052.58
Sugarloaf Key 2000-02 9659.44
Cypress Gardens 2000-02 4928.93
Evinston 2000-01 53509.69
Blountstown 2000-01 27024.7
Sanibel 2000-01 15870.34
Winter Springs 2000-01 31.46
Noma 2000-02 23903.58
已选择 24 行。
已用时间: 00: 00: 00.04
执行计划
----------------------------------------------------------
Plan hash value: 1865285285
------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop |
------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 607 | 46132 | 955 (2)| 00:00:12 | | |
| 1 | HASH GROUP BY | | 607 | 46132 | 955 (2)| 00:00:12 | | |
|* 2 | HASH JOIN | | 2337 | 173K| 954 (2)| 00:00:12 | | |
| 3 | PART JOIN FILTER CREATE | :BF0000 | 274 | 4384 | 18 (0)| 00:00:01 | | |
|* 4 | TABLE ACCESS FULL | TIMES | 274 | 4384 | 18 (0)| 00:00:01 | | |
|* 5 | HASH JOIN | | 12456 | 729K| 936 (2)| 00:00:12 | | |
| 6 | MERGE JOIN CARTESIAN | | 383 | 14937 | 408 (1)| 00:00:05 | | |
|* 7 | TABLE ACCESS FULL | CHANNELS | 1 | 13 | 3 (0)| 00:00:01 | | |
| 8 | BUFFER SORT | | 383 | 9958 | 405 (1)| 00:00:05 | | |
|* 9 | TABLE ACCESS FULL | CUSTOMERS | 383 | 9958 | 405 (1)| 00:00:05 | | |
| 10 | PARTITION RANGE JOIN-FILTER| | 918K| 18M| 526 (2)| 00:00:07 |:BF0000|:BF0000|
| 11 | TABLE ACCESS FULL | SALES | 918K| 18M| 526 (2)| 00:00:07 |:BF0000|:BF0000|
------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("S"."TIME_ID"="T"."TIME_ID")
4 - filter("T"."CALENDAR_QUARTER_DESC"='1999-12' OR "T"."CALENDAR_QUARTER_DESC"='2000-01' OR
"T"."CALENDAR_QUARTER_DESC"='2000-02')
5 - access("S"."CUST_ID"="C"."CUST_ID" AND "S"."CHANNEL_ID"="CH"."CHANNEL_ID")
7 - filter("CH"."CHANNEL_DESC"='Direct Sales')
9 - filter("C"."CUST_STATE_PROVINCE"='FL')
统计信息
----------------------------------------------------------
0 recursive calls
0 db block gets
1726 consistent gets
0 physical reads
0 redo size
1495 bytes sent via SQL*Net to client
531 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
24 rows processed
SQL> select count(*) from sh.sales;
COUNT(*)
----------
918843
SQL> select * From v$VERSION;
BANNER
--------------------------------------------------------------------------------
Oracle Database 11g Enterprise Edition Release 11.2.0.4.0 - 64bit Production
PL/SQL Release 11.2.0.4.0 - Production
CORE 11.2.0.4.0 Production
TNS for 64-bit Windows: Version 11.2.0.4.0 - Production
NLSRTL Version 11.2.0.4.0 - Production
MySQL :
mysql> SELECT c.cust_city,
-> t.calendar_quarter_desc,
-> SUM(s.amount_sold) sales_amount
-> FROM sh.sales s, sh.times t, sh.customers c, sh.channels ch
-> WHERE s.time_id = t.time_id
-> AND s.cust_id = c.cust_id
-> AND s.channel_id = ch.channel_id
-> AND c.cust_state_province = 'FL'
-> AND ch.channel_desc = 'Direct Sales'
-> AND t.calendar_quarter_desc IN ('2000-01', '2000-02','1999-12')
-> GROUP BY c.cust_city, t.calendar_quarter_desc;
+----+-------------+-------+------------+------+---------------+------+---------+------+--------+----------+----------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+------+---------------+------+---------+------+--------+----------+----------------------------------------------------+
| 1 | SIMPLE | ch | NULL | ALL | NULL | NULL | NULL | NULL | 5 | 20.00 | Using where; Using temporary |
| 1 | SIMPLE | t | NULL | ALL | NULL | NULL | NULL | NULL | 1804 | 30.00 | Using where; Using join buffer (Block Nested Loop) |
| 1 | SIMPLE | c | NULL | ALL | NULL | NULL | NULL | NULL | 55065 | 10.00 | Using where; Using join buffer (Block Nested Loop) |
| 1 | SIMPLE | s | NULL | ALL | NULL | NULL | NULL | NULL | 914584 | 0.10 | Using where; Using join buffer (Block Nested Loop) |
+----+-------------+-------+------------+------+---------------+------+---------+------+--------+----------+----------------------------------------------------+
mysql> select version();
+-----------+
| version() |
+-----------+
| 8.0.14 |
+-----------+
1 row in set (0.00 sec)
mysql> select count(*) from sh.sales;
+----------+
| count(*) |
+----------+
| 918843 |
+----------+
1 row in set (0.96 sec)
现有ZHS和AL2套数据库,需要将ZHS下的EAS Schema数据初始化复制到AL数据库。
准备工作： 在AL数据库中对应创建EAS用户，并赋权：
set ORACLE_SID=AL sqlplus / as sysdba create user eas identified by eas; grant connect,resource to eas;
打开DataGoGo.exe 点击开始
点击新建：
输入数据源ZHS实例的连接信息：
点击测试连接：
点击保存后， 再次新建目标数据库连接：
选中源数据源，点击下一步：
选中目标数据源，点击连接
连接后，会在左右2侧显示对象树形图：
选中用户名，右键点中，点击Transfer:
出现Schema 传输界面，默认选中了所有表
点击Start后开始Schema用户级别数据传输，传输过程中 会显示传输进度：
在有NVARCHAR、LOB(BLOB CLOB NCLOB)字段的情况下，DataGoGo的单线程传输速度约为4500条/秒。
在没有NVARCHAR、LOB(BLOB CLOB NCLOB)字段的情况下，DataGoGo的单线程传输速度约为30000条/秒。
点击Close后，可以在右侧树形图看到传输过来的表：
| 按照重要程度划分数据库级别 | |||||
| 级别 | D | C | B | A | S |
| 影响面 | 小于10人 | 10-1000人 | 1000-100000人 | 100000-1000000人 | 1000000人以上 |
| 业务类型举例 | 测试/开发系统，小型OA 记账软件等 | 中型OA ERP 财务软件等 | 中大型ERP MES HRM ，大型医院HIS | 电信CRM 银行BANKING等 | 大型公共应用 如12306等 |
| 灾难救援价格 | 500-5000 | 5千到三万 | 3万到10万 | 10万到50万 | 50万以上 |
| 一般的配套设施 | 几乎无任何有效备份 | 少量磁盘上逻辑备份 | 可能有物理备份+其他备份形式 | 物理/逻辑备份+DataGuard,OGG等物理/逻辑灾备;存储级别冗余等+多数据中心冗余 | 都有 |
Dgg Oracle/MySQL数据库复制同步校准软件
Dgg Rdbms Oracle MySQL Table/Schema Sync Compare Repair
最新版：
Dgg is a single application that allows you to tranfer data between Oracle and MySQL.
It will also support Microsoft SQL Server in future.
It supports below directionals:
Oracle To Oracle
Oracle To MySQL
MySQL To MySQL
MySQL To Oracle
特性：
快速比较同步Oracle表数据
快速比较同步MySQL表数据
支持异构传输 Oracle <=> MySQL ， 未来将支持 SQL Server
将支持快速数据表校准修复
将支持索引、视图、触发器等其他类型对象
Dgg Oracle MySQL数据同步校准工具最新版：https://zcdn.askmac.cn/Dgg2110.zip
=================================> 前期配置应在割接前10天完成 <=================================
1、在新服务器上配置必要的os参数，包含大内存页等
2、在新服务器上12.2.0.1 GI和RDBMS，安装2010补丁：p31741641_122010和p31750094_122010
3、创建一个与oldorcl库参数配置匹配的空数据库
4、复制密码文件到新服务器：
[oracle@]$ srvctl config database -d as19_fra1gh | grep ‘Password file’
Password file: +DATAC1//PASSWORD/passwd <– this file is what needs to be copied to /tmp and scp’d to the standby (result may differ)
[oracle@]$ export ORACLE_SID=+ASM1
[oracle@]$ export ORACLE_HOME=/u01/app/12.2.0.1/grid
[oracle@]$ export PATH=$ORACLE_HOME/bin:$PATH
[oracle@]$asmcmd cp +DATAC1//PASSWORD/passwd /tmp/passwd. copying +DATAC1//PASSWORD/passwd -> /tmp/passwd.
[oracle@]$ scp /tmp/orapw1 oracle@:/tmp/orapw
5、配置tnsnames.ora文件
包含 oldorcl 条目 和neworcl条目
oldorcl 老的源库
neworcl 新的目标库
6、在新服务器上恢复控制文件
startup nomount;
restore standby controlfile from service oldorcl;
alter database mount;
7、配置rman参数
CONFIGURE DEVICE TYPE DISK PARALLELISM 2;
8、 全量恢复数据库 ；也可以基于传输备份文件实现，影响大同小异
restore database from service oldorcl;
9、 增加standby logfile:
SQL> alter database add standby logfile thread 1
group 7 (‘+DATA’) size 4294967296,
group 8 (‘+DATA’) size 4294967296,
group 9 (‘+DATA’) size 4294967296;
SQL> alter database add standby logfile thread 2
group 11 (‘+DATA’) size 4294967296,
group 12 (‘+DATA’) size 4294967296,
group 13 (‘+DATA’) size 4294967296;
10、 配置 归档传输 log_archive_dest_2 (基于归档同步） log_archive_dest_2=’service=neworcl lgwr async’
如果 归档日志过多 ，那么可以 定期执行recover database from service oldorcl; (基于增量备份实现同步） ，而不打开归档传输
11、 将neworcl数据库启动到只读模式，并打开日志应用
alter database open read only;
alter database recover managed standby database using current logfile disconnect from session;
=================================> 割接窗口开始 <=================================
必须打开归档传输log_archive_dest_2=’service=neworcl lgwr async’
停止应用
停止数据库实例 shutdown immediate; ==》 约5分钟
将oldorcl数据库启动到 限制模式 ==》 约5分钟
startup restrict;
创建一条新记录 ，并确认传输到新库 ==> 约1分钟
create table test1（t1 date);
insert into test1 values(sysdate);
commit;
alter session set nls_date_format=’YYYY-MM-DD hh24:mi:ss’;
alter system checkpoint;
alter system switch logfile;
alter system switch logfile;
alter system switch logfile;
select * from test1;
在新orcl确认
select * from test1;
将neworcl数据库启动到打开模式 ==》10分钟
ALTER DATABASE RECOVER MANAGED STANDBY DATABASE FINISH;
ALTER DATABASE COMMIT TO SWITCHOVER TO PRIMARY;
alter database open;
检查数据
停数据库实例 、监听、SCAN ip资源 ==》10分钟
切换SCAN IP ==>10分钟
启动所有资源 ,启动neworcl 2节点数据库实例 ==》15分钟
去掉 log_archive_dest_2
=================================> 割接窗口结束 <=================================
