最近在搞数据迁移,从A库的U1用户迁移到B库的U2用户,用了开源的kettle配合数据泵,测试时都没什么问题,但是真正上线了,居然当
背景:
最近在搞数据迁移,从A库的U1用户迁移到B库的U2用户,用了开源的kettle配合数据泵,测试时都没什么问题,但是真正上线了,居然当天凌晨卡死在那边。第二天定位时发现是impdp一直卡在那,但也没看到日志中报什么错。后来用小数量做了个测试,,终于看到错误了。错误内容大致如下:
ORA-39125: 在KUPW$WORKER.PUT_DDLS 中 Worker 发生意外的致命错误 (在调用 DBMS_METADATA.CONVERT [] 时)
ORA-06502: PL/SQL: 数字或值错误
LPX-00225: end-element tag "HIST_GRAM_LIST_ITEM" does not match start-element tag "EPVALUE"
ORA-06512: 在 "SYS.DBMS_SYS_ERROR", line 95
ORA-06512: 在 "SYS.KUPW$WORKER", line 6228
作业 "NM01"."SYS_IMPORT_SCHEMA_01" 因致命错误于 09:48:10 停止
有错误就好办了,从网上找到相关解释:
发现这个问题是Oracle的一个BUG,BUG号为5071931。
可以有两种方式解决这个问题:
1. 给IMPDP增加一个参数,EXCLUDE=STATISTICS,这个方法要求你在导入之后,再手工导入statistics
2. Deploy patch 5071931或者将Oracle升级到10.2.0.4
解决:
1、我确实查询了一下我的数据库版本是
SQL> select version from v$instance;
VERSION
-----------------
10.2.0.1.0
2、我没有采用打补丁的方法,而是采用第一种方法,在每个parfile文件中加入了如下命令:
EXCLUDE=STATISTICS
至此问题解决
后记:
需要注意parfile文件中加入了EXCLUDE=STATISTICS有时在导入时也会报:
ORA-39002: invalid operation
ORA-39168: Object path STATISTICS was not found.
解决方法:
EXCLUDE=STATISTICS:"in('')"
至于为什么这样改我也没搞清楚,还望高手指点
本文永久更新链接地址:

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MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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