SQL点滴24 监测表的变化
在网上看到一篇关于监测表中的插入,更新,删除的方法,使用触发器实现的,很有价值。
有时候,我们在某一重要的时间段需要监控某张表的变化情况,包含插入、更新、删除。举例来说,当我们把数据导出到外部的系统时,我们希望导出的是全部的数据,而且最好是导出上次导出之后变动的数据。作为DBA,我们可采传统的触发器操作,来构建一个元数据表或一个时间戳列来监控数据的变化。
代码如下:Code Listing 1
该代码在 SQL 2005(SP3), SQL 2008 R2 (RTM with cu5)测试通过
代码如下:
-------------------
--Method 1: TRIGGER
-------------------
--Base Table Definition
IF OBJECT_ID('CheckSumTest', 'U') IS NOT NULL DROP TABLE CheckSumTest
GO
CREATE TABLE CheckSumTest
(
id int IDENTITY(1,1) NOT NULL PRIMARY KEY,
vc1 varchar(1) NOT NULL,
vc2 varchar(1) NOT NULL
)
GO
INSERT dbo.CheckSumTest (vc1, vc2) SELECT 'a', 'b'
INSERT dbo.CheckSumTest (vc1, vc2) SELECT 'b', 'a'
GO
--Create Audit Summary Table to hold Meta-Data
IF OBJECT_ID('dbo.TableAuditSummary', 'U') IS NOT NULL DROP TABLE dbo.TableAuditSummary
CREATE TABLE dbo.TableAuditSummary
( id INT IDENTITY(1,1) NOT NULL PRIMARY KEY,
TableName sysname NOT NULL,
LastUpdate DATETIME NOT NULL,
LastExport DATETIME NOT NULL
)
GO
INSERT dbo.TableAuditSummary (TableName, LastUpdate, LastExport) VALUES ('dbo.CheckSumTest', GETDATE(), GETDATE())
GO
--Tables that need exporting
SELECT * FROM dbo.TableAuditSummary WHERE LastUpdate>LastExport
--Create Trigger on all Base Tables
--This fires on any insert/update/delete and writes new LastUpdate column for the table set to Current Date and Time
IF OBJECT_ID('dbo.trg_CheckSumTest_MaintainAuditSummary', 'TR') IS NOT NULL DROP TRIGGER dbo.trg_CheckSumTest_MaintainAuditSummary
GO
CREATE TRIGGER dbo.trg_CheckSumTest_MaintainAuditSummary
ON dbo.CheckSumTest
AFTER INSERT, UPDATE, DELETE
AS
BEGIN
IF (object_id('dbo.CheckSumTest') IS NOT NULL)
UPDATE dbo.TableAuditSummary SET LastUpdate=GETDATE() WHERE TableName='dbo.CheckSumTest'
END
GO
--Make an Update
UPDATE dbo.CheckSumTest SET vc1='b', vc2='a' WHERE id=1
UPDATE dbo.CheckSumTest SET vc1='a', vc2='b' WHERE id=2
--Check Meta-Data
SELECT * FROM dbo.TableAuditSummary WHERE LastUpdate>LastExport
--When we have Exported the data, we run the following to reset MetaData
UPDATE dbo.TableAuditSummary SET LastExport=GETDATE() WHERE LastUpdate>LastExport
最近我正在读关天SQLSERVER在线帮助(BOL)相关的知识, 我接触到了 SQL Server CHECKSUM(), BINARY_CHECKSUM(), and CHECKSUM_AGG() 这几个函数, 由此突然想到这些函数是不是也可以监控表的数据变化,而事实证明CHECKSUM_AGG() 函数尽管被描述为检测表的变化,但这里不适用.
使用 CheckSum() and CheckSum_Agg() 函数
CHECKSUM_AGG() 函数, 在Books OnLine 和许多相关的站点上是这样描述的, 通常用于检测一个表的数据是否更改. 这是一个代替触发器的更好的方法,只是该操作会引起表扫描的操作。于是我这次我仍然使用元数据来跟踪数据的变化,只是新建了列LastChkSum代替了LastUpdate,该列用于保存CHECKSUM_AGG(BINARY_CHECKSUM(*)),它将会在全表中产生一个唯一值,以区别数据的变化情况。
代码如下: Listing 2.
代码如下:
---------------------------------------------
--Method 2 : using CheckSum (not reliable)
---------------------------------------------
--Base Table Definition
IF OBJECT_ID('CheckSumTest', 'U') IS NOT NULL DROP TABLE CheckSumTest
GO
CREATE TABLE CheckSumTest
(
id int IDENTITY(1,1) NOT NULL PRIMARY KEY,
vc1 varchar(1) NOT NULL,
vc2 varchar(1) NOT NULL
)
GO
INSERT dbo.CheckSumTest (vc1, vc2) SELECT 'a', 'b'
INSERT dbo.CheckSumTest (vc1, vc2) SELECT 'b', 'a'
GO
--Create Audit Summary Table to hold Meta-Data
IF OBJECT_ID('dbo.TableAuditSummary', 'U') IS NOT NULL DROP TABLE dbo.TableAuditSummary
CREATE TABLE dbo.TableAuditSummary
( id INT IDENTITY(1,1) NOT NULL PRIMARY KEY,
TableName sysname NOT NULL,
LastChkSum INT NOT NULL
)
GO
INSERT dbo.TableAuditSummary (TableName, LastChkSum)
SELECT 'dbo.CheckSumTest', CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM dbo.CheckSumTest
GO
--Tables that need exporting
SELECT * FROM dbo.TableAuditSummary WHERE TableName='dbo.CheckSumTest'
AND LastChkSum(SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM dbo.CheckSumTest)
UNION ALL
...
--Make a Simple (Single row) Update
UPDATE dbo.CheckSumTest SET vc1='c', vc2='a' WHERE id=1
--Tables that need exporting
SELECT * FROM dbo.TableAuditSummary WHERE TableName='dbo.CheckSumTest'
AND LastChkSum(SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM dbo.CheckSumTest)
UNION ALL
...
--Reset MetaData
UPDATE dbo.TableAuditSummary SET LastChkSum=(SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM dbo.CheckSumTest)
WHERE TableName='dbo.CheckSumTest'
--Make a Symmetric change
UPDATE dbo.CheckSumTest SET vc1='b', vc2='a' WHERE id=1
UPDATE dbo.CheckSumTest SET vc1='c', vc2='a' WHERE id=2
--Tables that need exporting (no rows returned as CHECKSUM_AGG() has not changed!!)
SELECT * FROM dbo.TableAuditSummary WHERE TableName='dbo.CheckSumTest'
AND LastChkSum(SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM dbo.CheckSumTest)
UNION ALLCode Listing 2
正如你所看到的那样,对于单个的变化的情况,CHECKSUM是使用比较好的,但是CHECKSUM_AGG()却不能反应数据的变化
代码如下:Code Listing 3
代码如下:
--Base Table Definition
IF OBJECT_ID('CheckSumTest', 'U') IS NOT NULL DROP TABLE CheckSumTest
GO
CREATE TABLE CheckSumTest
(
id int IDENTITY(1,1) NOT NULL PRIMARY KEY,
vc1 varchar(1) NOT NULL,
vc2 varchar(1) NOT NULL,
chksum1 AS (CHECKSUM(id, vc1, vc2)),
chksum2 AS (BINARY_CHECKSUM(id, vc1, vc2))
)
GO
INSERT dbo.CheckSumTest (vc1, vc2) SELECT 'a', 'b'
INSERT dbo.CheckSumTest (vc1, vc2) SELECT 'b', 'a'
GO
--Show Computed Columns and CheckSum_Agg() value = 199555
SELECT * FROM CheckSumTest
SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM CheckSumTest
--Make a Simple (Single row) Update
UPDATE dbo.CheckSumTest SET vc1='c', vc2='a' WHERE id=1
--Show Computed Columns and CheckSum_Agg() value = 204816 (Ok)
SELECT * FROM CheckSumTest
SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM CheckSumTest
--Make a Symmetric change
UPDATE dbo.CheckSumTest SET vc1='b', vc2='a' WHERE id=1
UPDATE dbo.CheckSumTest SET vc1='c', vc2='a' WHERE id=2
--Show Computed Columns and CheckSum_Agg() value = 204816 (Not Ok!)
SELECT * FROM CheckSumTest
SELECT CHECKSUM_AGG(BINARY_CHECKSUM(*)) FROM CheckSumTest
我们会发现调整前后 CHECKSUM_AGG(BINARY_CHECKSUM(*)) 的值是一样的,不能区分
结论:
CHECKSUM_AGG() 函数尽管被描述为能监测表数据的变化,在实际测试中是不行的。尤其是对表进行对称数据修改时,无法监测
作者:Tyler Ning

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

InnoDB's full-text search capabilities are very powerful, which can significantly improve database query efficiency and ability to process large amounts of text data. 1) InnoDB implements full-text search through inverted indexing, supporting basic and advanced search queries. 2) Use MATCH and AGAINST keywords to search, support Boolean mode and phrase search. 3) Optimization methods include using word segmentation technology, periodic rebuilding of indexes and adjusting cache size to improve performance and accuracy.

The difference between clustered index and non-clustered index is: 1. Clustered index stores data rows in the index structure, which is suitable for querying by primary key and range. 2. The non-clustered index stores index key values and pointers to data rows, and is suitable for non-primary key column queries.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

In MySQL database, the relationship between the user and the database is defined by permissions and tables. The user has a username and password to access the database. Permissions are granted through the GRANT command, while the table is created by the CREATE TABLE command. To establish a relationship between a user and a database, you need to create a database, create a user, and then grant permissions.

MySQL supports four index types: B-Tree, Hash, Full-text, and Spatial. 1.B-Tree index is suitable for equal value search, range query and sorting. 2. Hash index is suitable for equal value searches, but does not support range query and sorting. 3. Full-text index is used for full-text search and is suitable for processing large amounts of text data. 4. Spatial index is used for geospatial data query and is suitable for GIS applications.

Data Integration Simplification: AmazonRDSMySQL and Redshift's zero ETL integration Efficient data integration is at the heart of a data-driven organization. Traditional ETL (extract, convert, load) processes are complex and time-consuming, especially when integrating databases (such as AmazonRDSMySQL) with data warehouses (such as Redshift). However, AWS provides zero ETL integration solutions that have completely changed this situation, providing a simplified, near-real-time solution for data migration from RDSMySQL to Redshift. This article will dive into RDSMySQL zero ETL integration with Redshift, explaining how it works and the advantages it brings to data engineers and developers.
