In my last post, I talked about how you can get 43%-67% faster backups. This time, I’m using that same SQL Server setup to discuss how throwing more CPU cores might help you check for corruption faster if you’ve already got modern fast storage.
2020-09-28
Introduction A popular joke about DBAs and database backups goes like this. There are two types of DBAs: DBAs that do backups DBAs that will do backups The joke is only stating the obvious – lack of database backups might be the end of a DBA career and/or the supported business. Unfortunately, that joke fails […]
2020-01-07
9,813 reads
In this tip we look at to create a SQL Server DBCC CHECKDB errors email formatted in an HTML table. This will report any errors for all of your databases on the server.
2018-10-24
2,764 reads
The SQL Server model database is one of the core system databases, but it seem to get less attention in terms of importance. This post from Simon Liew will demonstrate the havoc the model database can cause when database integrity checks exclude the model database and corruption goes undetected.
2017-01-26
4,940 reads
DBCC CHECKDB is a built-in SQL Server command that allows you to check database integrity and consistency in one simple command, but running it on large databases can be a nightmare. In this article, Ahmad Yaseen explains how you can enhance the command to run faster in SQL Server 2016.
2016-09-28
3,423 reads
An enhanced version of a script originally posted by Robert Pearl some time ago. It now takes into account changes in the tabelresults for CHECKDB in latter versions of SQL Server.
2016-05-04 (first published: 2016-04-20)
1,221 reads
Sometimes running DBCC CHECKDB WITH DATA_PURITY returns thousands of affected columns. This script automates the identification of those columns.
2015-04-13 (first published: 2013-07-04)
2,413 reads
This article describes a utility that is able to report the most common DBCC CHECKDB errors significantly faster than DBCC CHECKDB does itself.
2011-08-23
15,317 reads
Ever restored a corrupted database from the backup, only to find that the backups are corrupted too - All the backups? Sure it can happen and it isn't nice when it does. To check that a database backup is internally consistent you have to use DBCC CheckDB. On a huge highly-loaded live system? Grant Fritchey has, as usual, a practical solution.
2011-05-02
3,896 reads
2009-09-17
5,021 reads
By Kevin3NF
Common Reasons for Emergency SQL calls If you are a production DBA (or Accidental...
By Steve Jones
I grabbed this book over the 2024 holiday season as it was on sale...
By Steve Jones
Investing small amounts of money over a long time works miracles, but no one...
When running clone sql is changing one specific table to History table and its...
Comments posted to this topic are about the item What is time?
Hello experts, The following SQL update is failing to install on some of our...
Consider the following script for a Sql Server database with Compatibility Level at least 130 (Sql Server 2016):
create table tjson ( id int primary key, j1 varchar(max), j2 varchar(max), j3 varchar(max)); insert into tjson (id, j1, j2, j3) values (1, '[{"c11":"value11A", "c12":"value12A"},{"c11":"value11B", "c12":"value12B"}]', '[{"c21":"value21A", "c22":"value22A"},{"c21":"value21B", "c22":"value22B"}]', '[{"c31":"value31A", "c32":"value32A"},{"c31":"value31B", "c32":"value32B"}]');How many rows does the Query Optimizer estimate for the following query?
select id, c1.c11, c2.c21, c2.c22, c3.c31, c3.c32 from tjson cross apply openjson(j1) with( c11 varchar(50) '$.c11', c12 varchar(50) '$.c12') c1 cross apply openjson(j2) with( c21 varchar(50) '$.c21', c22 varchar(50) '$.c22') c2 cross apply openjson(j3) with( c31 varchar(50) '$.c31', c32 varchar(50) '$.c32') c3;See possible answers