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DDL Triggers are AFTER triggers December 24, 2016

Posted by fofo in Sql Server, Sql Server 2005, SQL Server 2008, SQL Server 2012, SQL Server 2014, SQL Server 2016.
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In this post I would like to look into DDL triggers and explain their functionality.

Let me start with a short introduction on triggers

All SQL Server developers use SQL triggers that basically is a mechanism that is invoked when a particular action occurs on a particular table.

Triggers consist of

  • A name
  • An action
  • The execution

The maximum size of a trigger name is 128 characters.
The action of a trigger can be either a DML statement (INSERT, UPDATE, or DELETE) or a DDL statement (CREATE, ALTER, DROP)
Therefore, there are two trigger forms: DML triggers and DDL triggers.


The AFTER and INSTEAD OF options are two additional options that you can define for a trigger.

  • AFTER triggers fire after the triggering action occurs.
  • INSTEAD OF triggers are executed instead of the corresponding triggering action.
  • AFTER triggers can be created only on tables, while INSTEAD OF triggers can be created on both tables and views

DDL triggers were introduced in SQL Server 2005. DDL triggers are not INSTEAD OF triggers.

They are implemented as AFTER triggers, which means the operation occurs and is then caught in the trigger.

The the operation can be  optionally rolled-back, if you put a ROLLBACK statement in the trigger body.
This means they’re not quite as lightweight as you might think. Imagine doing the following:

ALTER TABLE MyTable ADD newcolumn VARCHAR (30) DEFAULT ‘default value’;

If we have a DDL trigger defined for ALTER_TABLE events, or DDL_TABLE_EVENTS, the trigger due to the above T-SQL batch will fire and every row in the table will be expanded to include the new column (as it has a non-null default), and the operation is rolled back by your trigger body.

Type (copy paste) the following T-SQL statements in a new query window in the SSMS



USE sampleDB;


 pname NVARCHAR(50) ,
 price DECIMAL(18, 4)

 PRINT 'Not Alter Statements are permitted on the tables of this DB'
 SELECT EVENTDATA().value('(/EVENT_INSTANCE/TSQLCommand/CommandText)[1]',
 RAISERROR ('Tables cannot be altered in this database.', 16, 1) 

ALTER TABLE dbo.Product ADD newcolumn VARCHAR (30) DEFAULT 'default value'; 

Let me explain what I do in the code above.

I create a sample database. I create sample empty table. I create a trigger “Not_Alter_tables” on this database. This trigger applies to all the tables in the database.

This trigger is a DDL trigger, hence an AFTER trigger. In the trigger I capture the T-SQL statement that invoked the trigger, I print a statement, raise an error and then rollback the operation.

Then I attempt to add a new column in the table.

In this example, when the trigger is invoked, the table will be expanded to include the new column (as it has a non-null default), and then the operation is rolled in the trigger body.

Have a look at the picture below.



In a nutshell DDL triggers are AFTER triggers and can be quite expensive. In the example above the best way is not to use DDL triggers but to use instead explicit permissions e.g REVOKE/DENY to prevent users from altering the schema of the table.

Hope it helps!!!

Looking into DMVs in SQL Server for Performance Tuning May 17, 2015

Posted by fofo in Sql Server, SQL Server 2008, SQL Server 2012, SQL Server 2014.
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I have been delivering a Microsoft Certified Course in MS SQL Server 2014 recently and I was highlighting with several examples and demos the importance of DMOs (DMVs and DMFs) in SQL Server. We can get a plethora of information regarding server state and monitor the health of a server instance, diagnose problems and tune performance with those objects.

In this post I will demonstrate with hands-on demos the power of DMVs and show how they can help a DBA, developer to identify expensive queries, low usage indexes, and check the fragmentation levels of indexes. These are very common problems that anyone that deals with an SQL Server database must look out for and troubleshoot. There are two types of DMVs, server scoped, which require the view server state permission on the server, and database scoped, which require the view database state permission on the database.

By querying these view with T-SQL statements, a lot of information is made available to the DBA. When you make a call to a DMV, you must use a minimum of a two part naming convention.

DMVs can be of very reliable resource for information about the performance of your system, but each time your SQL Server is restarted, the data in the views is reset.

I have installed SQL Server 2014 Enterprise edition in my machine but you can use the SQL Server 2014/2012/2008 Express edition as well (or any other edition).

I am connecting to my local instance through Windows Authentication.

The first query I’m going to run is for identifying fragmentation levels of indexes within the database. 

The more fragmented an index is, the slower it performs. I am going to use the DMV dm_db_index_physical_stats cause I’m looking at the statistics of how the indexes are physically laid out within SQL Server. The view returns the size and fragmentation details for the data and the indexes of a specified table or view. Fragmentation of indexes and tables can drastically affect performance of queries and maintenance, so this is a very good DMV to get familiar with.

Before I run my script let me explain a few things regarding Internal fragmentation.

Internal fragmentation occurs if there is unused space between records in a page. This fragmentation occurs through the process of data modifications (INSERT, UPDATE, and DELETE statements) that are made against the table and therefore, to the indexes defined on the table. This unused space causes poor cache utilization and more I/O, which ultimately leads to poor query performance.

I am connecting to a database that I am going to use for all of my demos and I open a new query window. Type (copy-paste the following)

USE mydb

EXEC sp_configure 'show advanced options', 1
DECLARE @DefaultFillFactor INT
 Name VARCHAR(100)
 ,Minimum INT
 ,Maximum INT
 ,config_value INT
 ,run_value INT
INSERT INTO @Fillfactor
 EXEC sp_configure 'fill factor (%)'
SELECT @DefaultFillFactor = CASE WHEN run_value = 0 THEN 100
 ELSE run_value
FROM @Fillfactor 

 ,QUOTENAME(s.name) AS SchemaName
 ,QUOTENAME(o.name) AS TableName
 ,i.name AS IndexName
 ,stats.Index_type_desc AS IndexType
 ,stats.page_count AS [PageCount]
 ,CASE WHEN i.fill_factor > 0 THEN i.fill_factor
 ELSE @DefaultFillFactor
 END AS [Fill Factor]
 ,CASE WHEN stats.index_level = 0 THEN 'Leaf Level'
 ELSE 'Nonleaf Level'
 END AS IndexLevel
FROM sys.dm_db_index_physical_stats(DB_ID(), NULL, NULL, NULL, 'DETAILED')
 AS stats
 ,sys.objects AS o
 ,sys.schemas AS s
 ,sys.indexes AS i
 AND s.schema_id = o.schema_id
 AND i.index_id = stats.index_id
 AND stats.avg_page_space_used_in_percent <= 85
 AND stats.page_count >= 10
 AND stats.index_id > 0
ORDER BY stats.avg_page_space_used_in_percent ASC
 ,stats.page_count DESC

Execute the code above and see the results.

Have a look at the picture below to see what results I have got.


Let me explain what the code above does.

At the beginning I am  just turning on some advanced options, re-configuring.

I am creating a temporary table variable to hold some information. I’m going to join the DMV with other objects, schemas, and indexes (system views) just to get more information.

In the Select list, I get information like the database name, the schema name, the table name, the index name, the index type, the page count, the fillfactor, the average page space used in percent and the index level.

Then I am using some of conditions like avg_page_space_used_in_percent is less than 85% and more than 10 pages in size for an index.

Then I’m  ordering them by the average page space used in percent (This is an average percentage use of pages that represents  internal fragmentation. Higher the value, the better it is. If this value is lower than 80%, then action should be taken) and then by the page count descending so the ones with the most pages come up first.  By all means do use this query for identifying fragmentation issues in your databases.

The second query I have is using the dm_execute_query_stats DMV, to identify our top 10 queries ranked by average CPU time. The query output will show us the statements that are the most expensive as far as resources and overhead regarding the CPU.

Knowing which are these queries, I can rewrite them in a way that will cause much less overhead.

In a new query window, type (copy-paste the following).

USE master

SELECT TOP 10 query_stats.query_hash AS "Query Hash",
 SUM(query_stats.total_worker_time) / SUM(query_stats.execution_count) AS "Average CPU Time",
 MIN(query_stats.statement_text) AS "SQL Statement"
 SUBSTRING(ST.text, (EQS.statement_start_offset/2) + 1,
 ((CASE statement_end_offset
 ELSE EQS.statement_end_offset END
 - EQS.statement_start_offset)/2) + 1) AS statement_text
 FROM sys.dm_exec_query_stats AS EQS
 CROSS APPLY sys.dm_exec_sql_text(EQS.sql_handle) as ST) as query_stats
GROUP BY query_stats.query_hash

Execute the  code above against your database and see the results.

Have a look at the picture below to see my results.


In the next demo I am going to use the dm_os_wait_stats DMV and actually do some calculations to show the ratio of time spent waiting for a CPU to free up and give us some processing power or for another resource such as memory or the disks to free up.

In a new query window, type (copy-paste the following).

USE master
Select signal_wait_time_ms=sum(signal_wait_time_ms)

 ,'%signal (cpu) waits' = cast(100.0 * sum(signal_wait_time_ms) / sum (wait_time_ms) as numeric(20,2))

 ,resource_wait_time_ms=sum(wait_time_ms - signal_wait_time_ms)

 ,'%resource waits'= cast(100.0 * sum(wait_time_ms - signal_wait_time_ms) / sum (wait_time_ms) as numeric(20,2))

From sys.dm_os_wait_stats

Execute the  code above against your database and see the results.

Have a look at the picture below to see my results.


On this server, we’re looking at about 15 % of the time is spent waiting on processing power to become available, versus almost 85% of the time is spent waiting usually for the disks to catch up and be able to give us the information that we need to load into memory or even for it to find it in the memory.

This indicates that I have a powerful enough server as far CPU is concerned but I have to look at how much memory is used and what my disk drives are doing and how well my storage is optimized on this server.

In this query I am going to use the dm_db_index_usage_stats DMV. I want to look at indexes and see how often are they used. If I have indexes that have not been used since the server’s restart and the server’s been running for a long time, then I probably do not need these indexes.

If the indexes are not being used, every time a table is updated by inserting, updating, deleting a record, the index is also being updated or changed in the table. The more indexes you have that are not being used, the more time you’re going to spend updating indexes and maintaining them. When it comes to defragmenting indexes, you’re going to be defragmenting indexes that you don’t even use.

USE mydb

SELECT o.name ,
 indexname = i.name ,
 i.index_id ,
 reads = user_seeks + user_scans + user_lookups ,
 writes = user_updates ,
 rows = ( SELECT SUM(p.rows)
 FROM sys.partitions p
 WHERE p.index_id = s.index_id
 AND s.object_id = p.object_id
 ) ,
 CASE WHEN s.user_updates < 1 THEN 100
 ELSE 1.00 * ( s.user_seeks + s.user_scans + s.user_lookups )
 / s.user_updates
 END AS reads_per_write ,
 'DROP INDEX ' + QUOTENAME(i.name) + ' ON ' + QUOTENAME(c.name) + '.'
 + QUOTENAME(OBJECT_NAME(s.object_id)) AS 'drop statement'
FROM sys.dm_db_index_usage_stats s
 INNER JOIN sys.indexes i ON i.index_id = s.index_id
 AND s.object_id = i.object_id
 INNER JOIN sys.objects o ON s.object_id = o.object_id
 INNER JOIN sys.schemas c ON o.schema_id = c.schema_id
WHERE OBJECTPROPERTY(s.object_id, 'IsUserTable') = 1
 AND s.database_id = DB_ID()
 AND i.type_desc = 'nonclustered'
 AND i.is_primary_key = 0
 AND i.is_unique_constraint = 0
 AND ( SELECT SUM(p.rows)
 FROM sys.partitions p
 WHERE p.index_id = s.index_id
 AND s.object_id = p.object_id
 ) > 20000
ORDER BY reads

Execute the  code above against your database and see the results.

Have a look at the picture below to see my results.


The query pulls some information since our server restarted to show which indexes have not been run that often.I have placed a filter  that says I have to have at least 20,000 rows in a table for my query results to have a practical value. You can see that I am looking for reads, writes and their ratio to see if it is worth keeping the index.

With DMVs we are  monitoring performance with minimal overhead. There are many DMVs available to us at the moment and  more are added with new versions of SQL Server.

Hope it helps!!!