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The Voice of the DBA

How Long Before You Upgrade?

It's 2014. SQL Server 2000 is 14 years old, but there are still quite of you managing instances. SQL Server 2005 is 9 years old, and I'm sure more of you still deal with that version. I know because I work for a software vendor and I'm constantly asked if our software will run against those two versions of SQL Server.

For many of you, however, if you're managing a SQL Server 2000 instance, it might only be 9 or 10 years old. Your company might still have been installing SQL Server 2000 in the year 2005. The same is true for SQL Server 2005. I wouldn't be surprised to find companies still installing 2005 instances in 2008 or even 2009.

Companies don't care much about versions. They tend to mostly care about databases getting the job done, and sometimes, support. Many organizations don't see value in upgrading too often because of the overhead. I suspect many managers would prefer to get many years usage out of a platform before they change in order to minimize work that doesn't add value to their business.

The question this week asks you about the longevity of your database instances. Think about the average instance, or even the majority of your applications and how long they will remain on a particular version.

How many years will you run a platform before you upgrade it?

Years ago I heard someone at a large Fortune 100 company say their stated policy was to get 10 years of service out of a database server. At the time I thought that was a long time, but the more I think about it, the more I think that might be a minimum amount of time I'd want from a platform.

Let us know this week what you experience, and perhaps what you'd prefer.

Steve Jones from SQLServerCentral.com

Join the debate, and respond to today's editorial on the forums


The Voice of the DBA Podcast

Listen to the MP3 Audio ( 2.2MB) podcast or subscribe to the feed at iTunes and LibSyn. feed

The Voice of the DBA podcast features music by Everyday Jones. No relation, but I stumbled on to them and really like the music. Support this great duo at www.everydayjones.com.

Everyday Jones

Follow Steve Jones on Twitter to find links and database related items and announcements.

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Paging Doctor Powershell

Zach Mattson from SQLServerCentral.com

Use Powershell to create a single script that checks over your server and every SQL instance on it to help pinpoint problems. More »


 

The DBA Detective: Disturbing Developments

Additional Articles from SimpleTalk

Originally one of the articles in the first DBA Team series, Grant wonders what Raymond Chandler or Dashiell Hammett would have done if asked to write technical articles for Simple-Talk. He came up with the DBA detective, hard-boiled Joe Dee Beay. More »


 

SQL Saturday #285 Atlanta

Press Release from SQL Saturday

SQL Saturday will come to Atlanta on May 3, 2014. This is a free, full-day event of SQL Server training and networking. SQL Saturday #285 also has 3 (paid for) pre-con sessions available run by Kalen Delaney, Teo Lachev, and Denny Cherry. Make sure to register for SQL Saturday while spaces are available. More »


 

From the SQLServerCentral Blogs - Speaker of the Month, April 2014

Grant Fritchey from SQLServerCentral Blogs

I’m really enjoying picking a speaker of the month. It forces me to sit through a lot more sessions at... More »


 

From the SQLServerCentral Blogs - Why So Serious? – #TSQL2sDAY #53

Tracy McKibben from SQLServerCentral Blogs

As a child/pre-teen/teenager/young adult, OK, most of my life, I’ve been labeled as “serious” or “grumpy”. Maybe I deserve it... More »


 

From the SQLServerCentral Blogs - T-SQL Tuesday #53: Why so serious

Kenneth Fisher from SQLServerCentral Blogs

Why so serious? If you ask anyone who knows me they will tell you I’m not a terribly serious person.... More »

Question of the Day

Today's Question (by Lara Rasner):

The question refers to the following simplified stored procedure:

CREATE PROCEDURE dbo.TestProcedure
AS
BEGIN

 SET NOCOUNT ON;

 CREATE TABLE #table (Id INT NOT NULL);

 INSERT INTO #table (Id) VALUES (42), (21), (590);

 SELECT Id FROM #table;

END;

Select the two answer below are that are TRUE:

Think you know the answer? Click here, and find out if you are right.


We keep track of your score to give you bragging rights against your peers.
This question is worth 2 points in this category: Temporary Tables.

We'd love to give you credit for your own question and answer.
To submit a QOTD, simply log in to the Contribution Center.

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Yesterday's Question of the Day

Yesterday's Question (by Auke Teeninga):

Given the query below, what result will be returned when you execute the query? 
declare @message varchar(15)

begin try
   print 1/0
   set @message = 'Query completed'
end try

begin catch

end catch

print IsNull(@message, 'Query completed with errors')

Answer: Query completed

Explanation:

The return type of IsNull function is the same as the check_expression. In this case varchar(15). The message 'Query completed with errors' is truncated to a length of 15, so only 'Query completed' remains.


» Discuss this question and answer on the forums

Featured Script

Index Breakdown

Sean Smith from SQLServerCentral.com

I've always been wary about dealing with indexes and indexing strategies. As I learn more and more about the subject I realize how little I actually know. On the surface indexing can appear quite simple and straightforward. But the reality is that indexing requires a great deal of knowledge, can differ from environment to environment, and is basically an art form.

A while back I was tasked with investigating performance issues within an application driven by a SQL Server database solution. It ended up coming down to improper indexing, but in the course of the investigation I started to notice other, unrelated, indexing issues. As I dug further I needed more and more data to properly assess each and every index in the database (I won't go into further details but the design was a disaster to say the least). By the time I had finished my investigation and applied my fixes I was left with a fairly robust script that lists out many details regarding each and every index contained within a database.

Below is a listing of all the fields in the output. It's somewhat overwhelming at first, but depending on what one column's output is will determine what additional columns you'll likely want to look at. I will try to explain how I evaluate the data though I won't go through all of the columns nor will I go into any extensive details as you should already have a decent understanding of indexes if you're going to be using the script for any type of troubleshooting and / or architectural restructuring.

NOTE: I do not claim to be an indexing expert in any way, shape, or form. I simply want to make available to others what I've learned as well as to share some code which might come in handy for individuals who find themselves in a situation similar to the one I experienced. Also, be very careful when playing around with indexes. What seems like a good idea / change could have an extremely negative impact!

Output Columns:

  • object_type: type of object (will either be "U" for User-Defined Table or "V" for View)
  • database_name: name of the database
  • schema_name: name of the schema
  • object_name: name of the object
  • create_date: date the object was created (time portion truncated, meant to give a general idea of how long ago the object was created)
  • modify_date: date the object was last modified (time portion truncated, will contain ".................." if it is the same date as the create_date column)
  • rows: total rows of data contained within the object
  • total_mb: total size of the object in megabytes
  • used_mb: total space used in megabytes
  • unused_mb: space reserved but not yet allocated in megabytes
  • data_mb: space used by data in megabytes
  • index_mb: space used by indexes in megabytes
  • pct_data: percentage of space used which is allocated to data
  • pct_index: percentage of space used which is allocated to indexes
  • index_type: type of index (Clustered, Nonclustered, Heap)
  • index_name: name of the index
  • system_named: indicates if the index name was generated by SQL Server or explicitly named (applicable to PKs and Unique Constraints / Indexes only)
  • is_pk: indicates if the index is a primary key
  • unique: indicates if the index is unique and whether its uniqueness if enforced by the index definition (displayed as "I") or a constraint (displayed as "C")
  • disabled: indicates if the index is disabled
  • hypothetical: indicates if the index is hypothetical
  • total_columns: number of columns which comprise the entire object
  • index_columns: number of columns which comprise the index key
  • include_columns: number of columns which comprise the include key
  • index_pct_of_columns: percentage of columns that make up the index as compared to the entire object
  • include_pct_of_columns: percentage of columns that make up the include as compared to the entire object
  • total_pct_of_columns: percentage of columns that make up the index + include as compared to the entire object
  • key_mb: space used by this particular index in megabytes
  • key_mb_pct: percentage of space used as compared to total space allocated to all indexes on the object
  • max_key_size_bytes: maximum possible byte size of the index based on the data size(s) of the column(s) involved
  • over_key_size_limit: indicates if the index key size exceeds the 900 byte limit
  • index_key: list of columns which comprise the index (ordinal sort) showing column name, data type, size, precision, scale, and sort order (ascending / descending)
  • include_key: list of columns which comprise the include portion of the index (ordinal sort) showing column name, data type, size, precision, scale, and sort order (ascending / descending)
  • filter_definition: filtered index definition / criteria
  • dupe_id: Indicates if the index is a duplicate (assigns a random "dupe group" ID and shows a count of total times the index is duplicated)
  • unused: indicates if the index is unused and therefore can potentially be dropped (does not look at PKs, Indexed FKs, Clustered Indexes, Unique Indexes / Constraints)
  • statistics_date: date when statistics were last updated on the index (blank for Heaps)
  • row_locks: indicates if the index allows row locks
  • page_locks: indicates if the index allows page locks
  • ignore_dupes: determines the error response when an insert operation attempts to insert duplicate key values into a unique index
  • auto_stats: indicates if statistics are automatically recomputed
  • padded: indicates if index padding is used
  • fill_factor: percentage of space to use when the index is created / rebuilt
  • user_seeks: total seeks by user queries
  • user_scans: total scans by user queries
  • user_lookups: total bookmark lookups by user queries
  • user_updates: total updates by user queries
  • last_user_seek: date of last user seek (time portion truncated)
  • last_user_scan: date of last user scan (time portion truncated)
  • last_user_lookup: date of last user lookup (time portion truncated)
  • last_user_update: date of last user update (time portion truncated)
  • system_seeks: total seeks by system queries
  • system_scans: total scans by system queries
  • system_lookups: total bookmark lookups by system queries
  • system_updates: total updates by system queries
  • last_system_seek: date of last system seek (time portion truncated)
  • last_system_scan: date of last system scan (time portion truncated)
  • last_system_lookup: date of last system lookup (time portion truncated)
  • last_system_update: date of last system update (time portion truncated)

Some Things To Keep In Mind / Look For Right Off The Bat:

  • Check the dupe_id column first, this is the easiest way to find low-hanging fruit
  • Check the unused column, but keep in mind how often the data is accessed and how long the instance has been online before deciding to drop any indexes
  • Make sure your statistics are up to date as this plays a large roll on how and when indexes are (or not) used
  • Compare how much of the object's space is used by indexes, and if it seems overly large consider dropping indexes which are rarely used and / or do little other than take up space
  • Check to make sure your index does not exceed the maximum index key size (see the over_key_size_limit column for this)
  • Even if an index is used, consider looking at the number of user_scans, user_seeks, etc. columns (if it is low then the index is likely not utilized that often and you are really just incurring a penalty to maintain it)
  • If an index is used, check to make sure it's not simply being used by the system for things such as updating statistics (check the system_scans, system_seeks, etc. columns)

Some Final Notes On The Script:

  • Certain rows of the output will have duplicate information suppressed for easier readability
  • The script does not include Spatial Indexes, XML Indexes, etc. (only Heaps, Clustered Indexes, and Non-Clustered Indexes), and some corresponding data values (such as size details) are calculated on these attributes only
  • Percentage breakdowns may not roll up to exactly 100% due to rounding issues
  • Certain stats (such as seeks / scans) on indexed views may not be what you'd expect (this will depend on how you query the object, for example whether you use WITH (NOEXPAND) or not on indexed views)
  • If you wish to run this on SQL Server 2005 you will need to comment out any code which references filter_definition

Any friendly feedback is always welcome. Enjoy!

More »

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