Your query returns the correct results, but even with supporting indexes it seems slow. Can it go any faster? In this session, we focus on T-SQL query antipatterns – commonly used techniques that are unintentionally counter-productive. Through an interactive story of user requests, we identify several antipatterns, examine what makes them troublesome, and show alternative methods to improve performance.

1. Breaking Bad Habits
Solutions for Common Query
Antipatterns
Jeff Iannucci

2. Who in the world is Jeff Iannucci?
I live in Arizona, and I sell used cars!
@desertdba
jeff@desertdba.com
desertdba.com
Senior Database Administrator at DriveTime
SQL Server data professional since 1998

3. Session Goals
WHAT are some T-SQL antipatterns?
WHY are they antipatterns?
HOW can we correct them?

4. 4
https://desertdba.com
WARNING!
Some index discussion!
Execution plans ahead!
(Image courtesy of designerpoint via pixabay)
…and more dog pictures!

5. What is an antipattern?
“A technique
that is intended
to solve a problem
but often leads to
other problems.”
-Bill Karwin

6. How to discuss antipatterns?
1. Scenario
2. Example
3. Name
4. Reasons
5. Solution

7. About these antipatterns…
They are all common T-SQL solutions
They all return a correct result set
…but they perform unnecessary work

8. Who is using antipatterns?
“Boss” “Junior”

9. 9
https://desertdba.com
Selection antipatterns
(Image courtesy of TheDigitalWay via pixabay)

10. Boss request #1
Hey!
Let’s find anyone
Named “Barker”
Because maybe
We are related!

11. Junior’s query #1

12. What’s wrong with “SELECT *”?
Read more data
Use more memory
Take more time

13. What about that Execution Plan?

14. What determines an Execution Plan?
Your query
Statistics
Server/Database Settings
Indexes
Optimizer Rules

15. How to see an Execution Plan

16. Antipattern: Unnatural SELECTion

17. A better way

18. How can we measure the difference?

19. Let’s compare the logical reads

20. Boss request #2
Hey!
I just had a killer workout
Chasing a yellow car
It looked magnificent!
I want a list of orders
With any yellow products
ASAP!

21. Junior’s query #2

22. Antipattern: DISTINCT disadvantage

23. DISTINCT = GROUP BY

24. A better way

25. What about the logical reads?

26. 26
https://desertdba.com
Joining antipatterns
(Image courtesy of violeta via pixabay)

27. Boss request #3
Hey!
Let’s find any US State
With Persons named “Jr”
Who ordered anything black
Because your name
And my color
Are awesome!

28. Junior’s query #3

29. Antipattern: JOIN-zilla

30. A better way

31. What about table variables?

32. Characteristic #TempTable @TableVariable
Can be altered
Can be truncated
Can be used with SELECT INTO
Has statistics
Can participate in a transaction
Writes only to memory
Avoids writing to the log file
Avoids a recompile in procedure
Can be passed from a function

33. Common Table Expressions?

34. Common Table Expressions?
Not a fair comparison
Can have poor estimates
CTEs are not materialized
…and poor execution plans

35. If you use CTEs…
Use minimal JOINs
Keeps estimates closer
Use minimal columns in SELECT
…but still not consistent

36. Boss request #4
Hey!
I just went for another run
Actually, I fetched the mail
And now I am exhausted
But I was wondering
Are any of our customers
Missing a mailing address?

37. Junior’s query #4

38. Antipattern: Avoiding the Semi

39. A better way

40. Comparison: Elapsed CPU Time

41. 41
https://desertdba.com
Predicate antipatterns
(Image courtesy of Pezibear via pixabay)

42. Boss request #5
Hey!
I was born in 2012
It is my favorite year
Let’s find how many orders
We had that year
Because
It is my favorite year!

43. Junior’s query #5

44. Antipattern: Fallacious arguments
This is not “SARGable”
SARGable - Able to efficiently use an index
for a search argument

45. So…what else is not SARGable?

46. So…what else is not SARGable?
Description Example
LIKE with a leading wildcard
Most functions
Conversions
Operators
CASE statements
Concatenating columns

47. And…what else is not SARGable?
Description Example
JOINs
GROUP BY
ORDER BY

48. What’s the solution?
“Embrace Verbosity!”
Vern Rabe says:

49. A better way

50. Show me the logical reads!

51. Boss request #6
Hey!
I need a report
To find any order shipped
On a given day
Or, any unshipped orders
Also, I am tired
And wish to take a nap

52. Junior’s query #6

53. Antipattern: A Lot of Nothing
Déjà vu - this is also not “SARGable”

54. A better way

55. An even better way

56. Tell me more about INTERSECT
INTERSECT – finds distinct common values
INNER JOIN – matches data
Rule #1: column name & order must match
Rule #2: column data types must match
Set1 Set2

57. How many logical reads this time?

58. Boss request #7
Hey!
We got a charge back
And we might have more
We need to find the SalesID
For an approval code
I will Slack you the code
And then take another nap

59. Junior’s query #7

60. Antipattern: Involuntary conversion

61. What are Implicit Conversions?
Did you say…?
(Image courtesy of BarkPost)

62. What about Precedence?
Data of lower precedence
must be implicitly converted
to be compared to data of
higher precedence
*The Fine Print
Abbreviated chart.
Includes only
commonly used data
types. There are 30
different data types in
the full chart, with User-
Defined Data Types
occupying the highest
precedence.

63. A better way

64. “sql authority find implicit conversion”
https://blog.sqlauthority.com/2017/01/29/find-all-queries-with-implicit-conversion-in-sql-server-interview-question-of-the-week-107/
Pinal Dave says:

65. “A final ask”
Hey!
I just woke up from a nap
And I wanted to reach out
To briefly touch base
With a final ask
To see if we can circle back
For a helicopter view

66. Junior’s Summary
Something about Index Seeks
Confusing execution plans
A bunch of dog pictures

67. Antipattern Characteristic Solution
Unnatural SELECTION SELECT * Limit column selection
DISTINCT Disadvantage SELECT DISTINCT… WHERE IN (…)
JOIN-zilla Optimization “Time Out” Break it up
Avoiding the Semi LEFT JOIN…WHERE NULL WHERE NOT EXISTS (…)
Fallacious Arguments Not SARGable “Embrace verbosity”
A Lot of Nothing ISNULL() = ISNULL() EXISTS & INTERSECT
Involuntary Conversion CONVERT_IMPLICIT Match all data types

68. And now…
Here is IDERA’s Tep Chantra
with a demo of
SQL Diagnostic Manager…

69. What questions do you have?

70. That’s the end. Thank you!
“Seven” “Daphne”
@desertdba
jeff@desertdba.com
desertdba.com