Team training session relating to high-level concepts in database querying

1. Database Querying
Tech Jam -25 november 2015
Rodger oates

2. Database Querying
• STUFF
• COALESCE vs ISNULL
• The LIKE Predicate
• Combining Predicates
• Joining Queries
• Table Expressions
• Window Functions

3. A Quick Note on Query Processing
1. FROM
2. JOINS
3. WHERE
4. GROUP BY
5. CUBE | ROLLUP
6. HAVING
7. SELECT
8. DISTINCT
9. ORDER BY
10. TOP

4. STUFF

5. REPLACE
• Used to replace parts of a string
• Will perform action through whole of original string
• Format
• REPLACE(<original>, <string to replace>, <replacement>)
• Note: <string to replace> and <replacement> do not need to be equal
in length

6. STUFF
• Used to insert one string into another
• Replaces characters in range specified with given string
• Format:
• STUFF(<original>, <start index>, <length>, <string to stuff>)
• Examples of use:
• www.sql-server-helper.com/

7. For XML PATH
• Can be used with STUFF to translate a table of results into a single
result.
• Real world example:
• Comma delimited list of names
• E.g. in names of users assigned to a given site
• See: Usage #6 in www.sql-server-helper.com

8. COALESCE vs ISNULL

9. ISNULL
• T-SQL specific
• Takes two inputs
• Format:
• ISNULL(<expression 1>, <expression 2>)
• Returns <expression 1> if not null, else <expression 2>
• Note: Data type of result is same as <expression 1> regardless of
which expression is returned

10. COALESCE
• Standard SQL
• Takes any number of inputs
• Format:
• COALESCE(<expression 1>, <expression 2>, …, <expression n>)
• Returns first input object that is not null
• Note: Data type of result is the same as the returned expression

11. The LIKE Predicate

12. Why LIKE?
• Used to find strings that are similar to a search term
• Without wildcards, predicate would only match with the search term
in its entirety, case insensitive
• With wildcards, we can find matches where only part of the string
matches our term
• Search terms that commence with wildcard(s) do not allow SQL to
use index ordering to speed up the query
• E.g UserFullName LIKE ‘%oates%’

13. Wildcards in LIKE
Source: Exam 70-461Training Kit

14. Combining Predicates

15. Types of combinations
• AND
• Predicates on both sides must be true
• OR
• Either predicate must be true
• NOT
• Negation of succeeding predicate
• Note: when predicate equates to NULL, the NOT of this predicate will still be
NULL

16. Natural Precedence Rules for Combinations
1. NOT
2. AND
3. OR
e.g.
WHERE col1 = ‘w’ AND col2 = ‘x’ OR col3 = ‘y’ AND col4 = ‘z’

17. Use of parentheses
• Can use parentheses if different precedence must be given to
predicates
• Previous example would equate to:
• WHERE (col1 = ‘w’AND col2 = ‘x’) OR (col3 = ‘y’ AND col4 = ‘z’)
• However, we could use:
• WHERE col1 = ‘w’ AND (col2 = ‘x’ OR col3 = ‘y’) AND col4 = ‘z’

18. Joining Queries

19. Joining Queries
• Types of Join
• Multi-Join Queries
• EXISTS
• Set Operators
• UNION vs UNIONALL
• INTERSECT
• EXCEPT

20. Types of Join
• CROSS JOIN
• Cartesian product of two tables
• Does not require a link between the tables
• INNER JOIN
• Requires a predicate between the tables (specified using the ON keyword)
• Filters out any rows that do not match the ON predicate
• SELF-JOIN
• Is simply an INNER JOIN
• Joins records in a table with other records in the same table

21. OUTER JOINS
• Outer joins preserve at least one side of the join if there is no match
• LEFT OUTER JOIN preserves the left table
• E.g. <tableA> LEFT OUTER JOIN <table B> preserves <table A>
• RIGHT OUTER JOIN preserves the right table
• E.g. <tableA> RIGHT OUTER JOIN <table B> preserves <table B>
• FULL OUTER JOIN preserves both tables where there is no match
• Further information on joins atTechNet

22. A Note on NULLs within JOINs
• Note: When determining row inclusion via predicate, a NULL value on
either side of the comparison will be discarded
• NULL is not a value, it is unknown

23. Multi-Join Queries
• Often need to look at multiple tables within the same query
• Use joins to link each table together
• Joins are evaluated in order of definition
• Need to be careful when combining outer joins with others, as the
results may not be what you expect

24. Example
Source: Exam 70-461Training Kit

25. Why was a supplier not returned?
Source: Exam 70-461Training Kit

26. How to get round this
Source: Exam 70-461Training Kit

27. EXISTS
• Accepts a subquery as input:
• WHERE EXISTS (SELECT … FROM <table>)
• Returns true if at least one row returned
• EXISTS doesn’t need to return the result of the subquery
• Rather, true or false depending on whether rows would have been
returned by the subquery
• Can be negated:
• WHERE NOT EXISTS (SELECT … FROM <table>)

28. Set Operator Guidelines
• Complete rows are matched between the input sets
• Number of columns in all queries must be the same
• Column types for corresponding columns must be compatible
• Considers two NULLs to be compatible
• This is different to JOINs
• Result column names are defined in the first query
• Result ordering can only be defined after the last input query

29. UNION vs UNION ALL
• UNION unifies the results of two input queries
• Both input queries must have
• UNION has an implicit DISTINCT property
• No duplicates in result
• UNION ALL returns all results, including any duplicates

30. UNION / UNION ALL UNION ALL

31. INTERSECT
• Only rows that exist in all input queries are returned
• Has an implicit DISTINCT operator

32. EXCEPT
• Works with two input queries
• Returns rows that exist in the first query, but not the second

33. Table Expressions

34. Types of Table Expression
1. DerivedTable
2. CommonTable Expression (CTE)
3. View
4. InlineTable-Valued Function
• 1 and 2 are only visible within the scope of the current statement and
are not reusable
• 3 and 4 have their definitions stored in the database and can be
reused

35. Optimisation Notes
• Table expressions are not tables, but definitions
• They do not hold any data
• They interact directly with the underlying tables
• They do not have a performance impact in themselves
• The above points must be noted when using a table expression within
a query operating on a large data set

36. Derived Tables
• Closely resemble a subquery
• Defined in the FROM clause of the outer query
• E.g. I want the two lowest priced products per category
Source: Exam 70-461Training Kit

37. Common Table Expressions (CTEs)
• Derived tables cannot be nested, if this is required, the statement
must define multiple instances of the same query
• Higher risk of mistake
• This is a CTE version of the previous query
Note: we could reuse C as many times as
we want, but only within the scope of the
current statement
Source: Exam 70-461Training Kit

38. A Note on Scoped Tables
• If you need to refer to the same data in multiple statements for a
given query it would be better to retrieve the data into a table.You
have two options:
• Create a temporary table
• CREATETABLE #<table name>
• Remember to use a DROPTABLE #<table name> command
• Declare a table variable
• DECLARE @<table name>TABLE
• This way, you are not having to go back to the raw tables to retrieve
the same data

39. Views and Inline Table-Valued Functions
• Define queries in the database, which can then be reused
• Do not store any data
• Performance issues arise from how it is used
• Views do not allow input parameters
• Functions do allow input parameters

40. Window Functions

41. Window Functions
• Window Aggregate Functions
• Window Ranking Functions

42. Window Aggregate Functions
• Same as group aggregate functions
• SUM,COUNT,AVG, MIN, MAX
• Are applied to a window of rows defined by the OVER clause
• Do not hide row detail
• Can mix detail and aggregated elements in the same query
• Without having to define a load of columns in the group section

43. Example

44. Window Ranking Functions
• ROW_NUMBER
• Unique number based on ORDER BY clause
• RANK
• Number based on ORDER BY clause
• Assigns same number when ordering values are tied
• Numbers may therefore not be sequential

45. Window Ranking Functions
• DENSE_RANK
• Similar to RANK
• Numbers are sequential
• NTILE
• Arranges rows within a partition of a number of equally sizes tiles
• Number of rows per partition is calculated by
• <total number of rows> / <partition size>
• If this calculation produces a remainder, additional row(s) are assigned to tiles in
their order defined by the ORDER BY clause (see example below)

46. Example
• Assuming 800 rows of data, and the following query
Source: Exam 70-461Training Kit

47. Example
custid orderid Val rownum rnk densernk ntile100
12 10782 12.50 1 1 1 1
27 10807 18.40 2 2 2 1
66 10586 23.80 3 3 3 1
76 10767 28.00 4 4 4 1
54 10898 30.00 5 5 5 1
88 10900 33.75 6 6 6 1
48 10883 36.00 7 7 7 1
41 11051 36.00 8 7 7 1
71 10815 40.00 9 9 8 2
38 10674 45.00 10 10 9 2
53 11057 45.00 11 10 9 2
75 10271 48.00 12 12 10 2
Source: Exam 70-461Training Kit

48. PARTITION
• Can be applied to window ranking functions
• Each partition has its own numbering
• E.g. to get the latest child event for each parent

49. Resources
• STUFF: www.sql-server-helper.com
• JOINS:TechNet
• Training:
• MicrosoftVirtual Academy
• MSDN
• Reference tutorial:
• http://www.tutorialspoint.com/sql/sql_tutorial.pdf