Introduction to Clustered Indexes and Heaps

Introduction to Clustered Indexes
and Heaps

Jason
Strate
e: jstrate@pragmaticworks.com
e: jasonstrate@gmail.com
b: www.jasonstrate.com
t: StrateSQL
Resources jasonstrate.com/go/indexing
Introduction
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Agenda
Introduction The Heap Clustered Index
Index Patterns Summary

Session Goals
• Define differences between
heaps and clustered indexes
• Explain design considerations
• Demonstrate differences
between key column choices

THE HEAP
Introduction The Heap
Clustered
Index
Index
Patterns
Summary

Heap Structure
• Pile of data
– Unordered
– First in, first out
– Scan “happy”
• Table Scan Access
• Forwarded Records

Heap

THE HEAP
Demo

CLUSTERED INDEX
Clustered
Index
Index
Patterns
Summary

Clustered Index
• Mechanism for storing data
– Logically ordered
– Structured
– Accessible
– Direct path

Clustered Index

Clustered Index Qualities
Static Narrow
Unique
Ever-
increasing

Static
Non-static key columns can reshuffle the rows in
the clustered index.

Narrow
Key columns from clustered indexes are included
in all non-clustered indexes.
Size
Rows 4 8 16 32 64
10,000 0.04 0.08 0.15 0.31 0.61
100,000 0.38 0.76 1.53 3.05 6.10
1,000,000 3.81 7.63 15.26 30.52 61.04
10,000,000 38.15 76.29 152.59 305.18 610.35
100,000,000 381.47 762.94 1,525.88 3,051.76 6,103.52
1,000,000,000 3,814.70 7,629.39 15,258.79 30,517.58 61,035.16

Unique
Uniqueifier: Adds a 4-byte integer to rows non-
unique clustered indexes to create unique rows.
Size
Rows 4 8 16 32 64
10,000 0.08 0.11 0.19 0.34 0.65
100,000 0.76 1.14 1.91 3.43 6.48
1,000,000 7.63 11.44 19.07 34.33 64.85
10,000,000 76.29 114.44 190.73 343.32 648.50
100,000,000 762.94 1,144.41 1,907.35 3,433.23 6,484.99
1,000,000,000 7,629.39 11,444.09 19,073.49 34,332.28 64,849.85

Ever-increasing
Ever-increasing values allows
new values to be added to
the end of the index structure
without reorganizing rows.
100
200
300

100
200
300
600
Ever-increasing

100
200
300
400
600
Ever-increasing

100
200
300
400
500
600
Ever-increasing

CLUSTERED INDEX
Demo

Pro Tip: Default
to Clustered
Indexes, unless
heaps are proven
to improve
performance

INDEX PATTERNS
Clustered
Index
Index
Patterns
Summary

Heap Patterns
• Staging tables
• Low use data
• Temporary tables
• Heavy scan data

Clustered Index Patterns
Identity
Column
Surrogate
Key
Foreign
Key
Multi-
Column

Identity Column
• Non-related value that defines each row
uniquely
• Assigned when data is inserted
• Typically uses:
– Int or bigint
– IDENTITY or SEQUENCE
– Uniqueidentifier

Identity Column
Static
Narrow
Unique
Ever-increasing

Surrogate Key
• Unique value is a part of the row
• Assigned in the source data
• Data type dependent on the data
• Value should be unchanging
– Employee ID
– Social Security Number
– Birthdate

Surrogate Key
Static
Narrow
Unique
Ever-increasing

Foreign Key
• One-to-many relationships
• Access path in child via parent
• Piggy-backs identity pattern
– Parent left of child identity value
• Common in many applications
– Order header to details
– Hotels to rooms

Foreign Key
Static
Narrow
Unique
Ever-increasing

Multi-Column
• Similar to foreign key pattern
• Many-to-many relationships
• Highly dependent on selectivity
• NOT a collection of dimension keys

Multi-Column
Static
Narrow
Unique
Ever-increasing

INDEX PATTERNS
Demo

SUMMARY
Clustered
Index
Index
Patterns
Summary

These are not
unbreakable rules!

Summary
• Clustered indexes are important
• Select clustering keys based on need
• Validate clustered indexes over time

More Information
Expert Performance Indexing
For SQL Server 2012
Jason Strate
Ted Krueger
Overview
Statistics
Maintenance
Tools
Analysis
http://amzn.com/1430237414

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For more information…
Name: Jason Strate
Email: jstrate@pragmaticworks.com
Blog: www.jasonstrate.com
Resource: jasonstrate.com/go/indexing
Need Help? jasonstrate.com/go/vmdba

Introduction to Clustered Indexes and Heaps

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