Module 3

Designing a Physical Database Model

Module Overview

• Selecting Data Types

• Designing Database Tables

• Designing Data Integrity

Lesson 1: Selecting Data Types

• Considerations for Selecting Standard Column Data Types

• Considerations for Selecting New SQL Server 2008 Data Types

• Considerations for Using CLR User-Defined Data Types

• Considerations for Using Spatial Data Types

• Guidelines for Using the XML Data Type

• Establishing Naming Standards for Database Objects

• Discussion: Working with Data Tables

Considerations for Selecting Standard Column Data Types

Integer versus GUID primary keysü

Fixed versus variable length columnsü

VARCHAR (MAX), NVARCHAR (MAX), and VARBINARY (MAX) data typesü

Character column collations and Unicode and non-Unicode data typesü

Transact-SQL user-defined data typesü

Considerations for Selecting New SQL Server 2008Data Types

• Same date precision as date• Same time precision as time • DateTimeOffset is time zone aware

Datetime2 / Datetimeoffset

• When a table contains a FILESTREAM column

• When objects are larger than 1 MB• Where fast read access is important• Where you use a middle tier

FILESTREAM

• Date: From 01/01/0001 to 12/31/9999• Date: No time component• Time: Based on 24 hour clock, NO date

component• Time: Accurate to 100 ns

Date / Time

• To create tables with a hierarchical structure

• To query and perform work with hierarchical data by using T-SQL

Hierarchyid

Considerations for Using CLR User-Defined Data Types

Use common language runtime (CLR) user-defined data types for nonstandard or proprietary data types

Avoid excessively complex data types

Consider the risks of tightly coupling a CLR user-defined data types and the database

Consider the overhead of row-by-row processing

Considerations for Using Spatial Data Types

Spatial Data:

• Represents information on the location and shape of geometric objects

• Can be of two types including geometry and geography data types

• Implemented as .NET common language runtime data types in SQL Server

• Supports eleven spatial data objects, or instance types

Spatial Data

Geometry Data Type

Geography Data Type

Guidelines for Using the XML Data Type

Use the XML data type for data that is not frequently updatedü

Use typed XML columnsü

Use the XML data type for data that is not relationally structuredü

Use the XML data type for configuration informationü

Use the XML data type for data with recursive structuresü< xml >

Establishing Naming Standards for Database Objects

Use only standard abbreviations in namesü

Use names that comply with the rules for forming SQL Server 2008 identifiersüUse descriptive termsü

Use models for naming standardsü

Be consistent across all objectsüRecord and communicate naming standardsüUse prefixes ONLY when it provides valueüUse policy-based managementü

Name intersection tables consistentlyü

Discussion: Working with Data Tables

Scenario:

Some developers argue to use a simple table structure containing only four columns—a unique row identifier, a field identifier (analogous to a column name), a datatype indicator, and the data itself stored as a sqlvariant.

Some say that the application could reconstitute all data fields, and pivot them into a virtual table.

The argument often goes further to whether developers should be involved in working with the database schema, since they can create new data properties (fields) as needed.

Question:

What is the fallacy in these arguments?

• Guidelines for Determining Table Width

• What Are Sparse Columns?

• Demonstration: How To Create a Table By Using Sparse Columns

• Guidelines for Using Computed Columns

• Discussion: Using Computed Columns

Lesson 2: Designing Database Tables

Guidelines for Determining Table Width

Large Object Types Data Overflow

Capacity Planning

Properties of Sparse Columns

What Are Sparse Columns?

• The SQL Server Database Engine uses the SPARSE keyword in a column definition to optimize the storage of values in that column.

• Catalog views for a table that has sparse columns are the same as for a typical table.

• The COLUMNS_UPDATED function returns a varbinary value to indicate all the columns that were updated during a DML action.

Sparse columns are ordinary columns that have an optimized storage for NULL values. They can be used with column sets and filtered index.

Data types that you cannot specify as sparse are geography, geometry, image, ntext, text, timestamp, and user-defined data types.

Demonstration: How To Create a Table By UsingSparse Columns

In this demonstration, you will see how to:

Create a table by using sparse columns

• Avoid the overhead of complex functions in computed columns • Avoid persisted computed columns on active data• Protect against numeric overflow and divide by zero errors

Use persisted computed columns for performance

Guidelines for Using Computed Columns

Use computed columns to derive results from other columns

Usage of Computed Columns

Exceptions in Column Data

Usage of Persisted Computed Columns

Usage of Persisted Computed Columns

Usage of Computed Columns

Exceptions in Column Data

Computed Columns

Discussion: Using Computed Columns

• What kind of problems do computed columns solve?

• When is a computed column actually computed?

Lesson 3: Designing Data Integrity

• Guidelines for Designing Column Constraints

• Guidelines for Designing Table Constraints

• Guidelines When Implementing DDL Triggers

• Discussion: Identifying the Best Options for Column Data Types and Data Constraints

Guidelines for Designing Column Constraints

Use column CHECK Constraints

CONSTRAINT chkQty CHECK (Amount > 0)...)

Declare columns as NOT NULL

(HireDate int NOT NULL...)

Use ANSI default constraints

(CONSTRAINT Qty DEFAULT 0...)

Use CHECK constraints instead of bound rules

Check Constraint

Bound Rules

Guidelines for Designing Table Constraints

Use DRI for data integrity in a database

Use triggers to enforce referential integrity

Use ANSI-standard options

Use table-level CHECK constraints Check Constraint

ON DELETE

Specify cascading levels and options

Guidelines for Designing Database Constraints byUsing DDL Triggers

Use DDL triggers for auditing

Use DDL triggers to prevent database changes

Use DDL triggers to support security

Guidelines When Implementing DDL Triggers

Use DDL triggers with transactionsü

Use DDL triggers scope to control database operations or objects that activates the triggerü

Avoid creating DDL Trigger on both CREATE_SCHEMA and CREATE_TABLE eventü

Use value() instead of query() when querying data returned from EVENTDATAü

Discussion: Identifying the Best Options for Column Data Types and Data Constraints

Scenario:QuantamCorp is a local company conducting business only in USA and Canada. You need to create a single table to contain the following information.1.Time of the day for a 24 hour clock2.Company name3.E-mail address4.Postal code5.Product information 6.Product descriptive brochure7.Telephone number

Question:What are the best options for column data types and data constraints?

Lab 3: Designing a Physical Database Model

• Exercise 1: Specifying Database Object Naming Standards

• Exercise 2: Converting a Logical Database Model into a Physical Database Model

Estimated time: 40 minutes

Logon Information

Virtual machine

User name

Password

NYC-SQL1

Administrator

Pa$$w0rd

Lab Scenario

The main goals of the HR VASE project are as follows:

• Provide managers with current and historical information about employee vacation and sick-leave data.

• Provide permission to individual employees to view their vacation and sick-leave balances.

• Provide permission to selected employees in the HR department to view and update employee vacation and sick-leave data.

• Provide permission to the HR manager to view and update all the data.

• Standardize employee job titles.

• In this lab, you will build a physical database model based on the logical model created earlier.

You are a lead database designer at QuantamCorp. You are working on the Human Resources Vacation and Sick Leave Enhancement (HR VASE) project that is designed to enhance the current HR system of your organization. This system is based on the QuantamCorp2008 sample database in SQL Server 2008.

Lab Review

• Can you explain the purpose of creating naming standards and having a Naming Standards policy?

• What kind of issues may arise if a Naming Standards policy does not exist?

Module Review and Takeaways

• Review Questions

• Real-world Issues and Scenarios