Tài liệu Module 9: Processing Dimensions and Cubes pptx

Lab A: Processing Dimensions and Cubes 27 Lab B: Updating Dimension Data 30 Lab C: Incrementally Updating Cubes 36 Troubleshooting Cube Processing 49 Review 54 Module 9: Processing D

Lab A: Processing Dimensions and Cubes 27

Lab B: Updating Dimension Data 30

Lab C: Incrementally Updating Cubes 36

Troubleshooting Cube Processing 49

Review 54

Module 9: Processing Dimensions and Cubes

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Instructor Notes

Multidimensional online analytical processing (OLAP) databases include schema and data, both of which change and need updating from the relational database management system (RDBMS) on a regular basis In this module, students learn to manage dimension and cube processing with Microsoft® SQL Server™ 2000 Analysis Services

After completing this module, students will be able to:

! Understand the difference between OLAP schema and data

! Process dimensions

! Perform the three types of cube processes

! Optimize cube processing

! Troubleshoot cube processing

Materials and Preparation

This section lists the required materials and preparation tasks that you need to teach this module

Required Materials

! To teach this module, you need Microsoft PowerPoint® file2074A_09.ppt

Preparation Tasks

To prepare for this module, you should:

! Read all the student materials

! Read the instructor notes and margin notes

! Complete all the demonstrations

! Practice the lecture presentation and demonstration

! Complete the lab

! Review the Trainer Preparation presentation for this module on the Trainer Materials compact disc

! Review any relevant white papers that are located on the Trainer Materials compact disc

Presentation:

75 Minutes

Lab:

75 Minutes

Demonstration: Rebuilding the State Dimension

The following demonstration procedures provide information that will not fit in the margin notes or is not appropriate for student notes

In this demonstration, you will rebuild the State dimension and will show students the impacts to the Sales Units cube after the rebuild

! To restore a new database and define a data source

1 In Analysis Manager, right-click the server, click Restore Database, click the Look in list, click the file C:\Moc\2074A\Labfiles\L09\Module

09.CAB, click Open, click Restore, and then click Close

2 Double-click Module 09 to expand the database

3 Below Module 09, double-click the Data Sources folder, right-click the

Module 09 data source, and then click Edit

4 Click the Connection tab of the Data Link Properties dialog box, and then verify that localhost is selected in step 1

5 In step 2, verify that Use Windows NT Integrated security is selected

6 In step 3, verify that Module 09 is selected

7 Click Test Connection and verify that the test succeeded Click OK twice

! To browse the Sales Units cube

1 In the Module 09 database, browse the Sales Units cube

2 Show students that the cube contains two dimensions—State and Time— and one measure—Sales Units

3 Point out that the cube is processed and able to accept queries

! To rebuild the State dimension

1 In the Module 09 database Shared Dimensions folder, right-click the State dimension, and then click Process

The Process a Dimension dialog box opens

Here you see two options for processing a dimension—incrementally updating the dimension and rebuilding the dimension

2 Click Rebuild the dimension structure, and then click OK

The Process dialog box opens and steps through the dimension rebuild

3 After the dimension finishes processing, double-click the line in the Process dialog box that begins with a yellow SQL icon

Here you see the SQL that executes to rebuild the State dimension:

SELECT DISTINCT "dbo"."State"."Country",

"dbo"."State"."Region", "dbo"."State"."STATE_ID",

"dbo"."State"."State_Name" FROM "dbo"."State"

4 Close the View Trace Line window, and then click Close

Demonstration:

10 Minutes

! To attempt to browse the Sales Units cube

1 In the Module 09 database, right-click the Sales Units cube, and then click

Browse Data

2 Notice that you receive the following error:

“Unable to browse the cube ‘Sales Units’ Cube not processed To browse sample data for this cube, open Cube Editor, and then on the View menu, click Data.”

You did not change the State source data, and therefore the dimension did not require a rebuild However, if the dimension is rebuilt, the Sales Units

cube is unavailable

After you rebuild a shared dimension, all cubes containing the shared dimension are unavailable for user access

3 Click Close

Other Activities

Difficult Questions

Below are difficult questions that students may ask you during the delivery of this module and answers to the questions These materials delve into subjects that are within the scope of the module but are not specifically addressed in the content of the student notes

1 How are incremental updates useful if the Analysis Server is unaware of data warehouse loads and it therefore does not know what data to load from

a table?

You can create a column in the fact table that has an identifying record, such as a time stamp or a batch number You can include the unique record in the WHERE clause of the associated partition definition and filter records based on that identifier

2 Are multiple partitions of a cube processed sequentially, even if they reside

on different computers?

Yes, unless you specify that you want certain partitions to be built in parallel You can do this by using Decision Support Objects (DSO)

Module Strategy

Use the following strategy to present this module:

! Introducing Dimension and Cube Processing

Define the term processing and explain that Analysis Server creates SQL

statements to extract information from the data source Next, define the

terms schema and data as they are used in Analysis Services

! Processing Dimensions Explain to students that dimensions must be processed when they are first designed and whenever there are changes or updates in the source dimension tables Describe the interface and the steps to follow to process a shared dimension Explain that there are two ways to process a shared dimension—a rebuild or an incremental update Describe when to use each type of processing and the implications of doing so Explain that private dimensions are created and manipulated in single cubes, and that to process

a private dimension, the entire cube must be processed Finally, define relational OLAP (ROLAP) dimensions and changing dimensions and explain when to use them

! Processing Cubes Begin with an explanation of when to process a cube and how to get to the

Process a Cube dialog box Describe the three options available in the

dialog box—full process, refresh, and incremental update Describe when to use each option and the implications of doing so Introduce the Incremental Update Wizard and the steps involved in performing an incremental update—specifying the data source and specifying the filter expression Explain what happens behind the scenes when using a filter Discuss available properties that affect cube and dimension processing

! Optimizing Cube Processing Explain to students that, while query performance is obviously a high priority when using OLAP cubes, processing time is also important

Describe several ways to improve cube processing performance—

optimizing the data source, optimizing the cube schema, optimizing cube design, and optimizing Analysis Server Explain how to perform each of these types of optimization

! Troubleshooting Cube Processing Describe the three most common cube problems related to processing—missing data, processing errors, and insufficient memory and disk space Give tips and techniques for solving each type of problem

Overview

! Introducing Dimension and Cube Processing

! Processing Dimensions

! Processing Cubes

! Optimizing Cube Processing

! Troubleshooting Cube Processing

Multidimensional online analytical processing (OLAP) databases include schema and data, both of which change and need updating from the relational database management system (RDBMS) on a regular basis In this module, you will learn to manage Analysis Server dimension and cube processing with Microsoft® SQL Server™ 2000 Analysis Services

After completing this module, you will be able to:

! Understand the difference between OLAP schema and data

! Process dimensions

! Perform the three types of cube processes

! Optimize cube processing

! Troubleshoot cube processing

In this module, you will learn

about dimension and cube

processing and the various

ways to perform processes

# Introducing Dimension and Cube Processing

! Definition of Processing

! Overview of Schema and Data

In this section, you are introduced to dimension and cube processing, and will learn the difference between OLAP schema and OLAP data

Topic Objective

To introduce the concept of

cube and dimension

processing

Lead-in

In this section, you are

introduced to dimension and

cube processing, and will

learn the difference between

OLAP schema and OLAP

data

Definition of Processing

! Processing Must Occur Prior to Users Querying the Cube

! Dimension Processing Loads Dimension Data

! Cube Processing Loads Cube Data and Creates Aggregations

! Processing Uses SQL Queries to Populate Dimension and Cube Data

Before users can access data from an OLAP cube, some form of processing

must occur in the cube In Analysis Services, the term processing means

loading dimensions and cube data from the RDBMS data source

When you process dimensions and cubes, Analysis Server creates SQL statements to extract the necessary information from the data warehouse dimension and fact tables In addition, Analysis Server creates any aggregations

in the cube that were designed previously

Before users can access

data from a cube, some

form of processing must

occur in the cube

Overview of Schema and Data

! OLAP Schema

! OLAP Data

To master various dimension and data load processes, it is important to

understand the difference between schema and data Definitions of the two

terms as used in Analysis Services may differ from what you are accustomed to when using other databases and technologies

OLAP Schema

Unlike relational databases, where member names are considered data, member

names in Analysis Services are considered part of the schema

The following is true of OLAP schema:

! The schema consists of the dimensional hierarchies and the members that populate these hierarchies

! OLAP schema comes from the dimension tables in the source RDBMS

! Member names, for example Quarter 1, Canada, and Bread, are

commonly referred to as OLAP metadata in multidimensional databases

OLAP Data

The data in Analysis Services is the numeric information, such as units sold,

prices, inventory levels, or dollar revenues

The following is true of OLAP data:

! This numeric information, or data, is commonly referred to as the measures

! OLAP data comes from the fact table in the source RDBMS

Understanding the distinction between schema and data is important for database administrators and OLAP architects

Topic Objective

To describe the differences

between OLAP schema and

OLAP data

Lead-in

It is important to understand

the difference between the

terms schema and data as

they are used in Analysis

Services

# Processing Dimensions

! Dimension Processing Overview

! Rebuilding Dimensions

! Incrementally Updating a Dimension

! Processing Private Dimensions

! Understanding ROLAP and Changing Dimensions

A cube consists of one or more dimensions combined with one or more measures The dimensions form the structure or organization for the data values

in the cube Before the Analysis Server can process a cube, it must have already processed each dimension that is used in the cube

In this section, you will learn about dimension processing and the various ways

In this section, you will learn

about dimension processing

and the various ways of

processing dimensions

Dimension Processing Overview

! Purpose of Dimension Processing

! Shared Dimension Processing Mechanics

! The Process Dialog Box

Before data can be loaded into a cube, you must first create and process the dimensions of the cube Once you process the dimensions, the Analysis Server can load data from the fact table into the cube and can create aggregations

Purpose of Dimension Processing

You process a dimension when you first create it, when you modify its structure, and when data updates occur in the source data dimension tables After the initial dimension process, you must maintain dimensions on an ongoing basis to reflect changes in the underlying dimension tables—for example, new products are added to the product line, sales representatives change sales regions, and so on Dimensions must reflect the changes in the business structure

Two methods are available to the Analysis Server developer for processing shared dimensions:

! Rebuild the dimension structure completely rebuilds and constructs a

on the server for cubes that use the MOLAP, hybrid OLAP (HOLAP), and relational OLAP (ROLAP) storage modes

Before data can be loaded

into a cube, you must first

create and process the

dimensions of the cube

Key Point

Analysis Server creates

multidimensional OLAP

(MOLAP) dimension

structures in the Data folder

located on the server,

except in those cases when

you use ROLAP

dimensions Non-ROLAP

dimensional structures are

created on the server for

cubes that use the MOLAP,

hybrid OLAP (HOLAP), and

relational OLAP (ROLAP)

storage modes

Do not spend too much time

here describing dimension

rebuilds and incremental

updates because they are

discussed in detail later in

this section

Shared Dimension Processing Mechanics

You can initiate the processing of a shared dimension in either of two ways:

! Expand the Shared Dimensions folder, right-click the dimension, and then click Process to display the Process a Dimension dialog box This interface

lets you choose between an incremental update and a dimension structure rebuild

! Right-click the Shared Dimensions folder and click Process All

Dimensions There is no choice about which type of process will occur

when you choose this option The Analysis Server determines the type of process applied to dimensions by determining which dimensions contain structure changes and which dimensions maintain their original structure

The Process Dialog Box

When you process a dimension in Analysis Manager, a Process dialog box

opens that steps through each of the processing phases The dialog contains the following information that you can use to troubleshoot errors or determine the success or failure of the process:

! Start time, end time, and process duration

! Number of RDBMS rows processed

! Initialization and committal information

! SQL statements performed on the RDBMS to access member and dimension data

! Information on the success or failure of the dimension build

Rebuilding Dimensions

! Situations in which to Rebuild a Dimension

! Implications of Rebuilding a Dimension

reprocessed

The Rebuild the dimension structure option in the Process a Dimension

dialog box entirely recreates the dimension structure It is the most comprehensive method for processing dimensions

Situations in which to Rebuild a Dimension

The following situations require a rebuild of the dimension structure to reflect the structural dimension changes:

! Adding or deleting a level

! Deleting a member

! Renaming a member

! Moving a child from one parent to another This movement is commonly

called re-parenting For example, if you move a product from one business

unit to another, the dimensional structure must reflect the change

Implications of Rebuilding a Dimension

Rebuilding a dimension is not a minor action The following are implications of rebuilding a shared dimension:

! The Analysis Server erases and rebuilds the dimensional structure that is stored on the Analysis Server

! Cubes that depend on the given dimension are unavailable to clients until the cubes are reprocessed In other words, clients cannot connect to cubes that depend on a rebuilt dimension until the cubes are reprocessed

! The rebuilding of the dimensional structure can be a time-consuming process if the dimension contains an abundance of members

Topic Objective

To describe the process of

rebuilding a dimension

Lead-in

The Rebuild the

dimension structure option

entirely recreates the

dimension structure It is the

most comprehensive

method for processing

dimensions

Incrementally Updating a Dimension

! Situations in which to Incrementally Update a Dimension

! Implications of Incrementally Updating a Dimension

The other option of the Process a Dimension dialog box is Incremental

update This option allows you to add members and member properties to a

shared dimension when no structural changes have occurred

Incremental updates do not force a reprocessing of the cube Therefore, perform incremental updates of dimensions instead of dimension rebuilds when

possible

Situations in which to Incrementally Update a Dimension

You can perform incremental updates in the following situations:

! Adding a member to a dimension

! Adding a member property to a dimension

Implications of Incrementally Updating a Dimension

Though the implications are not as severe as dimension rebuilds, it is still important to understand what happens when an incremental update occurs:

! Cubes that use the given dimension are available to clients during this process

! The dimension hierarchy reflects the member updates when the incremental update is complete

! Existing members are left intact

! New fact table data associated with the new members requires an

incremental cube update

When you process a cube, you have the option to incrementally update

Topic Objective

To describe dimension

incremental updates

Lead-in

Incremental updates allow

you to add members and

member properties to a

shared dimension when no

structural changes have

occurred

Note

all shared dimensions found in the cube You do this by selecting the

Incrementally update the shared dimensions used in this cube check box

found in the Process a Cube dialog box

Processing Private Dimensions

! Exist in Single Cubes

! Cannot Be Processed Independently

! Are Processed When The Cube Is Processed

You create and manipulate private dimensions in single cubes Because they exist in single cubes, you do not affect other cubes by processing private dimensions Therefore, you can isolate cube-processing needs by defining dimensions as private

You cannot process private dimensions without also processing the cubes in which they reside, and no options or commands exist that process private dimensions independently

There are two methods of processing private dimensions:

! Perform an incremental update or a refresh of a cube An incremental

update or a refresh of a cube performs an incremental update of all private dimensions in the cube In other words, an incremental update or a refresh

of a cube adds new members and member properties in private dimensions

in the cube

! Perform a full process of a cube A full process of a cube performs a rebuild

of all private dimensions in the cube In other words, a full process of a cube updates the structure and all members in private dimensions in the cube

For more information on cube refreshes and full processes, refer to the

next section in this module, Processing Cubes

Topic Objective

To discuss the processing of

private dimensions

Lead-in

In this section, you will learn

about private dimension

processing

Note

Understanding ROLAP and Changing Dimensions

! ROLAP Dimensions

$ Store dimension data in dimension tables

$ Can support tens of millions of members

$ Force you to define their cubes as ROLAP cubes

$ Require SQL Server 2000 Enterprise Edition

$ Are also considered changing dimensions

! Changing Dimensions

$ Are optimized for frequent data source changes

$ Permit more types of changes with incremental updates

$ Include virtual, parent-child, and ROLAP dimensions

$ Are set within the Dimension Editor

When you create a dimension, its structure is stored, by default, in multidimensional structures on the Analysis Server computer You maintain its dimensional structure based on the processing rules presented in the preceding pages of this section These dimensions are considered MOLAP dimensions

Alternatively, you can define dimensions as ROLAP dimensions to allow for millions of members in your dimension, or you can create changing dimensions

to allow for more frequent changes to the dimension structure

ROLAP Dimensions

A ROLAP dimension’s data is stored in the dimension table or tables

Therefore, there is no need to build the multidimensional dimension structures that MOLAP dimensions create on the Analysis Server

By defining a dimension as ROLAP, you can maintain a dimension with tens of millions of members If you attempt to store tens of millions of members in a MOLAP dimension, you receive errors when you process the dimension Because of the query performance degradation you receive when using ROLAP dimensions, you usually define a dimension as ROLAP only if the dimension contains millions of members

When you add a ROLAP dimension to a cube, the cube must use the ROLAP option for its cube storage mode You are not given the option to define the cube as MOLAP or HOLAP in the Storage Design Wizard

ROLAP dimensions require SQL Server 2000 Enterprise Edition

All dimensions that use the ROLAP storage mode are also considered to be

Changing Dimensions

A changing dimension is optimized for frequent changes It allows certain types

of changes to be made by using incremental updates instead of rebuilding the dimension and fully processing the cube Therefore, users can access the cubes without interruption when making these changes

The following types of dimensions are always changing dimensions:

! Virtual dimensions

! Parent-child dimensions

! ROLAP dimensions

You can define any dimension as changing by setting its Changing property to

True in the Properties pane of the Dimension Editor or Cube Editor

In a changing dimension, because aggregations are not stored at intermediate dimension levels, levels and members below the top level and above the bottom level of the dimension can be added, moved, changed, or deleted, and an incremental update applies the changes when you save the dimension You do not need to rebuild the dimension, a process that makes the cube unavailable to clients during the rebuild process

Changing dimensions provide for more flexibility in updating dimension structures However, queries that use changing dimensions are slower than queries that use non-changing dimensions

For more information on ROLAP and changing dimensions, see SQL Server Books Online

Note

Demonstration: Rebuilding the State Dimension

In this demonstration, you will learn how to rebuild the State dimension and will see the impacts to the Sales Units cube after the rebuild

Topic Objective

To demonstrate how to

rebuild a dimension

Lead-in

In this demonstration, you

will learn how to rebuild the

State dimension and will

see the impacts to the Sales

Units cube after the rebuild

Delivery Tips

The steps for this

demonstration are included

in the Instructor Notes

# Processing Cubes

! Cube Processing Overview

! The Full Process

! Refreshing a Cube

! Incrementally Updating a Cube

! The Incremental Update Wizard

! Processing Options

After you design a cube, you must process the cube to populate it with data MOLAP cubes, ROLAP cubes, and HOLAP cubes all require processing There are three different processes for cubes, the mechanics and logic of which are described in the next section

Topic Objective

To introduce cube

processing

Lead-in

After you design a cube, you

must process the cube to

populate it with data

The topics in this section are

very complex If students

are confused, tell them that

the following labs contain

exercises that include each

of the processing types

Cube Processing Overview

! Cube Processing Mechanics

! Using the Process Dialog Box

An OLAP cube is a fast and flexible representation of the information stored in

a data warehouse When the information in the data warehouse changes, you must update the cube so that the data in the cube is accurate Updating an OLAP cube to accurately represent the relational data warehouse is called

processing the cube Different types of changes can occur in the data

warehouse, and the Analysis Server provides different techniques for synchronizing the OLAP cube with the relational data warehouse

Cube Processing Mechanics

To initiate cube processing, right-click a cube and then click Process to display the Process a Cube dialog box Here, you decide if you want to perform an

incremental update, a data refresh, or a full process

Using the Process Dialog Box

When you process a cube in Analysis Manager, the process dialog box opens with processing information This is the same dialog you saw earlier when processing dimensions However, there are more steps documented These include:

! Start time, end time, and duration of entire process, as well as the times and duration of each of the steps of the process

! Number of RDBMS rows processed at each step

! Initialization and committal information

! SQL statements used to access data from the RDBMS

! Statistics on aggregations created

! Information on the success or failure of the process

Topic Objective

To introduce the mechanics

of cube processing

Lead-in

To contain accurate data, a

cube must be processed

when the data in the data

warehouse changes

The Full Process

! Situations in which to Perform a Full Process

$ The cube is new

$ A dimension is added or deleted

$ A dimension is rebuilt

$ A measure is added, deleted, or modified

! Implications of Performing a Full Process

$ Cube data, including aggregations, is erased and rebuilt

$ Dependent virtual cubes become unavailable until reprocessed

$ Partition data is read into the cube from the data source

$ Private dimensions and changed shared dimensions are rebuilt

A full process is the most comprehensive cube process you can perform To

initiate a process, click the third option in the Process a Cube dialog box All

cube structures and cube data is rebuilt

Situations to Perform a Full Process

Because a full process is the most time consuming method of processing, it is important to understand the situations that require a full process These include:

! Creating a new cube

! Adding or deleting dimensions

! Rebuilding any shared dimension belonging to the cube

! Adding, deleting, or modifying cube measures

Implications of Performing a Full Process

The following are important implications of performing a full process on a cube:

! If the cube is MOLAP, it is erased and rebuilt

! Regardless of cube storage—MOLAP, ROLAP, or HOLAP—aggregations are erased and rebuilt

! Any virtual cubes based on the cube are unavailable after the process until they are reprocessed themselves

! All partition data is read into the cube from the RDBMS data sources

! All private dimensions are rebuilt

Topic Objective

To describe when to

perform a full process and

the implications of doing so

! If a shared dimension belonging to the cube has been modified structurally and needs to be rebuilt, the dimension will automatically rebuild when the cube is processed All other cubes that use the same shared dimension will not be available again until they have each been reprocessed

! If an error occurs, the operation is rolled back

Refreshing a Cube

! Situations in which to Refresh a Cube

! Implications of Refreshing a Cube

Refreshing a cube erases all data and repopulates the cube by reading the data from the RDBMS data source The cube structure does not change when you perform a cube refresh

Situations in which to Refresh a Cube

A cube can be refreshed in the following situations:

! The source data of a cube has changed in the RDBMS but the structure of the cube is the same

! An incorrectly performed incremental update causes cube data to be duplicated

Implications of Refreshing a Cube

Although a cube refresh is not as major a procedure as a full process, it is still important to understand the implications of refreshing a cube:

! If the cube is MOLAP, the detailed data is erased and the cube is repopulated from the source RDBMS

! All aggregations are cleared and recalculated

! Shared dimension structures are unchanged, and private dimensions are incrementally updated

! The original cube is available to clients during the refresh Once the refresh

is complete, clients see the new data

! Virtual cubes based on the cube are available to clients during the refresh

! If an error occurs, the operation is rolled back

Topic Objective

To describe when to refresh

a cube and the implications

of doing so

Lead-in

Refreshing a cube erases all

data and repopulates the

cube by reading the data

from the RDBMS data

source

Tell students that duplication

of data due to an incorrectly

performed incremental

update will be discussed in

the next section

Incrementally Updating a Cube

! Situations in Which to Perform an Incremental Update

fact table

from a different fact table

not changed

changed

! Implications of Incrementally Updating a Cube

MOLAP cubes

ROLAP and HOLAP cubes

used

An incremental update is the process by which you add new data to a cube on a periodic basis It is the least time-consuming method of processing a cube because it retains the existing data in the cube and adds only the data you select However, you must understand the mechanics of cube incremental updates to avoid incorrectly duplicating data

Situations in Which to Perform an Incremental Update

Incremental updates can occur if the following are true:

! New data is added to the fact table

! New data is needed temporarily from a different fact table

To include data from a different fact table permanently, create a new

partition in the cube For information on partitions, see module 10,

“Managing Partitions,” in course 2074A, Designing and Implementing

OLAP Solutions with Microsoft SQL Server 2000

! The underlying source data has not changed

! There are no structural changes made to cubes, partitions, or dimensions

Topic Objective

To describe when to

incrementally update a cube

and the implications of doing

so

Lead-in

An incremental update is the

process by which you add

new data to your cube on a

periodic basis

Key Point

The Incremental Update

Wizard cannot determine

new fact table data

Therefore, you must define

what is new in the data

source If you incorrectly

define new data, you risk

creating incorrect values in

the cube

Note

Implications of Incrementally Updating a Cube

An incremental update produces the following results:

! For MOLAP cubes, new detailed data is imported into the cube—old data is unaffected

! For ROLAP and HOLAP cubes, since detailed data is already stored in the source RDBMS, there is no movement of detailed data

! For all storage options—MOLAP, ROLAP, and HOLAP—aggregations are updated

! Private dimensions included in the cube are incrementally updated

! Clients can work with the cube and dependent virtual cubes while the incremental update is in process Once completed, clients see new data

! If an error occurs, the operation is rolled back

! You can define a different fact table in the Incremental Update Wizard By defining a different fact table, you add the data in the new fact table to the existing cube data

! Filters can be defined in the Incremental Update Wizard to further specify the data to be loaded into your cube Filters are SQL statements that are passed to your RDBMS

The Incremental Update Wizard does not have a method for determining new fact table data Therefore, you must define what is new in the data source By incorrectly defining new data, you risk creating incorrect values

in your cube

Important

The Incremental Update Wizard

! Specifying the Data Source

! Specifying the Filter Expression

! Understanding Filters

By clicking Incremental update as your processing method, the Incremental

Update Wizard appears

This wizard allows you to specify exactly where the new data is coming from

In cubes containing multiple partitions, you define which partition is to be updated

You can also define a filter to specify exactly what data from a fact table will be loaded into your cube

Incremental updates to cubes are made simple in Analysis Services with the Incremental Update Wizard The wizard takes you through the setup of an incremental update This section describes each of the steps

Specifying the Data Source

The first step when performing an incremental cube update is to specify where the new data comes from:

1 Click Change to display the Choose a Fact Table dialog

The available data sources are listed in the left pane Only the data sources that have been defined previously in the current Analysis Server database are listed

2 Expand the data source to display the tables and then choose the fact table containing the incremental data

The columns belonging to the selected table are displayed in the right pane This is for information purposes only

Topic Objective

To introduce the

Incremental Update Wizard

Lead-in

The Incremental Update

Wizard allows you to specify

exactly where the new data

is coming from

Delivery Tip

Open the Incremental

Update Wizard by

right-clicking a cube and right-clicking

Process Click Incremental

Update and then click Next

Step through the wizard to

describe the required

components of an

incremental update, but do

not click Finish at the end of

the wizard

Specifying the Filter Expression

Having chosen a database and fact table, the next step is to specify the filter expression in the form of an SQL WHERE expression This is done without explicitly including the keyword WHERE

The filter expression determines which rows from the fact table will be imported into the cube

Here is the basic syntax of the filter expression:

Understanding Filters

This is what happens behind the scenes when you use a filter:

! The expression you enter becomes part of a WHERE clause

! The WHERE clause in turn is part of an SQL SELECT statement

! The SQL statement passes through to the particular relational database without a syntax check by Analysis Server

Processing Options

! Source Table Filter

! Processing Optimization Mode

! Stop Processing on Key Errors

! Key Error Limit

! Key Error Log File

! Processing Log File

You have access to several properties that affect cube and dimension processing In addition, you can enable log files that store processing information and errors You set the properties and log files in Analysis Manager

Source Table Filter

In the Cube and Dimension Editors, you can set the Source Table Filter property for cubes and dimensions The Source Table Filter property contains

an expression included in the WHERE clause of the SQL query that filters the data loaded into the cube or dimension The expression that you add is an expression used in the WHERE clause, without explicitly including the command WHERE

For example, to include only the Canada member and its descendants in a dimension, type the following in the dimension’s Source Table Filter:

“store”.”store_country” = ‘Canada’

You set the Source Table Filter in the Advanced tab of the Properties pane in the Cube Editor or the Dimension Editor In the Cube Editor, the Source Table

Filter limits fact table records included in the cube In the Dimension Editor,

the Source Table Filter limits members included in the dimension

The Source Table Filter box does not check the syntax of the expression

Always verify that the syntax you enter to define the filter is correct

so that you do not produce duplicated data

Topic Objective

To describe available cube

and dimension processing

properties

Lead-in

You have access to several

properties that affect cube

and dimension processing

Delivery Tip

Switch to Analysis Manager,

and show students how to

access each property as

you describe it

Caution