Introduction to the Analysis Services 2005 Query Log

Monday Jul 10th 2006 by William Pearson

Business Intelligence Architect Bill Pearson leads a hands-on examination of the Analysis Services 2005 Query Log. In addition, we discuss customization of the Query Log and its use as a direct reporting source.

About the Series ...

This article is a member of the series Introduction to MSSQL Server Analysis Services. The series is designed to provide hands-on application of the fundamentals of MS SQL Server Analysis Services, with each installment progressively presenting features and techniques designed to meet specific real - world needs. For more information on the series, please see my initial article, Creating Our First Cube.

Note: To follow along with the steps we undertake, the following components, samples and tools are recommended, and should be installed according to the respective documentation that accompanies MSSQL Server 2005:

  • Microsoft SQL Server 2005 Database Engine

  • Microsoft SQL Server 2005 Analysis Services

  • Business Intelligence Development Studio

  • Microsoft SQL Server 2005 sample databases

  • The Analysis Services Tutorial sample project and other samples that are available with the installation of the above.

To successfully replicate the steps of the article, you also need to have:

  • Membership within one of the following:

    • the Administrators local group on the Analysis Services computer

    • the Server role in the instance of Analysis Services.

  • Read permissions within any SQL Server 2005 sample databases we access within our practice session, if appropriate.

Note: Current Service Pack updates are assumed for the operating system, MSSQL Server 2005 ("MSSQL Server"), MSSQL Server 2005 Analysis Services ("Analysis Services"), MSSQL Server 2005 Reporting Services ("Reporting Services") and the related Books Online and Samples. Images are from a Windows 2003 Server environment, but the steps performed in the articles, together with the views that result, will be quite similar within any environment that supports MSSQL Server 2005 and its component applications.


In my article, Usage-Based Optimization in Analysis Services 2005, we introduced and explored Usage-Based Optimization, gaining some hands-on exposure to the Usage-Based Optimization Wizard. We noted that the new Usage-Based Optimization Wizard improves dramatically upon the effectiveness of the Analysis Services 2000 Usage Analysis (going significantly farther than the generation of the simple reports) and Storage Design (allowing for up-to-date, usage-based optimization) Wizards. We focused upon the way that the Usage-Based Optimization Wizard offers us the capability to base aggregation design upon a given cube's usage statistics, in combination with other factors, and allows us to make subsequent adjustments to our existing aggregation design and storage mode as time passes, and as information is collected from which meaningful statistics can be derived.

We examined the operation of the Usage-Based Optimization Wizard within a context of aggregation design, and then reinforced our understanding with a practice exercise within which we enabled the Analysis Server Query Log to capture query statistics within a copy of a sample Analysis Services database we created for the exercise. After next processing the clone database, we manipulated data within a cube therein to create Query log entries. The focus of the exercise then became performance of a procedure whereby we set aggregations for our designated practice cube with the Usage-Based Optimization Wizard. Throughout the guided steps of the Wizard we examined each of the possible settings that it makes available to us, and commented upon general optimization concepts as we proceeded through the practice example.

In this article, we will examine more closely the Query Log itself. I often receive requests from clients and readers, asking how they can approach the creation of more sophisticated reporting to assist in their usage analysis pursuits. This is sometimes based upon a need to create a report that presents data as it appears in, say, the Query Log table / file, in a way that allows for printing, publishing to the web, or otherwise delivering report results to information consumers. Moreover, some users simply want to be able to design different reports that they can tailor themselves, to meet specific needs. Yet others want a combination of these capabilities.

Each of these more sophisticated analysis and reporting needs can be met in numerous ways. In this lesson, we will we will examine the source of cube performance statistics, the Query Log, discussing its location and physical structure, how it is populated, and other characteristics. We will discuss ways that we can customize the degree and magnitude of statistical capture in the Query Log to enhance its value with regard to meeting more precisely our local analysis and reporting needs. We will practice the process of making the necessary changes in settings to illustrate how this is done. Finally, we will discuss options for generating more in-depth, custom reports than the wizard provides, considering ways that we can directly obtain detailed information surrounding cube processing events in a manner that allows more sophisticated selection, filtering and display, as well as more customized reporting of these important metrics.

The Analysis Services 2005 Query Log

Overview and Discussion

The entire idea behind "optimization based upon utilization" is, first and foremost, to enhance performance based upon what consumers ask for on a recurring basis. Beginning with capabilities that debuted in Analysis Services 2000, we have been able to leverage historical query details to ascertain the aggregations of data that our cubes need to maintain to support the most frequently "asked" queries. We could apply filters to refine this exploration, and extrapolate what we learn to the specification of which aggregations to maintain, thus maintaining the appropriate pre-calculations for the consumer populations we support, as we detailed in Usage-Based Optimization in Analysis Services 2005.

We have multiple options, when we venture upon utilization analysis and utilization-based optimization within Analysis Services 2005, in how we incorporate the Query Log. Examples include the use of the Usage-Based Optimization Wizard, as we saw in Usage-Based Optimization in Analysis Services 2005, to create usage-based aggregations in a directed manner, so as to fine tune the storage / processing tradeoffs involved. Alternatively, we might create reports, using Reporting Services or other relational report writers, to analyze usage – or even usage trends – to prompt forehanded action with regard to aggregation design, as well as general cube sizing and structure. As illustrations, I have created dashboard objects for various clients that keep administrators informed of what multidimensional intersects are being queried most often, as well as what the processing times for those queries are (to identify "candidate intersects" for more well-tuned aggregations); intersects that are rarely accessed (candidates, perhaps for removal, or less intensive aggregations); the overall cube size; and trends regarding these and other values to highlight the need for storage and optimization planning at future dates. Important to any optimization effort is the ongoing requirement to revisit the process to capture changes that occur over time in usage patterns – the more history we have of actual usage, the more value we can add with usage-based optimization.

Regardless of the ways we employ the data within the Query Log, we must populate the log first. We will perform the steps to do so once again in this session, as preparation to browsing the log, as well as discussing various reporting and "fine tuning" options, in general. In this article, we will:

  • Create of a copy of a sample Analysis Services database for use in our practice exercise;

  • Enable the Analysis Server Query Log to capture query statistics;

  • Process the cube and manipulate data, to create Query Log entries;

  • Examine the Query Log contents, discussing the various statistics captured;

  • Discuss reporting options, including the use of SQL Server Reporting Services as relational and / or OLAP reporting tool;

  • Comment upon customization concepts as we proceed through our practice example.

Considerations and Comments

For purposes of the practice exercises within this series, we will be working with samples that are provided with MSSQL Server 2005 Analysis Services. These samples include, predominantly, the Adventure Works DW Analysis Services database (with member objects). The Adventure Works DW database and companion samples are not installed by default in MSSQL Server 2005. The samples can be installed during Setup, or at any time after MSSQL Server has been installed. The topics "Running Setup to Install AdventureWorks Sample Databases and Samples" in SQL Server Setup Help or "Installing AdventureWorks Sample Databases and Samples" in the Books Online (both of which are included on the installation CD(s), and are available from and other sources), provide guidance on samples installation.

Important information regarding the rights / privileges required to accomplish samples installation, as well as to access the samples once installed, is included in the references I have noted.

Hands-On Procedure

Let's get some hands-on exposure to the Analysis Services Query Log. To prepare, we will create a new Analysis Services database, based upon the existing Adventure Works DW sample database, to insulate the original sample database from modifications we will make. We will accomplish the creation of the "clone" database from within the SQL Server Management Studio, and then enable query logging to prepare for our exploration of the Query Log.


Create a Clone Analysis Services Database in SQL Server Management Studio

We will begin our preparation within SQL Server Management Studio, where we will create a clone of the sample Adventure Works DW database. Adventure Works DW can be installed by anyone installing MSSQL Server 2005 Analysis Services.

1.  Click the Start button.

2.  Select Microsoft SQL Server 2005 within the Program group of the menu.

3.  Click SQL Server Management Studio, as shown in Illustration 1.

Illustration 1: Opening SQL Server Management Studio

The Connect to Server dialog appears.

4.  Select Analysis Services in the Server type selector.

5.  Type / select the server name / instance, if appropriate) into the Server name selector.

6.  Supply authentication information, as required in your own environment.

The Connect to Server dialog appears, with the appropriate input for our local environments, similar to that depicted in Illustration 2.

Illustration 2: The Connect to Server Dialog, with Representative Settings

7.  Click the Connect button to connect with the specified Analysis Services server.

The SQL Server Management Studio opens.

8.  Within the Object Explorer (the leftmost pane of the Studio, by default), expand the server in which we are working, if necessary, by clicking the "+" sign to its immediate left.

9.  Expand the Databases folder that appears underneath the expanded server.

10.  Right-click the Adventure Works DW database.

11.  Select Back Up... from the context menu that appears, as shown in Illustration 3.

Illustration 3: Right-click the Adventure Works DW Database – Select Back Up ...

The Backup Database – Adventure Works DW dialog appears.

12.  Replace the default name that appears in the Backup file box with the following:

ANSYS049 Adventure Works DW.abf

13.  Uncheck the Apply compression setting in the Options section.

14.  Uncheck the Encrypt backup file setting that immediately follows.

The relevant portion of the Backup Database – Adventure Works DW dialog appears, as depicted in Illustration 4.

Illustration 4: The Backup Database – Adventure Works DW Dialog (Relevant Portion)

15.  Click OK to begin the backup.

The Backup Database – Adventure Works DW dialog grays, as the Executing symbol in the Progress pane (lower left corner of the dialog) becomes active. The process may run several minutes depending upon the resources available on the local system. Once completed, the dialog closes, returning us to the Management Studio.

We will next restore the same backup, to create a differently named copy of the existing sample database – a copy wherein we can make modifications without impairing the existing sample, which we may wish to use to complete tutorials included with MSSQL Server 2005 or elsewhere.

16.  Within the Object Explorer, right-click the Databases folder underneath the Adventure Works DW database.

17.  Select Restore... from the context menu that appears, as shown in Illustration 5.

Illustration 5: Right-click the Databases Folder – Select Restore ...

The Restore Database dialog appears.

18.  Click the Browse button to the right of the box (second from the top) labeled From backup file.

The Locate Database Files dialog appears.

19.  Navigate to the following backup file (where we located it in our backup steps above):

ANSYS049 Adventure Works DW.abf

20.  Click the file within the Select the file window, to place the file name into the File name box, as depicted in Illustration 6.

Illustration 6: Locate Database Files Dialog with Our Input ...

21.  Click OK to accept the file path / name, and to close the Locate Database Files dialog.

We return to the Restore Database dialog, where we see the file we have selected appear in the From backup file box.

22.  Type the following into the Restore database box immediately above the From backup file box:

ANSYS049 Adventure Works DW

The relevant portion of the Restore Database dialog, with our input, appears as shown in Illustration 7.

Illustration 7: The Completed Restore Database Dialog (Partial View)

23.  Click OK to initiate the restoration.

The Restore Database dialog grays, as the Executing symbol in the Progress pane, once again, becomes active. The process runs, and, once completed, the dialog closes, returning us to the Management Studio. Here we see the new ANSYS049 Adventure Works DW database appear in the Object Browser, as depicted in Illustration 8.

Illustration 8: The New Database Appears ...

NOTE: If the new database does not appear immediately, right-click the Databases folder and select Refresh from the context menu that appears, as shown in Illustration 9.

Illustration 9: Refreshing as Required ...

Having created the ANSYS049 Adventure Works DW database, we can now transition to the procedural portion of our session, and get some hands-on exposure to the Query Log in Analysis Services 2005. In the next section, we will take an additional preparatory step: enabling the logging of query statistics.


Enable Query Logging to Gather Statistics

Usage-based optimization is based upon usage. We therefore must capture usage statistics to have a basis for optimization. We do this by enabling query logging within the Analysis Server, as we shall see in the steps that follow.

1.  Right-click the Analysis Server with which we are working.

2.  Select Properties from the context menu that appears, as depicted in Illustration 10.

Illustration 10: Select Properties from the Context Menu ...

The Analysis Services Properties dialog appears. As we have noted in other articles, this is a busy place, indeed: many settings of a default and operational nature are maintained here. (My advice is to learn all that we can about each entry within this table-like dialog, so as to know of its existence when the time comes to address the utility that it offers). Here we will enable the logging of query statistics.

3.  Scroll down to the Log \ QueryLog \ CreateQueryLogTable entry in the table within the dialog.

4.  Change the Value setting for the entry, which is defaulted to false, to true, via the selector provided, as shown in Illustration 11.

Illustration 11: Changing the CreateQueryLogTable Setting Value to True ...

We next need to direct Analysis Services as to where we wish to house the Query Log. Analysis Services 2005 offers us a great deal of flexibility (and improves upon Analysis Services 2000's provision of an MS Access database for this purpose, which could be migrated to MSSQL Server). We will direct that the Query Log database be created within the sample AdventureWorksDW relational database, which underlies our new clone Analysis Services database, ANSYS049 Adventure Works DW. This is a convenient place to put the Query Log for this session, but we are free to put it into any OLE-DB / .NET compatible data source.

5.  In the Log \ QueryLog \ QueryLogConnectionString row, immediately below the CreateQueryLogTable row (where we assigned the value of true above), click the Value box, and then click the box that appears to its immediate right (marked "..."), as shown in Illustration 12.

Illustration 12: Beginning Connection Setup for the Query Log Data Source

Connection Manager appears.

6.  Leave the Provider setting at its default of Native OLE DB \ SQL Native Client.

7.  Select / type the appropriate Server or Server / Instance combination into the Server name box.

(Mine is MOTHER1\MSSQL2K5, as we see in illustrations throughout recent articles of the series. )

NOTE: If we are working in an environment wherein a side-by-side installation of MSSQL Server 2000 and MSSQL Server 2005 has been performed, the Server Name / Instance will be required ("Localhost" / the Server name alone will not be assigned to the MSSQL Server 2005 instance, by default).

8.  In the Log on to the server section of the Connection Manager dialog, make the authentication selections appropriate to your environment.

I am using Windows Authentication, and therefore select the respective radio button.

9.  In the Connect to a database section in the lower half of the dialog, in the selector box labeled Select or enter a database name, select the AdventureWorksDW relational database.

The Connection Manager dialog appears, with our input, similar to that depicted in Illustration 13.

Illustration 13: Connection Manager Dialog, with our Input

10.  Click the Test Connection button to ascertain connectivity to the database.

Assuming correct settings, confirmation of connectivity appears in a message box, as shown in Illustration 14.

Illustration 14: "Test Connection Succeeded"

11.  Click OK to close the message box.

12.  Click OK to accept settings and to close the Connection Manager dialog.

We are returned to the Analysis Services Properties dialog, where we see that the Value box of the Log \ QueryLog \ QueryLogConnectionString row now contains a connection string, courtesy of the Connection Manager. We have enabled the collection of query statistics and established the location of their collection. Next, we will make a couple of additional adjustments before examining and then populating the Query Log table.

13.  In the Log \ QueryLog \ QueryLogSampling row, which appears three rows below the Log \ QueryLog \ QueryLogConnectionString row, change the Value from the default of 10 to 1.

Here we are merely increasing the sampling rate from the default of "capture statistics from every tenth query" to "capture statistics for each query," a step similar to those we took in previous articles with the Usage-based Optimization Wizard as it existed in Analysis Services 2000. (Although the setting was managed a bit differently, in the Write to log once per [number] box within Analysis Services 2000, our intent then, as it is now, was to simply allow the log to capture enough data to make the procedural steps of our practice exercise meaningful.)

14.  In the Log \ QueryLog \ QueryLogTableName row, which appears in the row immediately below the Log \ QueryLog \ QueryLogSampling row, modify the Value from its default of OLAPQueryLog to the following:


It might be useful to note, too, that we could have specified a file rather than a table for the intended destination for usage statistics collection. If we chose a file versus a table, we can specify the location of the file in the Log \ QueryLog \ QueryLogFileName row, which appears in the row immediately below the Log \ QueryLog \ QueryLogConnectionString row.

Our settings, within the relevant portions of the rows of the Analysis Services Properties dialog we have visited, appear as depicted in Illustration 15.

Illustration 15: Modified Settings within the Analysis Services Properties Dialog (Partial View)

15.  Click OK to enact the settings we have made above.

The "Executing" indicator appears in the bottom left corner of the dialog momentarily, and then the Analysis Services Properties dialog closes. We are returned to the SQL Server Management Studio.

We can confirm the creation of the new MSASQueryLog table within the AdventureWorksDW relational database easily from the SQL Server Management Studio, where we can access the relational world in combination with the OLAP world, as we shall see in the next steps.

16.  Click the Connect button atop the Object Explorer.

17.  Select Database Engine from the menu that appears, shown circled in Illustration 16.

Illustration 16: Connecting to the SQL Server 2005 Database Engine

The Connect to Server dialog appears, just as we saw earlier when connecting to Analysis Services.

18.  Enter the correct Server or Server / Instance combination into the Server name box.

19.  Select the appropriate authentication mode into the Authentication box that immediately follows (with related details in the Password box, as appropriate).

The Connect to Server dialog appears similar to that depicted in Illustration 17.

Illustration 17: The Connect to Server Dialog Appears

20.  Click Connect.

We return to the SQL Server Management Studio, where we see the instance of the Database Engine appear within the Object Explorer, underneath the Analysis Server with which we have been working, as shown in Illustration 18.

Illustration 18: The Database Engine Instance Appears within Object Explorer

21.  Expand the Database Engine Server by clicking the "+" sign to its immediate left, if required.

22.  Expand the Databases folder underneath the expanded server.

23.  Expand the AdventureWorksDW database.

24.  Expand the Tables folder within the AdventureWorksDW database.

The tables within the folder appear. Among them, we see the new ANSYS049_MSASQueryLog table that we created in our earlier steps, as depicted in Illustration 19.

Illustration 19: The MSASQueryLog Table Appears in the AdventureWorksDW Database

The table is in place and query logging is enabled. We are now positioned to generate some sample queries, and to begin our examination of the Query Log.

Process the Database Clone and Generate Statistics to be Captured by the Query Log

We need some log entries upon which to base an examination of the Query Log, so we will populate the table with some rows in a "quick and dirty" manner – by doing quick manipulations of the data in the cube. First, we will process the new Analysis Services database copy we have created.

1.  Within Object Explorer, once again, right-click the new Analysis Services database, ANSYS049 Adventure Works DW, which we created earlier. (The database can be found within the Databases folder of the Analysis Server instance.)

2.  Select Process from the context menu that appears, as shown in Illustration 20.

Illustration 20: Processing the Clone Analysis Services Database ...

The Process Database dialog appears for Analysis Services database ANSYS049 Adventure Works DW, as depicted in Illustration 21.

Illustration 21: The Process Database Dialog Appears

3.  Leaving all settings on the dialog at default, click OK to begin processing.

The Process Progress viewer appears, logging the events of database processing as they occur. Once all database objects are processed, we receive a Process Succeeded message in the Status bar at the bottom of the viewer, as shown in Illustration 22.

Illustration 22: Successful Processing Completion is Indicated ...

4.  Click the Close button to dismiss the Process Progress viewer.

We are returned to the SQL Server Management Studio, where next we will perform a few actions to generate statistics in the Query Log table.

5.  Expand the Analysis Services database ANSYS049 Adventure Works DW, as necessary, by clicking the "+" sign to its immediate left within Object Explorer.

6.  Expand the Cubes folder that appears within the ANSYS049 Adventure Works DW tree.

7.  Right-click the Adventure Works cube that appears within the Cubes folder.

8.  Select Browse from the context menu that appears, as depicted in Illustration 23.

Illustration 23: Select Browse from the Context Menu ...

The Adventure Works [Browse] tab appears within SQL Server Management Studio. Here we will do a few browses to generate sample query statistics within the Query Log.

9.  Expand Measures within the Metadata pane by clicking the "+" sign to its immediate left.

10.  Expand the Internet Sales measure folder that appears underneath the expanded Measures level.

The measures related to Internet Sales appear.

11.  Drag measure Internet Sales Amount into the Data pane, dropping it into the area marked Drop Totals or Detail Fields Here, as shown in Illustration 24.

Illustration 24: Drag and Drop the Measure into the Data Pane ...

12.  Drag measure Internet Order Quantity from the Metadata pane to the Data pane, dropping it to the right of the Internet Sales Amount.

13.  Expand the Date dimension within the Metadata pane.

14.  Expand the Calendar folder that appears underneath the expanded Date dimension.

15.  Expand the Date.Calendar hierarchy that appears within the expanded Calendar folder.

16.  Drag member Calendar Year into the Data pane, dropping it onto the area marked Drop Column Fields Here, as depicted in Illustration 25.

Illustration 25: Drag and Drop Calendar Year into the Column Fields of the Data Pane ...

17.  Expand the Product dimension within the Metadata pane.

18.  Expand the Product Categories hierarchy that appears underneath the expanded Product dimension.

19.  Drag the Category level, appearing underneath the Product Categories hierarchy, into the Data pane, dropping it onto the area marked Drop Row Fields Here, as shown in Illustration 26.

Illustration 26: Drag and Drop Product Categories into the Row Fields of the Data Pane ...

The Data pane appears, after our insertions, as partially depicted in Illustration 27.

Illustration 27: Our Initial Browse in the Data Pane (Partial View)

20.  Drill down on each of the Product Categories by clicking the "+" sign to its immediate left, as shown in Illustration 28.

Illustration 28: Drilling Down on Product Categories ...

21.  Drill down on the Calendar Year CY 2003, to display the bi-annual levels H1 CY 2003 and H2 CY 2003.

22.  Drill down on level H2 CY 2003 one level further, to expose the underlying quarterly levels Q3 CY 2003 and Q4 CY 2003, as depicted in Illustration 29.

Illustration 29: Drilling Down on Select Date Dimension Levels ...

23.  In a manner similar to the steps above, perform several browses involving different dimensions / dimension hierarchies and measures.

Having provided for the collection of a representative set of query statistics, we can now get some exposure to the contents of the Query Log.

Overview of the Query log

Structure and Operation of the Query Log

As we have seen in other articles, and have emphasized in the sections above, the Query Log lies at the heart of Usage Analysis for the Analysis Services Database and some of its child objects, including cubes. As we have also previously noted, the Query Log captures details about the queries that have been enacted upon the server by client applications. We have prepared the Query Log for examination in this section, having selected the creation and maintenance of the MSSQL Server table incarnation versus the file option, which we mentioned was possible in passing earlier.

A study of the MSSQL Server table, which we named ANSYS049_MSASQueryLog, reveals some differences over its counterpart in the previous version of MSSQL Server Analysis Services. Unlike its SQL Server Analysis Services 2000 predecessor (by default an MS Access database named msmdqlog.mdb), we can name the Query Log table whatever we direct in the Properties settings for the Analysis Server under consideration, and begin with an MSSQL Server table (rather than converting an MS Access table to one) as we saw above.

A look at the ANSYS049_MSASQueryLog table reveals the nature of the data within the Query Log. Let's look at the layout of the table from SQL Server Management Studio, before examining its contents on a more specific basis.

1.  From within Object Explorer, right-click the ANSYS049_MSASQueryLog table (housed within the Tables folder of the AdventureWorksDW relational database, as we saw earlier).

2.  Select Modify from the context menu that appears, as shown in Illustration 30.

Illustration 30: Opening the ANSYS049_MSASQueryLog Table Schema ...

The ANSYS049_MSASQueryLog table schema appears on a new Browser tab (adjacent to the Adventure Works [Browse] tab we opened earlier), within the SQL Server Management Studio, as depicted in Illustration 31.

Illustration 31: The ANSYS049_MSASQueryLog Table Schema

As we noted in Usage-Based Optimization in Analysis Services 2005, the Usage-Based Optimization Wizard relies upon the Query Log to support its operations. As we can see, the log is composed of several relatively straightforward fields. The fields, together with their respective descriptions, are summarized in Table 1.




The name of the Analysis Services database used in the query


The name of the cube used in the query


The name of the user that ran the query


A numeric string indicating the level from each dimension used to satisfy the query


The time the query began


The length of time (in seconds) of the query execution

Table 1: The Fields of the Query Log

In lockstep with a review of the fields from a description perspective, we can view the actual data in the table from the SQL Server Management Studio, as well.

3.  From the Object Explorer, right-click the ANSYS049_MSASQueryLog table, once again.

4.  Select Open Table from the context menu that appears, as shown in Illustration 32.

Illustration 32: Opening the ANSYS049_MSASQueryLog Table ...

The ANSYS049_MSASQueryLog table appears on another new Browser tab (adjacent to the tabs we have already opened), within the SQL Server Management Studio, as partially depicted in Illustration 33.

Illustration 33: Partial View of the ANSYS049_MSASQueryLog Table

Each of the fields has significant potential, with regard to analysis and reporting utility. I have even created cubes from this table, which, coupled with performance, sizing and other such information from various sources, can support all manner of administrative and similar analysis. The fourth column, Dataset, can be highly useful with regard to the specific information that it reveals about cube usage. The somewhat cryptic records within this column represent the associated levels accessed for each dimensional hierarchy within the query. An example of the Dataset field appears (enclosed in a red rectangle), within a subset of a sample row, as shown in Illustration 34.

Illustration 34: Example of the Dataset Field

While we won't go into a detailed explanation in this lesson, I expect to publish a prospective article that outlines the interpretation of the digits in the Dataset field (we will trace an example Dataset field's component digits to their corresponding components in the respective cube structure), along with more information regarding report writing based upon the Query Log in general. Our purpose here is more to expose general options for using the Query Log directly to generate customized usage analysis reports.

Additional fields provide rather obvious utility in analyzing cube usage, together with performance in general. The fields present information which, particularly in combination with Dataset, helps us to report precisely on the exact points at which queries interact with the cube. These combinations can provide excellent access and "audit" data. To some extent, they can confirm the validity of cube design if, say, a developer wants to verify which requests, collected during the business requirements phase of cube design, are actually valid, and which, by contrast, might be considered for removal from the cube structure based upon disuse, should the time arrive that we wish to optimize cube size and performance by jettisoning little-used data.

StartTime and Duration provide the ingredients for evolved performance trending (via relational reports, OLAP reports, KPIs assembled from either or both, and more), and act as useful statistics upon which to base (or filter) numerous types of administrative reports, including information that will help us to plan for heavy reporting demands and other cyclical considerations.

Customizing Query Log Capture

As we have seen, the usage-based analysis and optimization processes provided via the Usage-Based Optimization Wizard perform their functions based upon statistics captured in the Query Log. From within the Analysis Server Properties dialog box, which contains options that control user interfaces, server environment, processing, logging, and add-ins, we can make the query logging process more frequent than the default of one-in-every-ten queries, as we saw earlier. Moreover, from the Properties settings, we can:

  • Stop and start logging (we can leave it stopped entirely, if we desire);
  • Clear, idle or restart the log;
  • Create a new "prospective" log, while retaining its predecessor for archiving, etc.;
  • Change the logging interval.

We have also mentioned that we can further manage the automatic logging of processing messages by directing the server to enable the logging of the messages to a log file for which we can designate a file path and name.

While setting the logging interval too low might degrade performance in a busy production environment, the logging interval setting for a development environment might typically be a lower number than 10. This would obviously allow us to capture more voluminous statistics to support intensive analysis of cube performance and use, prior to optimizing it for final delivery to information consumers. To cite an example of the utility of lowering the Sampling Rate that most of us might find intuitive, a fairly straightforward approach to optimizing performance based on usage is to create partitions with zero aggregations, adjust query logging to log every query for a period of time to capture typical usage patterns, and then use the Usage-Based Optimization Wizard to design aggregations appropriate to the usage. Once this is done, we can likely afford to raise the Sampling Rate frequency again, to lower the overhead inherent in its use.

5.  Exit SQL Server Management Studio when ready.

Now that we have a basic understanding of the workings of the Query Log, we will discuss options for producing customized reports to meet our business needs.

Direct Reporting for Sophisticated Utilization Analysis

As many of us probably can see, we can rely upon the fact that the options for reporting choices for cube utilization analysis are plentiful, whether we maintain the Query Log in an MSSQL relational table or a file, as we have discussed, or otherwise move / transform the data, and house it in an administrative reporting warehouse / mart, or some other such arrangement. We will find that many common packages can be used in identical fashion to report from these stores via ODBC and other channels. I have even created cubes (both for Analysis Services and other popular OLAP cubes) for larger clients from the statistical information regarding cube usage, together with statistics that come from other diagnostic sources, generating robust and useful mechanisms for tracking cube usage and performance from many perspectives. (I expect to publish articles that detail more of the specifics of some of these administrative database and reporting options, in later articles in this series, as well as my MSSQL Server Reporting Services series, here at Database Journal).

Regardless of the reporting application, the concepts are essentially the same in reporting from the Query Log. The general steps include the following:

  • Establishment of a connection to MSSQL Server, and the database containing the Query Log table (or a connection to the respective location of the data if it has been housed elsewhere);
  • Creation of a query / dataset against the data source;
  • Creation of a report or other layout file within which to accumulate / present the selected data;
  • Publication / deployment of the report / other layout in a manner whereby it becomes accessible to the intended audience(s).

As I have stated, our "medium" for reporting can be selected from a wide array of applications. I have created similar reporting processes in the past using a wide range of business intelligence tools, including MSSQL Server Reporting Services, Cognos, Business Objects, Crystal Reports, ProClarity, MicroStrategy, and Microsoft Office, among other less common tools.

Because reporting typically entails more than the mere entrainment of the data from the Query Log, for use in a report or reports within any of a multiple choice of applications, we will not be able to examine report writing and formatting considerations, aggregating the data in the report or elsewhere, etc., in this article. Many of us will know the steps required to create robust and attractive reports within our own choices of solutions. Other of my articles elsewhere deal with the specifics of working with various reporting options. The demand is evident, in discussions with my clients and readers, for the capability to trend cube performance, create user access reports, and so forth, and I will focus later on some of those needs, together with ways to meet them. I will attempt to accomplish this over the months to come, with different reporting tools after we have exposed other components of the statistical data source, of which the Query Log is only a part.

Summary ...

In this article, we introduced the general need for more sophisticated analysis based upon usage analysis statistics that we can collect surrounding our Analysis Services cubes. Our primary focus was a closer examination of the source of Analysis Services Database (and predominantly cube) performance statistics, the Query Log, discussing its location and physical structure, how it is populated, and other characteristics.

We first created a copy of a sample Analysis Services database for use in our practice exercise, and then enabled the Analysis Server Query Log to capture query statistics. We then processed our cube, before manipulating data to create Query Log entries, to complete preparation for our overview of the Query Log.

We next moved into the focus of our session, examining the Query Log contents, discussing the various statistics captured. Finally, we discussed reporting possibilities, commenting on both relational and OLAP options. As a part of our exploration of Query Log statistics capture, we touched upon various means of customizing Query Log capture to meet local needs.

» See All Articles by Columnist William E. Pearson, III

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