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Structure and Operation of the Concern Log
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As we accept apparent in added articles, and accept emphasized in the sections above, the Concern Log lies at the affection of Acceptance Assay for the Assay Services Database and some of its adolescent objects, including cubes. As we accept additionally ahead noted, the Concern Log captures capacity about the queries that accept been allowable aloft the server by applicant applications. We accept able the Concern Log for assay in this section, accepting called the conception and aliment of the MSSQL Server table apotheosis adjoin the book option, which we mentioned was attainable in casual earlier.
A abstraction of the MSSQL Server table, which we called ANSYS049_MSASQueryLog, reveals some differences over its analogue in the antecedent adaptation of MSSQL Server Assay Services. Unlike its SQL Server Assay Services 2000 antecedent (by absence an MS Admission database called msmdqlog.mdb), we can name the Concern Log table whatever we absolute in the Properties settings for the Assay Server beneath consideration, and activate with an MSSQL Server table (rather than converting an MS Admission table to one) as we saw above.
A attending at the ANSYS049_MSASQueryLog table reveals the attributes of the abstracts aural the Concern Log. Let’s attending at the blueprint of the table from SQL Server Management Studio, afore analytical its capacity on a added specific basis.
1. From aural Object Explorer, right-click the ANSYS049_MSASQueryLog table (housed aural the Tables binder of the AdventureWorksDW relational database, as we saw earlier).
2. Select Modify from the ambience card that appears, as apparent in Illustration 30.
Illustration 30: Opening the ANSYS049_MSASQueryLog Table Action …
The ANSYS049_MSASQueryLog table action appears on a new Browser tab (adjacent to the Adventure Works [Browse] tab we opened earlier), aural the SQL Server Management Studio, as depicted in Illustration 31.
Illustration 31: The ANSYS049_MSASQueryLog Table Schema
As we acclaimed in Usage-Based Admission in Assay Services 2005, the Usage-Based Admission Wizard relies aloft the Concern Log to abutment its operations. As we can see, the log is composed of several almost aboveboard fields. The fields, calm with their agnate descriptions, are abbreviated in Table 1.
The name of the Assay Services database acclimated in the query
The name of the cube acclimated in the query
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The name of the user that ran the query
A numeric cord advertence the akin from anniversary ambit acclimated to amuse the query
The time the concern began
The breadth of time (in seconds) of the concern execution
In lockstep with a assay of the fields from a description perspective, we can appearance the absolute abstracts in the table from the SQL Server Management Studio, as well.
3. From the Object Explorer, right-click the ANSYS049_MSASQueryLog table, already again.
4. Select Open Table from the ambience card that appears, as apparent in Illustration 32.
Illustration 32: Opening the ANSYS049_MSASQueryLog Table …
The ANSYS049_MSASQueryLog table appears on addition new Browser tab (adjacent to the tabs we accept already opened), aural the SQL Server Management Studio, as partially depicted in Illustration 33.
Illustration 33: Partial Appearance of the ANSYS049_MSASQueryLog Table
Each of the fields has cogent potential, with attention to assay and advertisement utility. I accept alike created cubes from this table, which, accompanying with performance, allocation and added such advice from assorted sources, can abutment all address of authoritative and agnate analysis. The fourth column, Dataset, can be awful advantageous with attention to the specific advice that it reveals about cube usage. The somewhat cryptic annal aural this cavalcade represent the associated levels accessed for anniversary dimensional bureaucracy aural the query. An archetype of the Dataset acreage appears (enclosed in a red rectangle), aural a subset of a sample row, as apparent in Illustration 34.
Illustration 34: Archetype of the Dataset Field
While we won’t go into a abundant account in this lesson, I apprehend to broadcast a -to-be commodity that outlines the estimation of the digits in the Dataset acreage (we will trace an archetype Dataset field’s basal digits to their agnate apparatus in the agnate cube structure), alternating with added advice apropos address autograph based aloft the Concern Log in general. Our purpose actuality is added to betrayal accepted options for appliance the Concern Log anon to achieve customized acceptance assay reports.
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Additional fields accommodate rather attainable account in allegory cube usage, calm with achievement in general. The fields present advice which, decidedly in aggregate with Dataset, helps us to address absolutely on the exact credibility at which queries collaborate with the cube. These combinations can accommodate accomplished admission and “audit” data. To some extent, they can affirm the authority of cube architecture if, say, a developer wants to verify which requests, calm during the business requirements appearance of cube design, are absolutely valid, and which, by contrast, ability be advised for abatement from the cube anatomy based aloft disuse, should the time admission that we ambition to optimize cube admeasurement and achievement by auctioning little-used data.
StartTime and Duration accommodate the capacity for acquired achievement trending (via relational reports, OLAP reports, KPIs accumulated from either or both, and more), and act as advantageous statistics aloft which to abject (or filter) abundant types of authoritative reports, including advice that will advice us to plan for abundant advertisement demands and added alternate considerations.
Customizing Concern Log Abduction
As we accept seen, the usage-based assay and admission processes provided via the Usage-Based Admission Wizard achieve their functions based aloft statistics captured in the Concern Log. From aural the Assay Server Properties chat box, which contains options that ascendancy user interfaces, server environment, processing, logging, and add-ins, we can achieve the concern logging action added accepted than the absence of one-in-every-ten queries, as we saw earlier. Moreover, from the Properties settings, we can:
We accept additionally mentioned that we can added administer the automated logging of processing letters by administering the server to accredit the logging of the letters to a log book for which we can baptize a book aisle and name.
While ambience the logging breach too low ability abase achievement in a active assembly environment, the logging breach ambience for a development ambiance ability about be a lower cardinal than 10. This would acutely acquiesce us to abduction added abundant statistics to abutment accelerated assay of cube achievement and use, above-mentioned to optimizing it for final commitment to advice consumers. To adduce an archetype of the account of blurred the Sampling Rate that best of us ability acquisition intuitive, a adequately aboveboard admission to optimizing achievement based on acceptance is to actualize partitions with aught aggregations, acclimatize concern logging to log every concern for a aeon of time to abduction archetypal acceptance patterns, and afresh use the Usage-Based Admission Wizard to architecture aggregations adapted to the usage. Already this is done, we can acceptable allow to accession the Sampling Rate abundance again, to lower the aerial inherent in its use.
5. Exit SQL Server Management Studio back ready.
Now that we accept a basal compassionate of the apparatus of the Concern Log, we will altercate options for bearing customized letters to accommodated our business needs.
As abounding of us apparently can see, we can await aloft the actuality that the options for advertisement choices for cube appliance assay are plentiful, whether we advance the Concern Log in an MSSQL relational table or a file, as we accept discussed, or contrarily move / transform the data, and abode it in an authoritative advertisement barn / mart, or some added such arrangement. We will acquisition that abounding accepted bales can be acclimated in identical appearance to address from these food via ODBC and added channels. I accept alike created cubes (both for Assay Services and added accepted OLAP cubes) for beyond admirers from the statistical advice apropos cube usage, calm with statistics that appear from added analytic sources, breeding able-bodied and advantageous mechanisms for tracking cube acceptance and achievement from abounding perspectives. (I apprehend to broadcast accessories that detail added of the specifics of some of these authoritative database and advertisement options, in afterwards accessories in this series, as able-bodied as my MSSQL Server Advertisement Services series, actuality at Database Journal).
Regardless of the advertisement application, the concepts are about the aforementioned in advertisement from the Concern Log. The accepted achieve accommodate the following:
As I accept stated, our “medium” for advertisement can be called from a advanced arrangement of applications. I accept created agnate advertisement processes in the accomplished appliance a advanced ambit of business intelligence tools, including MSSQL Server Advertisement Services, Cognos, Business Objects, Crystal Reports, ProClarity, MicroStrategy, and Microsoft Office, amid added beneath accepted tools.
Because advertisement about entails added than the bald entrainment of the abstracts from the Concern Log, for use in a address or letters aural any of a assorted best of applications, we will not be able to appraise address autograph and formatting considerations, accumulation the abstracts in the address or elsewhere, etc., in this article. Abounding of us will apperceive the achieve appropriate to actualize able-bodied and adorable letters aural our own choices of solutions. Added of my accessories abroad accord with the specifics of alive with assorted advertisement options. The appeal is evident, in discussions with my admirers and readers, for the adequacy to trend cube performance, actualize user admission reports, and so forth, and I will focus afterwards on some of those needs, calm with agency to accommodated them. I will attack to achieve this over the months to come, with altered advertisement accoutrement afterwards we accept apparent added apparatus of the statistical abstracts source, of which the Concern Log is alone a part.
In this article, we alien the accepted charge for added adult assay based aloft acceptance assay statistics that we can aggregate surrounding our Assay Services cubes. Our primary focus was a afterpiece assay of the antecedent of Assay Services Database (and predominantly cube) achievement statistics, the Concern Log, discussing its area and concrete structure, how it is populated, and added characteristics.
We aboriginal created a archetype of a sample Assay Services database for use in our convenance exercise, and afresh enabled the Assay Server Concern Log to abduction concern statistics. We afresh candy our cube, afore manipulating abstracts to actualize Concern Log entries, to complete alertness for our overview of the Concern Log.
We abutting confused into the focus of our session, analytical the Concern Log contents, discussing the assorted statistics captured. Finally, we discussed advertisement possibilities, commenting on both relational and OLAP options. As a allotment of our analysis of Concern Log statistics capture, we affected aloft assorted agency of customizing Concern Log abduction to accommodated bounded needs.
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