Skip to main content

Star schemas and aggregate (or summary) fact tables


Aggregate tables can further improve query performance by reducing the number of rows over which higher-level metrics must be aggregated. 
However, the use of aggregate tables with dimension tables is not a valid physical modeling strategy. Whenever aggregation is performed over fact data, it is a general requirement that tables joined to the fact table must be at the same attribute level or at a higher level. If the auxiliary table is at a lower level, fact rows will be replicated prior to aggregation and this will result in inflated metric values (also known as "multiple counting").

With the above Time dimension table, a fact table at the level of Day functions correctly because there is exactly one row in DIM_TIME for each day. To aggregate the facts to the level of Quarter, it is valid to join the fact table to the dimension table and group by the quarter ID from the dimension table.

Sql
select DT.QUARTER_ID,
   max(DT.QUARTER_DESC) Quarter_Desc
   sum(FT.REVENUE) Revenue
from DAY_FACT_TABLE FT
   join DIM_TIME DT
      on (FT.DAY_ID = DT.DAY_ID)
group by DT.QUARTER_ID

If, however, there is an aggregate fact table already at the level of Quarter, the results will not be correct. This is because the query must join on Quarter ID, but the quarter ID is not a unique key of the dimension table. Because any given quarter of a year contains 90, 91 or 92 days, the dimension table will contain that many rows with the same quarter ID. Thus fact rows will be replicated prior to taking the sum, and the sum will be too high.

Sql
select FT.QUARTER_ID,
   max(DT.QUARTER_DESC) Quarter_Desc
   sum(FT.REVENUE) Revenue
from QTR_FACT_TABLE FT
   join DIM_TIME DT
      on (FT.QUARTER_ID = DT.QUARTER_ID)
group by FT.QUARTER_ID

This is a generally recognized problem with star schemas, and is not strictly a MicroStrategy limitation.

Star schemas will function correctly with MicroStrategy SQL Generation Engine 8.x as long as they obey the general data warehousing principle that fact tables should not be at a higher level than the dimension tables to which they are joined.

If aggregate tables are required, it is necessary to provide higher-level lookup tables with unique rows corresponding to each aggregate table's key. Logical views are a way to do this without adding tables or views to the warehouse. For example, LWV_LU_QUARTER may be defined using the following SQL statement:

Sql
select distinct QUARTER_ID, QUARTER_DESC, YEAR_ID
from DIM_TIME

 

With this logical view, it becomes possible for MicroStrategy SQL Generation Engine 8.x to query the quarter-level fact table as follows. Since the logical view has distinct rows per quarter, multiple counting will not occur in this query.

Sql
select FT.QUARTER_ID,
   max(LQ.QUARTER_DESC) Quarter_Desc
   sum(FT.REVENUE) Revenue
from QTR_FACT_TABLE FT
   join (select distinct QUARTER_ID, QUARTER_DESC, YEAR_ID
         from DIM_TIME) LQ
      on (FT.QUARTER_ID = LQ.QUARTER_ID)
group by FT.QUARTER_ID

For more information on the use of logical views in MicroStrategy SQL Generation Engine 8.1.x and 9.x, consult the MicroStrategy Project Design Guide manual, Appendix B: Logical Tables, "Creating logical tables."

Aggregate tables store pre-summarized totals at a higher level of aggregation than the most granular fact table. They allow reports to be generated from small, rather than large, tables; therefore, performance is enhanced. A successful aggregation strategy seeks to choose aggregate tables that will have the most impact while taking the least amount of space.

Aggregation decisions are driven by the following factors:

  • Usage patterns: Build aggregate tables that are likely to be used the most.
  • Compression ratios: The compression ratio between two tables is defined as the size of the aggregate compared to the size of the smallest table from which the aggregate can be derived.
  • Volatility: Changes in hierarchies over time impact the accuracy of aggregate tables. Sometimes aggregate tables must be rebuilt as a result of changes in dimensions.
A good candidate for aggregation should have at most 10-15 percent of the size of the smallest table from which it is derived.

EXAMPLE:
The MicroStrategy Tutorial project uses aggregate tables by default. A simple metric sum (Revenue) will go to different aggregate tables depending on the attributes on the template.

  1. Create a report with Year on the rows and Revenue on the columns.
  2. Execute the report and view the SQL:

  3. Drill from Year to Item and view the SQL:

The query will go from using ORDER_FACT to ORDER_DETAIL. When Year is on the template, the engine selects the smaller table and the fact is calculated as:

sum(a11.ORDER_AMT)
    instead of:

    sum((a11.QTY_SOLD * (a11.UNIT_PRICE - a11.DISCOUNT)))
    Labels:

    Comments

    1. hinaFebruary 5, 2021 at 12:19 PM

      Is there any solution now to use aggregate tables with star schema without creating logical tables?

      ReplyDelete

    Post a Comment

    Popular posts from this blog

    MicroStrategy URL API Parameters

    MicroStrategy URL Structure The following table summarizes the root URL structure used for every request to MicroStrategy Web. Environment Main Application URL Administration URL J2EE http://webserver/MicroStrategy/servlet/mstrWeb http://webserver/MicroStrategy/servlet/mstrWebAdmin .NET http://webserver/MicroStrategy/asp/Main.aspx http://webserver/MicroStrategy/asp/Admin.aspx Every request sent to MicroStrategy Web calls a central controller. Parameters are appended to  Main.aspx  or  mstrWeb  (in a .NET and J2EE environment, respectively) to indicate to the controller how the request should be internally forwarded and handled. The following examples show a URL for accessing a MicroStrategy folder when the user does not have an existing session. The URL contains not only the parameters needed to connect to MicroStrategy Web, but also the parameters needed to log on and create a session. J2EE environment: <a href="http:...
    2 comments
    Read more

    Microstrategy "Error type: Odbc error. Odbc operation attempted

     "Error type: Odbc error. Odbc operation attempted: SQLExecDirect. [HYT00:0: on SQLHANDLE] [MicroStrategy][ODBC Oracle Wire Protocol driver]Timeout expired" is shown when executing reports from Web When users are trying to execute some reports in MicroStrategy web in particular, they may receive the Error “SQL Generation Complete Index out of range” and “Timeout expired” error as shown below: Possible Causes: One possible cause is that the MicroStrategy Intelligence Server using a cached database connection that was already dropped by the RDBMS. To resolve this: Admin should delete the database connection caches and create a new DSNs in case they are sharing DSNs to connect to different databases. In addition, change the settings for the ‘Connection lifetime’ and the ‘Connection idle time out’.  Follow the steps below to perform the mentioned changes and verify the report after each step and some of the settings require i-server r...
    4 comments
    Read more

    Case functions Microstrategy

    Ca se functions Microstrategy Case functions return specified data in a SQL query based on the evaluation of user-defined conditions. In general, a user specifies a list of conditions and corresponding return values. Case This function evaluates multiple expressions until a condition is determined to be true, then returns a corresponding value. If all conditions are false, a default value is returned.  Case  can be used for categorizing data based on multiple conditions. This is a single-value function. Syntax Case ( Condition1 ,  ReturnValue1 ,  Condition2 , ReturnValue2 ,...,  DefaultValue ) Example Case(([Total Revenue] < 300000), 0, ([Total Revenue] < 600000), 1, 2) sum(Case (Day@DESC in (“Sat”,”Sun”), Sales, 0) {~+} Sum(Case(Category@DESC In("Books","Electronics"),Revenue,0)){~+} CaseV (case vector) CaseV  evaluates a single metric and returns different values according to the results. It can be used to perfo...
    3 comments
    Read more

    Create an alert-based subscription in MicroStrategy Distribution Services

    Create an alert-based subscription in MicroStrategy Distribution Services on Web Subscription to a report or Report Services document which will be executed when a certain conditional threshold is met based on another executing report. For example, a scheduled report executes which shows the Revenue by day for the past week. If the Revenue on any one day falls below a certain value, a subscription to another report or Report Services document can be triggered and delivered to a recipient. An alert based subscription can only be created directly on a report; however, another report or Report Services document can be delivered when the alert based subscription is triggered. Note: you need a grid report to create an alert and you cannot create if you want to create on a document with text boxes. The following example will walk through the basic steps on how to setup a subscription based on an alert like this: Follow the brief  steps bel...
    2 comments
    Read more

    RunningSum calculation only on the metric subtotal in MicroStrategy

    RunningSum calculation only on the metric subtotal in MicroStrategy Here are the series of steps to setup report objects in which metrics and subtotals so only the  subtotal field  will contain the  RunningSum  and the  regular metric values  will be  standard sum values . 1) Create Metric 1 which is the sum of the fact that is to be in the columns. 2) Create Metric2 as the RunningSum of Metric1.  NOTE:  The  sortby  parameter for the RunningSum should be set to whichever attribute you want the report sorted by. 3) Create Metric3 as Metric1 + (Metric2 x 0) 4) Create a new subtotal called "Max" which is defined as Max() 5) On the Subtotals/Aggregation tab for Metric 3, set the Total subtotal function to be "Max" and select the check box for "Allow Smart Metric" 6) Create the desired report and place the 3 metrics on the report.  NOTE:  Only Metric3 is required on the gri...
    2 comments
    Read more

    Creating a .mstrc file from an empty text file

    Creating a .mstrc file from an empty text file If instead a “.mstrc” file needs to be created for an environment connection prior submission, please follow these steps. To create a MicroStrategy Environment connection file .mstrc, please open a Notepad or Notepad++. Use the Notepad and use the following syntax by replacing the values according to your environment: {   "authenticationMode" : 1,   "dossierServerURL" : " https://LIBRARY_SERVER_URL/MicroStrategyLibrary_EXAMPLE/" ",   "environmentName" : "ENVIRONMENT_NAME" } The file looks like: Note: If it is a default MicroStrategy installation of MicroStrategy Library, the environment URL format will be the following: https://LIBRARY_SERVER_URL_or_IP:8080/MicroStrategyLibrary/ Save and assign a name to the file like “My_first_connection_file.mstrc”.   What does the .mstrc include? Environment Name—a unique name for your environment dossierServerURL—refers to URL of the Li...
    1 comment
    Read more

    Apply or Pass-through functions in Microstrategy

    Ap ply (Pass-Through) functions MSTR Apply functions provide access to functions or syntactic constructs that are not standard in MicroStrategy but are provided by various RDBMS systems.. Syntax common to Apply functions Apply Function Name   ("expression with placeholders", Arg1, Arg2, Arg3, …ArgN) where: Apply Function Name  – is a generic name used for the predefined pass-through functions described above expression with placeholders  – is the string describing the actual expression or syntax that the engine uses while generating the SQL and which is sent to the RDBMS. The placeholders are represented by #0, #1, and so on. "#" is a reserved character for MicroStrategy. Arg  – is an argument that replaces the parameter markers in the pattern. Arg1 replaces #0, Arg2 replaces #1, and so on. There are   five  pre-defined Apply functions to replace regular, predefined functions of the same type. For more details, cli...
    6 comments
    Read more

    Fact tables levels tables in Microstrategy explained

    Fact tables levels in Microstrategy: Fact tables are used to store fact data. Fact tables should contain attribute Id's and fact values which are measurable. All the descriptive information about the fact tables should stored in Dimension tables either in Star Schema fashion or Snow Flake Schema fashion which is best suited to your reporting solution. Since attributes provide context for fact values, both fact columns and attribute ID columns are included in fact tables. Facts help to link indirectly related attributes using these attribute ID columns. The attribute ID columns included in a fact table represent the level at which the facts in that table are stored. So the level of a fact table in the Fact_Item_Day_Customer can be the attribute Id's which is at Day, Item & Customer Id level. For example, fact tables containing sales and inventory data look like the tables shown in the following diagram: Base fact columns ver...
    2 comments
    Read more

    Update the data on an Intelligent Cube without having to republish the entire cube in MicroStrategy

    Update the data on an Intelligent Cube without having to republish the entire cube in MicroStrategy MicroStrategy has introduced a feature known as, Incremental Refresh Options, which allow Intelligent Cubes to be updated based on one or more attributes, by setting up incremental refresh settings to update the Intelligent Cube with only new data. This can reduce the time and system resources necessary to update the Intelligent Cube periodically versus a full republish. For example, if a user has an Intelligent Cube that contains weekly sales data, the user may want this Intelligent Cube to be updated at the end of every week with the sales data for that week. By setting up incremental refresh settings, he can make it so that only data for one week is added to the Intelligent Cube, without affecting the existing data and without having to reload all existing data. Users can select t...
    7 comments
    Read more

    Microstrategy Dashboard performance improvements steps

    Microstrategy  Dashboard performance improvements steps: Many times, causes of poor performance can be simplified to specific components. To troubleshoot performance issues, users must identify these components, then make the appropriate modifications to the environment and/or to the MicroStrategy dashboard to reduce bottlenecks. Dashboard execution stages can be represented below: MicroStrategy Intelligence Server When an end user makes a  Document Execution Request  through any client (a web browser via MicroStrategy Web, the MicroStrategy Desktop/Developer client, the MicroStrategy Mobile app, or the MicroStrategy Office client), the request is sent to the MicroStrategy Intelligence Server, which processes the request and prepares the response. The MicroStrategy Intelligence Server will execute all children datasets on the dashboard by either generating SQL and running this against the data warehouse, or by fetching data from a cache. The Inte...
    1 comment
    Read more