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

    Best practices for using Distribution Services in Microstrategy

    Best practices for using Distribution Services MicroStrategy recommends the following best practices when scheduling Distribution Services subscriptions, in addition to the best practices given above: • For best results, follow the steps listed in  High-level checklist to set up a report delivery system . • PDF, plain text, and CSV file formats generally offer the fastest delivery performance. Performance can vary, depending on items including your hardware, operating system, network connectivity, and so on. • The performance of the print delivery method depends on the speed of the printer. • When sending very large reports or documents: ▫ Enable the zipping feature for the subscription so that files are smaller. ▫ Use bulk export instead of the CSV file format. Details on bulk exporting are in the  Reports  chapter of the  Advanced Reporting Guide . ▫ Schedule subscription deliveries to occur when your Intelligence Server is experiencing low ...
    1 comment
    Read more

    Data Mart Reports in Microstrategy

    Creating Data Mart Reports in Microstrategy   When there is requirement to store all the report results to a database table you can use the interesting feature in Microstratgey called Data Mart Reports. To create a data mart table, you first create a data mart report that defines the columns of the data mart table. You then create the data mart table and populate it with data. The steps below walk you through the process of creating a data mart report and then executing the report to create a data mart table. The steps also include an example for most steps, based on Tutorial sample data in the MicroStrategy Tutorial project.                Follow the simple steps below to create a datamart report: 1 In MicroStrategy Developer, create a new report or select an existing report to use as the data mart table. The report should contain the attributes...
    1 comment
    Read more

    Derived metric based on attribute values

    Derived metric based on attribute values Here is how could create and display data correctly on using below simple steps.  Create a report with Category, Subcategory and Revenue. Create New Metric in a report or VI.  Case((Category@ID = 1), Revenue, 0) Booksand Name it as Revenue for  where 2 is Category ID for "Books"  Report will display result as below.  Result for new metric is blank. Now to fix this create a new Derived metric on Category attribute first with formula as  Max(Category) {~ }  and calling Books Now Edit the "Revenue for Books metric and Replace Category@ID with this new Books metric formula would looks like this  Case((Books = 1), Revenue, 0).  Report result would now display as expected as shown below
    2 comments
    Read more

    Prompt-in-prompt(Nested Prompts) in Microstrategy

    Prompt-in-prompt(Nested Prompts) in  Microstrategy Nested prompts allows you to create one prompt based on the other and other bases on another, nested prompts allows us to prompt the highest level(Like year) to middle level(like Quarter, then to the low level(like Month). Here you can see how to  create a 3-level deep nested prompt that will prompt the user to select a year, then a quarter within that year, then a month within that quarter. Prompt-in-prompt is a feature in which the answer to one prompt is used to define another prompt. This feature is only implemented for element list prompts . The following procedure describes how to achieve this: Create the highest level filter. This is a filter which contains a prompt on an attribute element list. Create a filter on the attribute "Year." Click "prompt on attribute element list" and click "Next" through the rest of the screens to accept the default values. Do not set any additio...
    3 comments
    Read more

    User request is completed. (Ran out of memory)

    Unable to Run/Edit particular MicroStrategy reports ue to the following error: User request is completed. (Ran out of memory) User request is completed. (Ran out of memory) The above issue appeared in MSTR Web Universal version 10.5 We tried the below options without any luck: 1. i-server restart 2. Web server restart 3. clear document cache/dataset cache 4. Web server cache clear as below: The correct option is to increase the contract memory settings: Using the Memory Contract Manager The  MCM settings are in the Intelligence Server Configuration Editor, in the  Governing Rules: Default: Memory Settings  category. The  Enable single memory allocation governing  option lets you specify how much memory can be reserved for a single Intelligence Server operation at a time. When this option is enabled, each memory request is compared to the  Maximum single allocation size (MBytes)  setting. If the request ...
    1 comment
    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

    MicroStrategy VLDB properties with Hive

     Recommended VLDB Properties for use of  MicroStrategy 9 with Hive 0.7x The recommended VLDB optimizations for Hive 0.7x are listed below. These values are set by default when the "Hive 0.7x" database object is used (set at  Configuration Managers > Database Instances > Database Instance > Database connection type ) Selected Default VLDB Properties for Hive 0.7x  VLDB Category  VLDB Property Setting  Value   Tables  Fallback Table Type  Permanent Table  Tables  Maximum SQL Passes Before FallBack   0 (no threshold)  Tables  Maximum Tables in FROM Clause Before FallBack  0 (no threshold)  Tables  Drop Temp Table Method  Drop after final pass   Tables  Table Creation Type  Implicit Table  Query Optimizations   Sub Query Type   Use Temporary Table, falling back to IN (SELECT COL) for cor...
    Post a Comment
    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

    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

    Types of prompts in Microstrategy

    Types of prompts in Microstrategy The different types of prompts allow you to create a  prompt  for nearly every part of a report. Prompts can be used in many objects including reports, filters, metrics, and custom groups, but all prompts require user interaction when the report is executed. The correct prompt type to create depends on what report objects you want users to be able to base a filter on to filter data, as described in the list below. Filter definition prompts   allow users to determine how the report's data is filtered, based on one of the following objects: Attributes in a hierarchy : Users can select prompt answers from one or more attribute elements from one or more attributes. The attribute elements that they select are used to filter data displayed on the report. This prompt lets you give users the largest number of attribute elements to choose from when they answer the prompt to define their filtering criteria. For example, on a repor...
    1 comment
    Read more