Skip to main content

Types of result caches in Microstrategy

Types of result caches Microstrategy

The following types of result caches are created by Intelligence Server:
•Matching caches
•History caches
•Matching-History caches
•XML caches
All document caches are Matching caches; documents do not generate History caches or XML caches. Intelligent Cube reports do not create Matching caches.

Matching caches

Matching caches are the results of reports and documents that are retained for later use by the same requests later on. In general, Matching caches are the type of result caches that are used most often by Intelligence Server.
When result caching is enabled, Intelligence Server determines for each request whether it can be served by an already existing Matching cache. If there is no match, it then runs the report or document on the database and creates a new Matching cache that can be reused if the same request is submitted again. This caching process is managed by the system administrator and is transparent to general users who simply benefit from faster response times.

History caches

History caches are report results saved for future reference in the History List by a specific user. When a report is executed, an option is available to the user to send the report to the History List. Selecting this option creates a History cache to hold the results of that report and a message in the user’s History List pointing to that History cache. The user can later reuse that report result set by accessing the corresponding message in the History List. It is possible for multiple History List messages, created by different users, to refer to the same History cache.
The main difference between Matching and History caches is that a Matching cache holds the results of a report or document and is accessed during execution; a History cache holds the data for a History List message and is accessed only when that History List message is retrieved.
For more information about History Lists, see Saving report results: History List.

Matching-History caches

A Matching-History cache is a Matching cache that is referenced by at least one History List message. It is a single cache composed of a Matching cache and a History cache. Properties associated with the Matching caches and History caches discussed above correspond to the two parts of the Matching-History caches.

XML caches

An XML cache is a report cache in XML format that is used for personalized drill paths. It is created when a report is executed from MicroStrategy Web, and is available for reuse in Web. It is possible for an XML cache to be created at the same time as its corresponding Matching cache. XML caches are automatically removed when the associated report or History cache is removed.
To disable XML caching, select the Enable Web personalized drill paths option in the Project definition: Drilling category in the Project Configuration Editor. Note that this may adversely affect Web performance. 
Labels:

Comments

Post a Comment

Popular posts from this blog

HyperIntelligence Training Videos

HyperIntelligence  Training Videos           Design and build hyper cards Optimizing Datasets for HyperIntelligence Using the HyperIntelligence for Office Outlook Add-In Building HyperIntelligence Cards Using HyperIntelligence for Mobile on Android Deploying HyperIntelligence for Outlook Insights On-The-Go: HyperIntelligence for Mobile Building HyperIntelligence Profile Cards Designing Custom HyperIntelligence Cards Using the Calendar with HyperIntelligence for Mobile
4 comments
Read more

Microstrategy Dossiers explained

Microstrategy  Dossiers With the release of MicroStrategy 10.9, we’ve taken a leap forward in our dashboarding capabilities by simplifying the user experience, adding storytelling, and collaboration.MSTR has  evolved dashboards to the point that they are more than dashboards - they are  interactive, collaborative analytic stories . Ultimately, it was time to go beyond dashboards, both in concept and in name, and so  the've  renamed VI dashboards to  ‘ dossiers ’.  Dossiers can be created by using the new Desktop product or Workstation or simply from the Web interface which replaces Visual Insights. All the existing visual Insights dashboards will be converted to Dossiers   With MicroStrategy 10.9, there was an active focus on making it easier to build dashboards for the widest audience of end users. To achieve this, some key new capabilities were added that make it easier to author, read, interact and collaborate on dashboards ...
7 comments
Read more

Customers Who Live in the Same City as Call Centers

Customers Who Live in the Same City as Call Centers Your new utility company has call centers located throughout the country, and your recent surveys indicate that customers who live in the same city as a call center are particularly satisfied with service due to extremely rapid repairs during power outages. To begin your new advertising campaign, you want to generate a list of Call Centers that coincide with Customer Cities. The following steps create an attribute-to-attribute qualification filter that generates the list of desired cities. To Create an Attribute-To-Attribute Qualification that Compares the Call Center and Customer City Attributes In MicroStrategy Web, log in to a project. Open any folder page (for example, click Shared Folders on the home page). Click the  Create Filter  icon  . From the Object browser on the left, select the  Customer City  attribute from the Customers hierarchy and drag it to the filter pane on the right. Change  Qualify...
1 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

Administration standards to optimize network data transfer speeds

Optimization standards to help developers work with the System Administrator to optimize network data transfer speeds: Place all server components in the same segment to minimize latency between the Intelligence Server, Web server, data warehouse server, and metadata server Expand bandwidth and minimize latency between servers and clients to ensure that bottlenecks do not occur when data is requested over your network Use HTTP compression between the Web servers and Web clients to achieve maximum throughput between these components Configure a Web proxy server to handle caching and reduce the load on the Web server
1 comment
Read more
Microstrategy Release Types Platform release Interval:  Annually every twelve (12) months in December Who:  Entire customer base What:  Focus on production level security, stability, and performance defect fixes for all customers. Expectation:  Customer has chosen platform path and wants product stability without new enhancements. Support:  Three (3) years, patches for approved P1 defects, and regular hotfix cadence addresses critical defects. Feature Release Interval:  Quarterly every three (3) months Who:  Customers with specific feature requirements. What:  New functionality developed in close collaboration with customers and customer council. Expectation:  Customer has chosen feature path, will consume further feature releases. Support:  Six (6) months patch support for approved P1 defects and (eighteen) 18 months troubleshooting. Customers upgrade to next feature release for roll-up f...
1 comment
Read more

mstrio – Python and R wrappers for the MicroStrategy

mstrio – Python and R wrappers for the MicroStrategy REST APIs Connecting to MicroStrategy  Create a connection to the Intelligence Server using   Connection()   and    connect()  in Python and R, respectively. Required arguments for the   Connection()  function are the URL for the MicroStrategy REST API server, MicroStrategy Intelligence Server username and password, as well as the MicroStrategy project name. By default, the   connect()  function anticipates your MicroStrategy Intelligence Server username and password. LDAP authentication is also supported. Use the optional argument    login_mode=16    in the    connect()  function for LDAP authentication.  Extract data from cubes and reports  To extract data from MicroStrategy cubes and reports, use the   get_cube()  and   get_report()  functions. Use...
8 comments
Read more

Types of filters in Microstrategy

Types of filters in Microstrategy Below are the types of filters: 1. Attribute qualification filter These types of qualifications restrict data related to attributes on the report. a) Attribute form qualification Filters data related to a business attribute’s form(s), such as ID or description. •  For example, the attribute Customer has the forms ID, First Name, Last Name, Address, and Birth Date. An attribute form qualification might filter on the form Last Name, the operator Begins With, and the letter H. The results show a list of customers whose last names start with the letter H. b) Attribute element list qualification Filters data related to a business attribute’s elements, such as New York, Washington, and San Francisco, which are elements of the attribute City. • For example, the attribute Customer has the elements John Smith, Jane Doe, William Hill, and so on. An attribute element list qualification can filter data to display only those customer...
6 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