Patent Publication Number: US-7716172-B2

Title: Method of splitting a multi-dimensional cube between a multi-dimensional and a relational database

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a divisional of application Ser. No. 10/101,664, entitled “A METHOD OF SPLITTING A MULTI-DIMENSIONAL CUBE BETWEEN A MULTI-DIMENSIONAL AND RELATIONAL DATABASE” by Vaishnavi Anjur, Vijay K. Anjur, Hemanta Banerjee, Maya Binkovich, Srinivas Duvvuri, Mark Goldenshteyn, Arun Kumar, Kevin Kaixuan Liao and Igor Nazarenko, filed on Mar. 19, 2002 now U.S. Pat. No. 7,028,046. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates to multi-dimensional databases. 
     BACKGROUND OF THE INVENTION 
     Relational databases are a collection data items organized as a set of formally described tables from which data can be accessed or reassembled in different ways without having to reorganize the database tables. 
     The standard user and application program interface for relational databases is the Structured Queried Language (SQL). A relational database is a set of tables containing data fitted into predefined categories. Each table contains one or more data categories in the column. Each row contains a unique data element for the categories defined by the columns. Tables describe categories such as an order, product, customer, date, and sales price. 
     The relational database, arranged in tables, may be too slow for on-line analytical processing (OLAP) applications. A multi-dimensional database rapidly process data to quickly generate responses to on-line requests. Multi-dimensional databases use the concept of a cube to represent dimensions of the data available to the user. For example, dimensions can include product, geography, time or other dimensions. Additionally, the Multi-dimensional database creator can define hierarchies and levels within a dimension (for example, quarter and month levels within a time hierarchy). 
     Frequently, multi-dimensional databases are created using input from existing relational databases. Data is transferred and processed for the multi-dimensional database in order to allow for rapid analysis by users. Not all of the data in the relational database can typically be transferred into the multi-dimensional database since relational databases can be much larger than Multi-dimensional databases 
     It is desired to have an improved system for operating a multi-dimensional database. 
     SUMMARY OF THE INVENTION 
     Exemplary embodiments of the present invention relate to a method, the method comprising transferring data from a relational database to a multi-dimensional database. The multi-dimensional database stores data for multiple data dimensions down to predetermined levels in each dimension hierarchy. The method includes enabling access to the relational database for data not stored in the multi-dimensional database. The method includes responding to multi-dimensional data requests by first accessing the multidimensional database and, if necessary, accessing the relational database by constructing queries to the relational database. 
     Exemplary embodiments of the present invention are directed to a system comprising a multi-dimensional database storing data for multiple data dimensions down to first predetermined levels in each dimension hierarchy. The system includes a relational database with access enabled for data not stored in the multi-dimensional database. The multi-dimensional data requests cause data to be obtained from the multidimensional database and, if necessary, data is obtained from the relational database by constructing queries to the relational database. 
     In an exemplary embodiment, a user selects multi-dimensional and relational portions of a hierarchy for each dimension. When the user requests data that is in the relational portion of the relational database but not in the multi-dimensional portion stored in the multi-dimensional database, the system will produce queries to the relational database to obtain data in the relational portion left behind in the relational database. 
     In an exemplary embodiment of the present invention, a graphical interface is used that allows a selection of multi-dimensional and relational portions of at least one hierarchy for at least one dimension. The selection is done by selecting levels in the hierarchy for which the multi-dimensional portion is to be built and selecting second levels below the first level in which the relational portion is enabled. Data is obtained from the multi-dimensional proportion from a multi-dimensional database and data is obtained from the relational portion by constructing queries to a relational database. 
     In an exemplary embodiment, a multi-dimensional portion, blocked portion and relational portion of at least one hierarchy for one dimension is selected. Data is then transferred between the relational database and the multi-dimensional database for the multi-dimensional portion and, thereafter, the size of the blocked and relational portions are modified. 
     In an exemplary embodiment of the present invention, a multi-dimensional portion and relational portion of at least one hierarchy for at least one dimension is selected. Metadata is produced. The metadata indicates a partition between the multidimensional and relational portions and for each member of the lowest level of the multi-dimensional portion of the hierarchy. The metadata indicates whether any child nodes exist below the partition. Data is obtained from the multi-dimensional portion from a multi-dimensional database and obtained from the relational portion by constructing queries to the relational database, the queries being constructed using the metadata. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWING FIGURES 
         FIG. 1A  is a diagram that illustrates an exemplary embodiment of the present invention. 
         FIG. 1B  is a flowchart that illustrates an exemplary embodiment of the present invention. 
         FIG. 2A  is a diagram that illustrates examples of hierarchies. 
         FIG. 2B  is a diagram that illustrates the cube used for the example of  FIG. 2A , illustrating the multi-dimensional, blocked and relational portions. 
         FIG. 3  is diagram illustrating an exemplary method of the present invention. 
         FIG. 4  is a diagram illustrating an exemplary method of the present invention. 
         FIG. 5  is a diagram that illustrates a display of the hierarchies that allows the selection of the relational and multi-dimensional storage. 
         FIG. 6  is a diagram that illustrates metadata used in one embodiment of the present invention. 
         FIG. 7  is a diagram that illustrates a graphical interface showing the access to elements of the hierarchy. 
         FIGS. 8A and 8B  are diagrams that illustrate examples of a spreadsheet display for one embodiment of the system of the present invention. 
         FIG. 9  is a diagram of a flowchart of an exemplary embodiment of the present invention. 
         FIG. 10  is a flowchart of an exemplary embodiment of the present invention. 
         FIG. 11  is a flowchart of an exemplary embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     An exemplary embodiment of the present invention is directed to a system. The system comprises a multi-dimensional database storing data for multiple data dimensions down to first predetermined levels in each dimension hierarchy. The system includes a relational database with access enabled for data not stored in the multi-dimensional database. The multi-dimensional data requests cause data to be obtained from the multidimensional database and, if necessary, data to be obtained from the relational database by constructing queries to the relational database. 
     In the example of  FIG. 1 , the system  100  comprises a multi-dimensional database  102  storing data for multiple data dimensions down to first predetermined levels in each dimension hierarchy. The system includes a relational database  108  with access enabled for data not stored in the multi-dimensional database. Multi-dimensional data requests cause data to be obtained from the multidimensional database  102  and, if necessary, data to be obtained from the relational database  108  by constructing queries to the relational database. 
     In an exemplary embodiment, the multi-dimensional database  102  is a database that is arranged to allow for On-Line Analytical Processing (OLAP) and to respond to multi-dimensional data requests. Examples of Multi-dimensional databases include MicroSoft OLAP Services and Oracle&#39;s Express. 
     In an exemplary embodiment, the relational database  108  is arranged in a star schema, including dimensional tables and fact tables. The use of the star schema simplifies the transfer of data to the multi-dimensional database  102 . 
     In an exemplary embodiment, administrative software  104  is used to allow the graphical selection of multi-dimensional, relational and blocked portions of the hierarchy for each dimension. Administrative software  104  also controls the transfer of the multi-dimensional data between the relational database and the multi-dimensional database. A number of transfer methods are available for multi-dimensional databases. In an exemplary embodiment, data is manipulated to make it more easy for on-line analysts to obtain the analysis results. 
     Additionally, in an exemplary embodiment, the administrative software  104  creates metadata reflecting a partition between the multi-dimensional and relational portions. In an exemplary embodiment, the metadata indicates the partition between the data stored in the multi-dimensional database and the data stored in the relational database. In an exemplary embodiment, the metadata indicates for each member of the lowest level of the multi-dimensional portion of the hierarchy whether any child node, exists below the partition. 
     In an exemplary embodiment, Software  106  produces requests into the multi-dimensional database. In an exemplary embodiment, software  106  uses the metadata to construct queries into the relational database to obtain data for the relational portion data. 
     In an exemplary embodiment, the data from the relational database  108  is displayed to the user along with the data from the multi-dimensional database  102  using OLAP client software  107 . The OLAP client software  107  does not need to know whether the data is stored in the relational or multi-dimensional database. 
     In an exemplary embodiment, the multi-dimensional, relational, and blocked portions are selectable graphically. 
     An exemplary embodiment of the present invention relates to a method. The method comprises transferring data from a relational database to a multi-dimensional database. The multi-dimensional database stores data for multiple data dimensions down to predetermined levels in each dimension hierarchy. The method includes enabling access to the relational database for data not stored in the multi-dimensional database. The method includes responding to multi-dimensional data requests by first accessing the multidimensional database and, if necessary, accessing the relational database by constructing queries to the relational database. 
       FIGS. 2A and 2B  illustrate of a hierarchy of three dimensions. The dimensions, in this example, are product, time and market. In the example of  FIGS. 2A and 2B , the product dimension includes the hierarchal levels: product group, product sub-group, type and product ID. The time dimension includes the hierarchal levels: year, quarter, month, date. The market dimension includes the hierarchal levels: region, state, county and zip code. Although three dimensions are shown, dimensions of four or greater are also used. In the example of FIGS.  2 A and  2 B, the hierarchal levels are selected as being multi-dimensional, relational, or blocked. In this example, the date level of the time hierarchy is indicated as being relational and the zip code level of the market hierarchy is indicated as being blocked. 
     In one embodiment, there are levels in between the multidimensional portion of a dimension and the relational portion that are not available for access. Thus multidimensional and relational levels do not have to be contiguous. For example: 
     Market (Multidimensional Level M) 
                         
So in this example, drilling down on region level returns cities instead of states because state and county levels are skipped.
 
       FIG. 2B  illustrates an example of a multi-dimensional cube. The multi-dimensional portion includes the data transferred to the multi-dimensional database. In an exemplary embodiment of a multidimensional database, each of the intersections of the database have pre-calculated data. For example, at the intersection region, year, group, which is within the multi-dimensional portion, calculations are done for each specific product group, each specific region and each specific year. This precalculated data is stored in the multi-dimensional database so that this data is easily accessible for on-line analysis. The relational portion includes data that requires queries to be made to the relational database and cannot be obtained directly from the multi-dimensional database. In this example, if one wanted to know the amount of a specific product group sold on a certain date in a given state, one would have to obtain this information from the relational database. This data is obtained by constructing queries to the relational database. 
     The blocked levels, in this example, include the zip code. No data categorized by zip code can be obtained. The blocked data is not accessible through the system. 
     In an exemplary embodiment, a graphical system is used to select which levels in the hierarchy to place within the relational, multi-dimensional and blocked portions. In an exemplary embodiment, the relational portion, multi-dimensional portion and blocked portion can be modified. In a preferred embodiment, the multi-dimensional portion is determined before the transfer of data between the relational database and the multi-dimensional database occurs off-line. In an exemplary embodiment, the selection between the relational and blocked portions occurs after the data transfer. 
       FIG. 3  illustrates a flowchart for an exemplary embodiment of the present invention. In step  300 ; the multi-dimensional, relational and blocked levels of the hierarchy are selected. In step  302 , data is transferred between the relational database to the multi-dimensional database for the multi-dimensional portion of the data. In step  304 , the transferred data is manipulated for multi-dimensional access. As described above, typically the values need to be calculated for a variety of a level combinations that are contained within the multi-dimensional portion. In step  306 , the metadata is constructed and stored. In a preferred embodiment, the metadata indicates the relational portions of the cube, as well as indicating whether there are any members at the lowest multi-dimensional level has any child units. Later, in step  310 , the relational and blocked portions can be adjusted and this causes the metadata to be modified as well. 
       FIG. 4  illustrates a flowchart for an exemplary embodiment. If data is needed, it is determined whether the data is from the relational portion. If so, information is obtained using the multi-dimensional database in step  400 . If the data is from the multi-dimensional database, then it is obtained from the multi-dimensional database in step  402 . 
       FIG. 5  illustrates an example of a graphical interface which is used to select whether a level in the hierarchy is part of the multi-dimensional portion, the relational portion or the blocked portion.  FIG. 5  illustrates an example in which the levels of the hierarchy are selectable by the user or obtained from the star schema in a relational database. The user selects whether each level in the hierarchy is within the multi-dimensional database or relational or blocked portions. In a preferred embodiment, for a specific level, the user clicks on a level to build down the multi-dimensional portion to that level. Additionally, the user can click on a lower level and enable relational storage down to that level. In an exemplary embodiment, all levels above the clicked-on the lowest multi-dimensional level are built into the multi-dimensional database and all of the levels between the lowest multi-dimensional level and the lowest enabled relational level are enabled for the relational portion. Below the lowest enabled relational level are blocked levels. In the example shown in  FIG. 5 , the administrator chooses to build the “market” dimension down to the “state” level into the multi-dimensional database. The user then enables the relational storage down to the next lower level of the hierarchy. Any number of dimensions can be partitioned in this fashion. 
       FIG. 6  illustrates an example of metadata stored for the system of one embodiment of the present invention. The metadata shows for the time hierarchy the multi-dimensional database enabled levels: year, quarter and month, and the relational database enabled level: date. Different members for each level are shown. 
     In an exemplary embodiment, each member of the lowest multi-dimensional level, in this case, month, has associated metadata. In the example of  FIG. 6 , the member “January” of the level “month” has associated with it metadata indicating whether there are any child nodes stored in the relational database. Additionally, in a preferred embodiment, table, column, database indicators of a star schema dimension table, associated with the relational level, are also stored. In an exemplary embodiment, the relational database uses a star schema, and the data within the fact tables of the star schema are modified in the relational database without requiring an update of the metadata. Even when the contents of the dimension levels in the relational portion of the cube change, transparent access to the relational database is maintained. 
       FIG. 7  illustrates an example of how leaf elements of the multi-dimensional portion of the cube track information about whether there are members in the relational portion of the split cube that can be accessed by drilling down the hierarchy. The metadata information is captured when the cube is built. In case of an unbalanced hierarchy, only leaf level elements that have their hierarchies extended need to track this information. Storing whether there are any child nodes of a leaf in the metadata helps the system handle ragged hierarchies. 
     The end-user interacts with the multi-dimensional cube, including the multi-dimensional portion and the relational portion without knowing whether the cube is split between the stores. In an exemplary embodiment, all hierarchal navigational capabilities are available for both the multi-dimensional and relational portions of the cube. In an exemplary embodiment, only navigation among hierarchies of dimensions that have been split is tracked to determine if the cube boundary needs to be crossed for data or metadata access. Information associated with leaf level members about whether the hierarchy continues beyond the member is used to determine if there is a need to access a relational source. 
     In an exemplary embodiment, the end user can either choose to view the entire cube as a transparent logical entity or to be notified when the cube boundary is crossed. 
       FIGS. 8A and 8B  illustrate spreadsheet displays for the examples shown in  FIGS. 2A and 2B . In the example of  FIG. 8A , if a user decides to find out more information about the time dimension, the user can click on January, Quarter 1, 2002. By clicking on the January portion of the spreadsheet, the user drills down to the next lowest level in the time hierarchy, in this case, the date information. As shown in the example of  FIGS. 2A and 2B , the date information is stored in a relational portion of the database. Thus, the system constructs the queries to the relational database to get this data. The production of the queries may depend upon, the spreadsheet arrangement. Note, in the examples of  FIGS. 8A and 8B , the total sales figures for January 24-31 need to be obtained from the relational store to update the display. As the user scrolls down the display, additional data needs to be accessed from the relational database. 
     In one embodiment, when the user clicks upon January, the metadata is checked to see whether January Q1, 2002 has any child elements at the date level, which is part of the relational portion of the cube. In this case, there are a number of level members for the date. The level members for the date are obtained from column values of the dimension table in the star schema of the relational database. 
     In an exemplary embodiment, metadata is used to quickly get the date level members from the dimensional table using an SQL query. If the metadata had indicated that there are no members of the child level, access to the relational database need not be done. Using the date values obtained from the dimensional table, values of the total sales information can be obtained from the fact table in another round of SQL queries. 
     The arrangement of the display can influence the construction of the queries by the system. For example, data below the screen display need not be obtained right away. In one example, if there are thousands of members of a specific level stored in the relational store, it does not make sense to do a SQL query that obtains a large amount of data which requires buffering and which might not ever be displayed. 
       FIG. 9  illustrates a flowchart of an exemplary embodiment of the present invention. In step  900 , a graphical interface is used to select multi-dimensional and blocked portions of at least one hierarchy for at least one dimension, the selection being done by selecting a first level in the hierarchy for which the multi-dimensional portion can be built down to and for selecting a second level, below the first level, at which the relational portion is built down to. In step  902 , data is obtained from the multi-dimensional portion from a multi-dimensional database and data is obtained from a relational portion by constructing queries to a relational database. 
       FIG. 10  illustrates the flowchart of an exemplary embodiment of the present invention. In step  1000 , the multi-dimensional, relational and blocked portions of a least one hierarchy are selected. In step  1002 , data is transferred between the relational database and the multi-dimensional database. In an exemplary embodiment, this database is arranged and manipulated so as to speed the multi-dimensional database access. In step  1004 , after the transfer of the data, between the relational database and the multi-dimensional database, the size of the blocked and relational portions can be modified, preferably by using the graphical interface. 
       FIG. 11  illustrates an exemplary embodiment of the present invention. In step  1102 , the multi-dimensional and relational portions of at least one hierarchy, for at least one dimension, are selected. In step  1104 , metadata is produced, the metadata indicating a partition between the relational and multi-dimensional portions. For each member of the lowest level of the multi-dimensional portion of the hierarchy, the metadata indicates whether any child node exists below that partition. In step  1106 , data is obtained from the multi-dimensional portion from a multi-dimensional database and data is obtained from the relational portion by constructing queries to the relational database, the queries being constructed using the metadata. 
     It will be appreciated by those of ordinary skill in the art that the invention can be implemented in other specific forms without departing from the spirit or character thereof. The presently disclosed embodiments are therefore considered in all respects to be illustrative and not restrictive. The scope of the invention is illustrated by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents thereof are intended to be embraced herein. 
     Embodiments of the present invention relate to relational databases and dimensional databases. As would be known to a person of skill in the art, relational and dimensional databases execute on a computer. A computer may operate according to a program which can be a set of instructions stored on a tangible computer readable medium. Some exemplary tangible computer readable mediums are hard disks (HD), compact discs (CD), and digital versatile discs (DVD). A person of skill in the art would readily appreciate that embodiments of the present invention operate on a computer, which may include a tangible computer readable medium containing a program to implement the steps that provide the functionality of embodiments of the present invention.