Abstract:
A computer-implemented method of using a database management system (DBMS) for providing an aggregate of a plurality of entities, constructing an aggregate of said plurality of entities in a memory to provide a result, and returning the result from the memory. Constructing the aggregate in memory includes storing in the memory a plurality of intermediate aggregation results each associated with a unique identifier. The unique identifier for each intermediate result is stored in the DBMS. Each unique identifier indicates information identifying a position within a sequence of generating the intermediate result and a pointer to a location in the memory where that intermediate result is stored.

Description:
BACKGROUND OF THE INVENTION  
         [0001]    1. Field of the Invention  
           [0002]    The invention relates to information processing and storage systems. More particularly, it relates to methods, apparatuses and articles of manufacture for manipulating information contained in a database system.  
           [0003]    2. Description of the Related Art  
           [0004]    An aggregate combines several entities into a single entity. In many database systems there is no support to define and implement user-defined aggregate functions.  
           [0005]    For example, consider a table with a spatial column that contains several geometric shapes, one in each row. In database systems without native support for generating an aggregate there is no simple way to construct a single geometric value that represents the union of all the geometries in the column, or a subset thereof. FIGS. 1A and 1B illustrate an aggregate function. Each of the polygons  102  through  112  shown in FIG. 1A constitutes a single value in a database table in which each of the values is represented in a single row. A tabular representation for the polygons shown in FIG. 1A is shown below in Table 1, which shows rows having stored therein information for the polygon shape and other information related to that shape.  
                           TABLE 1                                   geometry   other columns                           polygon1   . . .            polygon2   . . .            polygon3   . . .            polygon4   . . .            polygon5   . . .            polygon6   . . .                       
 
           [0006]    An aggregation of the polygons shown in FIG. 1A can be described by equation 1 set forth below and is shown by shape  114  in FIG. 1B.  
           polygon1 union polygon2 union polygon3 union polygon4 union polygon5 union polygon6  Eq. 1  
           [0007]    In more abstract terms, entities can be combined into an aggregate entity according to the following equation, Eq. 2, set forth below, where v1 . . . vn are values of type t, and op is an operation.  
           v1 op v2 op . . . op vn  Eq.2  
           [0008]    A database system that implements recursive queries as defined in the SQL-99 standard (ISO/IEC 9075-2) provides the facilities to create aggregates. However, such solutions tend to be rather complex as recursion introduces its own set of complexities which are well-known and not described here. An example of the use of recursion to generate an aggregate is illustrated by the SQL-like statements shown in Table 2 below.  
                                                     TABLE 2                                       WITH union_tab(result, row_no) AS (                SELECT geometry, 1           FROM  table           WHERE &lt;first row&gt;           UNION ALL           SELECT union (result, geometry), row_no +1           FROM  table, union_tab           WHERE &lt;next row, based on row_no&gt;)                SELECT geometry           FROM  union_tab           WHERE row_no =( SELECT MAX (row_no)                FROM  union_tab )                      
 
           [0009]    It is well-known how to establish correlations between various rows in a database when using recursive techniques. However, there are several drawbacks to those approaches. First, when using recursion an iteration over the rows is required, so some sort of unique counter is needed. Also, infinite loops can occur when using recursion, which cannot be easily, if at all, detected by the database management system (DBMS). Further, the technique shown in Table 2 is not useable in practice.  
           [0010]    Accordingly, there is a need for user-defined aggregate functions for use with database systems that do not use recursive programming techniques.  
         SUMMARY OF THE INVENTION  
         [0011]    In accordance with an aspect of the present invention, a computer implemented method provides an aggregate of a plurality of entities using a database management system (DBMS) that utilizes a memory external to the database in which the aggregate is constructed. Functions provided by the DBMS are used to construct the aggregate in the memory to provide a result. The result is returned from the memory to the DBMS and a counter is used to detect an identifier of the aggregate&#39;s location in the memory.  
           [0012]    In accordance with a further aspect of the invention, a computer implemented method uses a database management system to successively generate an aggregate of a plurality of entities, wherein input entities are computed with results comprised of a combination of prior input entities to provide a successive aggregated result. An identifier is assigned to each successively aggregated result, and those identifiers include values assigned in ascending order. The identifier having the maximum number, which is indicative of the last combination formed, is identified and whereby the location of the last combination is identified.  
           [0013]    Features and advantages as well as further aspects of the invention will become apparent upon consideration of the following descriptions and descriptive figures of specific embodiments thereof. While these descriptions go into specific details of the invention, it should be understood that variations may and do exist and would be apparent to those skilled in the art based on the descriptions herein. 
       
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0014]    [0014]FIG. 1A depicts a plurality of geometric shapes stored in a database.  
         [0015]    [0015]FIG. 1B shows an aggregate of the geometric shapes shown in FIG. 1A.  
         [0016]    [0016]FIG. 2 is a flowchart illustrating a process for computing an aggregate and obtaining an aggregate result.  
         [0017]    [0017]FIG. 3A shows an embodiment of an aggregate identifier used in the process illustrated in the flowchart of FIG. 2.  
         [0018]    [0018]FIG. 3B shows a storage arrangement for storing the geometric shapes, the aggregate identifiers, and an intermediate aggregate result.  
         [0019]    [0019]FIG. 4 is a block diagram of a computer system suitably configured for operation of the present invention. 
     
    
     DETAILED DESCRIPTION  
       [0020]    The embodiments described below are described with reference to the above drawings, in which like reference numerals designate like components.  
         [0021]    Embodiments of the invention are described here in terms of aggregating geometric shapes. However, the invention is not limited to constructing such aggregates of spatial objects, which are described here only for purposes of illustration. Rather, the invention is broadly applicable to constructing aggregates of entities, which by way of non-limiting example in addition to geometric figures include various types of database records, sets of values or numbers, physical objects, etc.  
         [0022]    A way to write the query shown in Table 2 to obtain exactly the same result, but without using recursion, is described here using two new functions called “ComputeAggregate” and “GetAggregateResults.” Using structured query language (SQL) syntax, the following query shown in Table 3 can be used to obtain the same result that the query in Table 2 produces, but without using recursion.  
                   TABLE 3                           SELECT   GetAggregateResult(MAX(ComputeAggregate(geometry)))       FROM   table                  
 
         [0023]    The query shown in Table 3 constructs the aggregate in memory that is external to a database and exploits the database system&#39;s native aggregate functions (MAX, MIN, . . . ) to keep track of, find and retrieve the final result. The benefits of this approach are, besides greatly improved usability, enhancing performance by avoiding communication needed to construct and transfer intermediate results that are generated, and exploiting the grouping functionality of existing DBMSs, such as the DB® database system marketed by IBM. The query shown in Table 3 includes the two new functions: ComputerAggregate and GetAggregateResults.  
         [0024]    [0024]FIG. 2 shows a flowchart for processing the query shown in Table 3. The flowchart illustrates the use of the functions ComputerAggregate  200  and GetAggregateResult  201 .The first call made to the ComputeAggregate function  200  performs the initialization. That is, it places the identity element for the aggregation operation into the memory area. The “identity element” is, for example, 0 (zero) for addition, 1 (one) for multiplication and an empty set for a union operation. This initialization is depicted in FIG. 2 by operation  202 .  
         [0025]    The function then enters a loop where it builds up an aggregate, keeping the intermediate results generated in each iteration of the loop in a variable stored in memory that is external to the database. Generally, the entities, or in this example, the geometric shapes, to be aggregated are held by the DBMS, most likely in a relational storage structure such as an internal table within the DBMS. The DBMS provides from that table the first entity, or shape, to be processed to the ComputeAggregate function  200 . The ComputeAggregate function then applies the aggregate operation to that entity and then stores an intermediate result produced by applying the aggregation function to the entity, in the variable stored in memory as depicted by operation  204 . The result of the operation becomes the new intermediate result. For the very first entity, this intermediate result will be a value of the entity itself because only the identity element is applied to it, which does not cause any change to the value.  
         [0026]    In the example illustrated in FIG. 2, operation  204  computes the union of the geometric shape produced by the database and stores the computed intermediate result in the variable stored in memory. The first time operation  204  is executed the intermediate result contains the empty set. Accordingly, the union of the first geometric entity and the empty set generates an intermediate result that merely is the first geometric entity.  
         [0027]    Each time an intermediate result is produced it is stored in the variable in memory by the ComputeAggregate function. The location where the intermediate result is stored in memory can change each time through the loop, because of, for example, system storage management features of the computing system such as reallocation of memory spaces, etc. In order to locate the intermediate result in the memory an identifier that indicates the location of that intermediate result is generated and returned to the DBMS. The ComputeAggregate function  200 , in operation  206 , constructs the unique identifier for the intermediate result that was generated in operation  204 . That identifier is then returned to the database system, as indicated in operation  208 . Many database systems store returned values in a sequential manner, such as by storing those returned values in a table. Here, the identifier returned to the DBMS is stored in such a sequential matter, such as in a table, along with other previously returned identifiers.  
         [0028]    An example of such a unique identifier is shown in FIG. 3A, and includes a counter portion  301 , a pointer portion  302 , and an additional information portion  303 . A counter generates a sequential count value for each generated intermediate result. That count value is placed in the counter portion  301  of the unique identifier  300 . The count value uniquely identifies an intermediate result because the counter generates a new sequential count value for each intermediate result that is generated in the loop. The count value identifies that the unique identifier corresponds to the n-th intermediate result. Placing the count value as the first entry in the identifier allows the DBMS to use it as criteria for sorting and filtering the identifiers that are stored by the DBMS. The pointer portion  302  contains a pointer to the location in the memory where the corresponding intermediate result is stored.  
         [0029]    The pointer can include several pieces of information to uniquely identify where the intermediate result can be found. For example, the first piece of pointer information can be a host identifier (machine name) if used in a distributed processing system. The second piece of pointer information can be a process identifier or a shared memory identifier. This is to ensure that the function that returns the final result to the DBMS actually accesses the correct memory area. The third piece of pointer information can be offset into the memory or a structure mapped onto the memory area to identify exactly where the intermediate result can be found. The “additional information” portion  303  of the identifier can include additional information which, if necessary, can be determined on a case by case basis depending on the application.  
         [0030]    [0030]FIG. 3B illustrates data structures that hold the data items used in computing a union of shapes according to the process illustrated in FIG. 2. In FIG. 3B, the DBMS  304  includes a shape table  306  in which the geometric shapes to be processed are held. Each shape is associated with a geometric shape identifier (ID) that identifies the shape. As shown in FIG. 3B, n geometric shapes  306   a  through  306   n  are stored in shape table  306 . When an intermediate result  310  is computed, it is stored in a variable in memory  308 . The variable is associated with a memory address  312 . Since the location of the intermediate result can change due to the dynamics of the computing system, an identifier  300 , as shown in FIG. 3A, is generated for each intermediate result and returned to the DBMS. The DBMS receives the returned identifiers for the intermediate results and stores those identifiers in an identifier table  314 . In FIG. 3B, n identifiers  314   a  through  314   n,  corresponding to n intermediate results, are stored in the identifier table  314 . The pointer field in an identifier points to the location in memory where the intermediate result is located.  
         [0031]    Referring again to FIG. 2, in operation  210  the DBMS determines whether any further geometric shapes are to be processed. That is, the DBMS determines if any further rows in the table holding the geometric shapes remain to be processed in computing the union of shapes. If further geometric shapes remain in the DBMS table that have not been used in computing the union, the DBMS, in operation  212 , passes the next entity to be processed, in this example a geometric shape, to the ComputeAggregate function. The operation is again performed combining the next shape to be processed with the intermediate result, and a new identifier for the now new intermediate result is returned and stored in the DBMS.  
         [0032]    The loop defined by operations  204 ,  206 ,  208 ,  210  and  212  builds up the aggregate in memory. After each identifier is returned to the database system, it is determined if the union of all entities has been computed, as depicted by operation  210 . If not, and one or more entities have yet to be included in the union, the next entity is input as depicted by operation  212 . If, on the other hand, it is determined in operation  210  that no further geometric shapes are to be used in the computation of the union, the DBMS function MAX is applied in operation  214  to find the identifier with the maximum counter value, which corresponds to the last computed intermediate result. The counter is ever-increasing, so the maximum identifier always corresponds to the last computed intermediate result. On the other hand, if the counter had been arranged to count down from some finite number, it is the minimum that would be sought rather than the maximum. It should be understood that the word “maximum” as used herein should be construed as meaning “minimum” if such an alternative arrangement is employed.  
         [0033]    Once the identifier with the maximum count value is determined, the identifier is provided to the GetAggregateResult function  201 . The GetAggregateResult function, using the pointer in the identifier, retrieves the aggregate result from the memory and returns it to the DBMS. As part of that function, the identifier is verified and decomposed into the counter and pointer portions, as depicted in operation  216 . Depending on the information carried in the pointer and/or “additional information” portion of the identifier, additional verifications such as the host name and process ID might be performed. Once the pointer is obtained, the respective memory area is accessed and the final aggregation result is returned to the DBMS, as indicated in operation  211 . The process then returns, in operation  220 , to the calling application.  
         [0034]    It should be understood that while in the preferred embodiment the aggregate is built up by adding one entity at a time, if the database function permits, a union of more than one entity at a time may be effected, and the present invention encompasses such arrangements. Also, while the embodiments described above relate to computing a union of geometric shapes, other combinations of entities stored in a database can be computed using the techniques described here.  
         [0035]    [0035]FIG. 4 is a block diagram of a computer system  400 , suitable for employment of the present invention. System  400  can be implemented on a general-purpose microcomputer, such as one of the members of the IBM Personal Computer family, or other conventional workstation or graphics computer devices, or mainframe computers. In its preferred embodiment, system  400  includes a user interface  417 , a user input device  407 , a display  415 , a printer  420 , a processor  455 , a read only memory (ROM)  450 , a data storage device  122 , such as a hard drive, memory/ 440  such as a random access memory (RAM), and a storage media interface  435 , all of which are coupled to a bus  425  or other communication means for communicating information. Although system  400  is represented herein as a standalone system, it is not limited to such, but instead can be part of a networked system. For example, the computer system  400  may be connected locally or remotely to fixed or removable data storage devices  122  and data transmission devices  445 . Further the computer system  400 , such as the server computer system  102  or the client computer system  104 , also could be connected to other computer systems via the data transmission devices  445 .  
         [0036]    The memory  440 , the data storage device  122  and the ROM  450 , are components of a means  458  that stores data and instructions for controlling the operation of processor  455 , which may be configured as a single processor or as a plurality of processors. The processor  455  executes a program  442  recorded in one of the computer-readable storage media described above, to perform the methods of the present invention, as described herein.  
         [0037]    While the program  442  is indicated as loaded into the RAM  440 , it may be configured on a storage media  430  for subsequent loading into the data storage device  122 , the ROM  450 , or the RAM  440  via an appropriate storage media interface  435 . Storage media  430  can be any conventional storage media such as a magnetic tape, an optical storage media, a compact disk, or a floppy disk. Alternatively, storage media  430  can be a random access memory  440 , or other type of electronic storage, located on a remote storage system. The term “memory” herein in which the aggregate is built up typically refers to a non-persistent memory such as a random access memory (RAM)  440  although persistent memory also can be used. Other memory devices described herein can also be used, although access time may be increased.  
         [0038]    Generally, the computer programs and operating systems are all tangibly embodied in a computer-readable device or media, such as the memory  458 , the data storage device  122 , or the data transmission devices  445 , thereby making an article of manufacture, such as a computer program product. As such, the terms “computer program product” as used herein are intended to encompass a computer program  442  accessible from any computer readable device or media.  
         [0039]    Moreover, the computer programs  442  and operating systems are comprised of instructions which, when read and executed by the computer system  400 , cause the computer system  400  to perform the steps necessary to implement and use the methods and systems described here. Under control of the operating system, the computer programs  442  may be loaded from the memory  458 , the data storage device  122 , or the data transmission devices  445  into the memories  458  of the computer system  400  for use during actual operations. Those skilled in the art will recognize many modifications may be made to this configuration without departing from the scope of the present invention.  
         [0040]    The user interface  417  is an input device, such as a keyboard or speech recognition subsystem, for enabling a user to communicate information and command selections to the processor  455 . The user can observe information generated by the system  400  via the display  415  or the printer  420 . The user input device  407  is a device such as a mouse, track-ball, or joy-stick, which allows the user to manipulate a cursor on the display  415  for communicating additional information and command selections to the processor  455 .  
         [0041]    The methods and systems described here are typically implemented using one or more computer programs  442 , each of which is executed under the control of an operating system and causes the system  400  to perform the desired functions as described herein. Thus, using the present specification, the invention may be implemented as a machine, process, method, system, or article of manufacture by using standard programming and engineering techniques to produce software, firmware, hardware or any combination thereof.  
         [0042]    Having described apparatuses, articles of manufacture and methods of manipulating information contained in a database system, it is believed that other modifications, variations and changes will be suggested to those skilled in the art in view of the teachings set forth herein. It is therefore to be understood that all such variations, modifications and changes are believed to fall within the scope of the present invention as defined by the appended claims. Although specific terms are employed herein, they are used in their ordinary and accustomed manner only, unless expressly defined differently herein, and not for purposes of limitation.  
       Trademarks  
       [0043]    IBM is a trademark or registered trademark of International Business Machines, Corporation in the United States and other countries.  
         [0044]    DB2 is a trademark or registered trademark of International Business Machines, Corporation in the United States and other countries.