Abstract:
A database reorganization technique uses multiple-coordinated read, sort and write tasks to substantially reduce the overall time to reorganize a database object. Coordination between the different functional tasks (e.g., read, sort and write tasks) is facilitated through the logical partitioning of the key values associated with the object to be reorganized. Object key values are determined by interrogating the object&#39;s associated database prior to initiating reorganization processing.

Description:
BACKGROUND 
     The invention relates generally to computer database systems and more particularly, but not by way of limitation, to methods and devices for reorganizing database files. 
     Databases may be characterized as comprising two types of “objects”—data objects and index objects. Both data and index objects are typically embodied as files stored on one or more direct access storage devices (DASDs). The process of reorganizing a database, then, generally involves reading a database object (“unloading”), passing the data to a sort utility that reorders (sorts) the data in accordance with a specified sort key and writing the data back to the object in a new sequence determined by the sort key (“reloading”). The needs for sorting are many and varied and are well-known to those of ordinary skill in the art of database system use and design. For example, periodic sorting of database objects can improve a user&#39;s response time during database search and retrieval operations. 
     A typical prior art technique for sorting a database object is shown in  FIG. 1 . Initially, prior art reorganization process  100  interrogates the targeted database to determine various structural and logical details needed to inform the sort operation (block  105 ). Illustrative details include, for example, the locations and names of the files in which the database data is physically stored and the identification and location of the sort key(s) within the targeted data. Next, reorganization process  100  obtains data records from the target database (block  110 ) and passes them to a sort routine (block  115 ). If additional records remain to be read from the target database (the “NO” prong of block  120 ), the acts of blocks  110  and  115  are repeated. If no additional records remain to be read (the “YES” prong of block  120 ), the sorted records are written back to the target database in their new (sorted) sequence (block  125 ). Following completion of write-back operations in accordance with block  125 , the reorganization routine terminates (block  130 ). 
     One significant drawback to prior art database reorganization techniques is that for large databases consisting of hundreds of gigabytes to tens of terabytes, the time required to perform the read and write-back operations (e.g., blocks  110  and  125  in  FIG. 1 ) can be significant. Thus, it would be beneficial to provide a technique to reorganize database objects that is more time efficient than current techniques. 
     SUMMARY 
     In one embodiment, the invention provides a method to reorganize a database object using multiple coordinated read, sort and write tasks. The method includes determining a key range for a database object, identifying two or more logical partitions for the database object (where each partition is associated with a different section of the determined key range), initiating a plurality of read tasks (where each read task is associated with a different physical portion of the database object), initiating a plurality of sort tasks (where each sort task is associated with at least one of the partitions) and initiating one or more write tasks for reloading the reorganized database object. Each read task obtains information having a key value (generically referred to as “data”) from its associated portion of the database object and provides the data to that sort task associated with that partition that includes the key value. After the data is obtained and sorted, the one or more write tasks reload the sorted data back to the database. Methods in accordance with the invention may be used to reorganize an entire database, one object within a database (data or index) or two or more objects within a database (any combination of data and index objects). Methods in accordance with the invention may be stored in any media that is readable and executable by a programmable control device. In another embodiment, the invention provides a device for performing a database reorganization. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a prior art database reorganization technique. 
         FIG. 2  illustrates, in flowchart form, one embodiment of a database reorganization process in accordance with the invention. 
         FIG. 3  illustrates, in flowchart form, another embodiment of a database reorganization process in accordance with the invention. 
         FIG. 4  illustrates, in flowchart form, a feature of the embodiment of  FIG. 3 . 
     
    
    
     DETAILED DESCRIPTION 
     The invention relates generally to computer database systems and more particularly, but not by way of limitation, to methods and devices for reorganizing database files. Techniques in accordance with the invention use multiple, coordinated, read, sort and write tasks to unload, sort and reload a target database object. One benefit of a reorganization process in accordance with the invention is that it provides a substantial reduction in the start-to-finish time required to reorganize a database compared with prior art techniques. 
     Referring to  FIG. 2 , reorganization process  200  in accordance with the invention can be used to reorganize one object within a database (e.g., a data object or an index object) or multiple objects within a database. Initially, reorganization process  200  interrogates a target database to obtain process control information for the object to be reorganized (block  205 ). For example, reorganization process  200  may query the target database&#39;s catalog to determine the structure of the object to be reorganized, the identity of fields within the stored object and which fields are indexed, the size and location of the stored data on DASD and an indication of the range of primary key values associated with the stored object. In addition, if the object being reorganized is a data object and not an index object, reorganization process  200  may also query the object&#39;s associated index object to obtain a more accurate indication of the range of primary key values associated with the stored data. 
     The database object to be reorganized is then logically divided into ‘N’ partitions based on the range of primary key values determined during the acts of block  205 , where each partition includes a contiguous range of key values (block  210 ). For example, if the database object&#39;s primary key range is determined to be 000 to 999 and ‘N’ is two (2), a first partition may be defined by the 000-499 range of primary key values and a second partition may be defined by the 500-999 primary key values. Similarly, if ‘N’ equals four (4), partitions may be defined by the primary key value ranges of 000-249, 250-499, 500-749 and 750-999. 
     Once logically partitioned, two or more read tasks are initiated (block  215 ), where each read task is assigned to read a different portion of the object being reorganized (block  220 ). For example, if the acts of block  205  indicate the database object being reorganized is 100 Gigabytes (GB) in size and two (2) read tasks are initiated, then a first read task may be assigned to read from the “first” 50 GB of the object and a second read task may be assigned to read from the “second” 50 GB of the object. One of ordinary skill in the art will recognize that the acts of block  205 , inter alia, identify the (likely, discontinuous) starting and stopping locations or addresses of the targeted object on DASD. Accordingly, the acts of block  220  assign each read task initiated in accordance with block  215  a different portion of the object from which to obtain information (e.g., “data” or ‘index’ information). 
     In addition, two or more sort tasks are initiated (block  225 ), where each sort task is associated with a different logical partition (block  230 ). For example, if the acts of block  210  divide the target data object&#39;s key range into two (2) partitions and two (2) sort tasks are initiated in accordance with block  225 , the first sort task may be assigned to sort data (or indices) having key values included in the first partition and the second sort task may be assigned to sort data (or indices) having key values included in the second logical partition. Hereinafter, unless expressly noted otherwise, the term “data” includes both stored object data (i.e., information stored by a user) and stored index information. 
     Once initiated, read tasks obtain data from their assigned portion of an object (typically one record at a time) and pass the obtained data to the appropriate sort routine which then sorts its (block  235 ). For example, if a first read task reads a record from its assigned portion of the object and determines that the record&#39;s key value is XYZ, the read task will communicate that record to the sort task associated with the key range that includes the value XYZ. 
     After each read task has read all the records within its assigned portion of the object and passed those records to the appropriate sort routine, reorganization process  200  initiates one or more write tasks (block  240 ) to write-back or “reload” the sorted records to the target object (block  245 ). 
     On completion of the write-back process of block  245 , reorganization process  200  may perform certain cleanup operations (block  250 ) prior to termination (block  255 ). Illustrative cleanup operations include, but are not limited to, releasing any access locks and closing all files associated with the target database object and/or database. In one embodiment, for example, if the object reorganized is a data (not an index) object, cleanup operations in accordance with block  250  may update the data object&#39;s associated index object to reflect its now-reorganized state. 
     Determination of an optimal or beneficial number of read, sort and write tasks to initiate in accordance with blocks  215 ,  225  and  240  requires precise knowledge of the user&#39;s computational environment. In particular, resources such as the amount of memory available for the reorganization process (volatile and nonvolatile), the number and speed of access paths to the data being reorganized and the particular overhead associated with running cooperating tasks or processes within a given environment must be considered. Tradeoffs between these factors will inform the decision maker as to how many of each task (read, sort and write) should be selected to optimize the reorganization process (e.g., minimize start-to-finish reorganization time). While complex, this task is within the ability of those having ordinary skill in the art of database system design, management and administration. 
     It is noted that the number of read, sort and write tasks initiated in accordance with the invention are independent of one another. Thus, in one embodiment the number of read tasks and the number of sort tasks are equal, with one sort task associated with each logical partition. In other embodiments, there are more or fewer read tasks than sort tasks, and more or fewer sort tasks than logical partitions. Similarly, the number of write tasks may be equal to, less than or greater than the number of sort tasks. It has been found that in some environments, matching the number of sort tasks and the number of write tasks (that is, associating one write task to one sort task during the operations of block  245 ) reduces DASD write-back conflicts. 
     One of ordinary skill in the art will recognize that the use of multiple read, sort and write tasks coordinated through the logical partition of a target data object&#39;s key range provides numerous advantages over prior art reorganization techniques. For example, the use of multiple coordinated read tasks can reduce the amount of time required to “unload” a target database object. Similarly, the use of multiple coordinated write tasks can reduce the amount of time required to “reload” the target database object once reorganized. It will further be recognized that use of multiple sort tasks, each associated with a unique range of data object key values, allows reorganization techniques in accordance with the invention to conveniently and efficiently distribute and coordinate the work performed by each of the multiple read and write tasks. 
     A specific embodiment of the invention directed to reorganizing a DB2® data object is shown in  FIG. 3 . (DB2 is a registered trademark of the International Business Machines corporation of Armonk, N.Y.) In the illustrated embodiment, reorganization process  300  interrogates DB2 database  305  on DASD  310  to identify the name, location and the range of primary key values (the “key range”) associated with the data object to be reorganized (block  315 ). Next, the determined key range is divided into two (2) partitions with each partition associated with a continuous range of key values (block  320 ). For example, partition 1 may be associated with key values in the lower half of the determined key range, while partition 2 may be associated with key values in the upper half of the determined key range. Two read tasks are then initiated with each assigned a different portion of the data object. For example, if the target data object is determined (during the acts of block  315 ) to comprise 96 GB of data, 48 GB of this data may be assigned to each of the two read tasks. 
     Once initiated, each read task opens its assigned portion of the data object (blocks  325   a  and  325   b ), reads a single record (blocks  330   a  and  330   b ) and passes the record to the appropriate sort routine (blocks  335   a  and  335   b )—that sort routine associated with the partition including the key value of the record. These actions are repeated until each read task has exhausted the records stored in its assigned portion of the data object (see blocks  340   a  and  340   b ). Sorted data are written back (i.e., “reloaded”) into database  305  on completion of all sort operations (blocks  345   a  and  345   b ). In one embodiment, each sort task informs its associated write task how much space is required to store its sorted data records. In another embodiment, each read task informs the write tasks of the number of records it sent to each sort task and, based on an average record size, each write task can determine the approximate amount of DASD storage it needs. In either case, the write tasks reload the sorted data into database  305 . Substantially concurrent with the write-back operation, write tasks may also update the index object in database  305  for the data object being reorganized (see blocks  345   a  and  345   b ). On completion of the write-back operation, reorganization process  300  terminates (block  350 ). 
     Referring now to  FIG. 4 , each read task initiated by the process of  FIG. 3  will generally have a buffer for each initiated sort task. Accordingly, during operation a read task reads a record from database  305  (blocks  330   a  and  330   b ), determines which sort task it should go to (blocks  400   a  and  400   b ) and places the record in the appropriate buffer ( 405   a ,  410   a ,  405   b  and  410   b ). Records are transferred from a read tasks&#39; buffers to the appropriate sort tasks ( 415   a  and  415   b ) only when a buffer is filled or when the read task completes reading records from its assigned portion of the data object. Within the context of large database management systems and, DB2 in particular, it will be recognized by those of ordinary skill in the art that E15 exit programs may be used to pass data into a sort task and that E35 exit programs may be used to pass data from a sort task to a write task. 
     It will be recognized and understood that many modern databases such as DB2 may be “partitioned,” which is to say that data associated with key ranges may be located in different data sets. The present invention treats each such partition as an independent object. Thus, partitions in accordance with the invention may or may not match the partitioning of a data object as used in contemporary databases such as, for example, DB2. 
     While the embodiments described herein have assumed the object being reorganized resided on a single DASD, the invention is not so limited. For example, a target object may span a number of different storage media and may further be distributed to physically disparate locations. 
     Various changes in the details of the illustrated operational methods are possible without departing from the scope of the following claims. For instance, acts in accordance with  FIGS. 2-4  may be performed in an altered order and/or embodied in program instructions for execution by a programmable control device. A programmable control device may be a single computer processor, a plurality of computer processors coupled by a communications link, or a custom designed state machine. Storage devices suitable for tangibly embodying program instructions include, but not limited to: magnetic disks (fixed, floppy, and removable) and tape; optical media such as CD-ROM disks; and semiconductor memory devices such as Electrically Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Programmable Gate Arrays and flash devices. 
     While the invention has been disclosed with respect to a limited number of embodiments, numerous modifications and variations will be appreciated by those skilled in the art. It is intended, therefore, that the following claims cover all such modifications and variations that may fall within the true sprit and scope of the invention.