Patent Abstract:
The present system indexes a plurality of entries in a database that contains a database table having a base index. As a recent row is inserted in the database table, an index increment is generated based on the inserted row. Preferably, the index increment is smaller in size than the base index because it is recently generated. The smaller size of the index increment facilitates the management of the index increment. An index entry associated with the inserted row is added to the index increment, and the index increment is merged with the base index.

Full Description:
PRIORITY CLAIM 
   The present application claims the priority of European patent application, Serial No. 05100168.3, titled “Incremental Indexing,” which was filed on Jan. 13, 2005, and which is incorporated herein by reference. 
   FIELD OF THE INVENTION 
   The present invention generally relates to the field of updating a database, and it particularly relates to managing indexes upon insertion of data rows. 
   BACKGROUND OF THE INVENTION 
   Computer databases are a common mechanism for storing information on computer systems while providing easy access to users. A typical database is an organized collection of related information stored as rows having fields of information. As an example, a database of employees may have a row for each employee comprising different columns or fields such as name, department, phone number, salary, etc. Rows are organized in a table, a two-dimensional structure with rows indicating the rows having fields of information and columns indicating the fields. 
   To speed up access to the data of the database table, rows can be indexed and the index entered into a base index. For example, one index can indicate where to find the rows containing a particular name, another index can indicate where to find the rows containing specific departments. 
   To allow for complete responses to queries, each time the database is updated by inserting a new row, the index or indexes are also updated; i.e., a corresponding entry is inserted in the index. 
   Rows and indexes are physically stored on storage media such as tape or disk. When taking any action on the database such as processing a query, inserting a new row, indexing a new row, etc., the corresponding data is retrieved from the storage medium into a cache. The database management system performs actions on the data while the data is in the cache. 
   In large databases, the index is also large. Consequently, new entries are time consuming. This is particularly a problem if the index is larger than the cache such that many storage medium reads are necessary for updating the index. 
   What is therefore needed is a system, a computer program product, and a method for indexing incrementally to enhance the inserting performance of a database. The need for this solution has heretofore remained unsatisfied. 
   SUMMARY OF THE INVENTION 
   The present invention satisfies this need, and presents a system, a computer program product, and an associated method (collectively referred to herein as “the system” or “the present system”) for incremental indexing upon insertion of data rows in a database. 
   According to a preferred embodiment of the present invention, a database management system manages a database that stores a database table containing data pages. Each data page is capable of storing data rows. The data rows store information organized into particular columns. The database table has a base index for logically ordering the data rows. The base index comprises index entries wherein each data row is referenced by a corresponding index entry. The present system comprises a method for indexing the database comprises inserting a row, generating an index increment, making an index entry associated with the row into the index increment, and merging the index increment with the base index. 
   If the database is updated by inserting a new row, the indexing is performed immediately, to provide correct access to all information. However, the present system does not perform the indexing in the base index. Rather, the present system generates an index increment and performs the corresponding index entry in the index increment instead of the base index. The present system merges the index increment with the base index. 
   The index increment is typically smaller than the base index because it is newly generated. The small size of the index increment facilitates management of the index increment. The place at which to enter the new index entry is found much faster than when searching the entire base index for an entry place. The merger of the index increment and base index can be timed such that the performance of the database management system is not impeded by the merger. If a query is submitted before the index increment and base index have been merged, the incremental index and the base index are scanned. Consequently, correct access to information is provided. 
   When more than one row is inserted, index entries concerning the rows are made into the index increment and the merging is performed after rows have been inserted and indexed. In cases where a plurality of rows is inserted, the gain in speed by indexing into an index increment instead of the base index is especially high. 
   Furthermore, the present system can insert more than one row and generate more than one index increment. This is especially convenient if large amounts of rows are inserted that would otherwise lead to too large an index increment, thus leading again to a decrease in speed of the indexing. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The various features of the present invention and the manner of attaining them will be described in greater detail with reference to the following description, claims, and drawings, wherein reference numerals are reused, where appropriate, to indicate a correspondence between the referenced items, and wherein: 
       FIG. 1  schematically illustrates a conventional database management system; 
       FIG. 2  comprises  FIGS. 2A and 2B  and schematically illustrates conventional indexing; 
       FIG. 3  schematically illustrates indexing according to the present invention; 
       FIG. 4  comprises  FIGS. 4A ,  4 B,  4 C, and  4 D and schematically illustrates a database management system according to the present invention; 
       FIG. 5  is a process flowchart illustrating a method for insert processing; 
       FIG. 6  is a process flowchart illustrating a method for building incremental indexes; 
       FIG. 7  is a process flowchart illustrating a method for query processing; 
       FIG. 8  is a process flowchart illustrating a method for implicit merging of incremental indexes; and 
       FIG. 9  is a process flowchart illustrating a method for explicit merging of incremental indexes. 
   

   DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
     FIG. 1  illustrates schematically a conventional database management system  1 . The conventional database management system  1  may be implemented, for example, as computer with an appropriate computer program product running on it. The computer may be a stand-alone device or be a member of a network with servers and clients. 
   The conventional database management system  1  comprises a relational data system  10 , a data and index manager  11 , and a cache manager  12 . The conventional database management system  1  interacts with an application program  2  or interactive user that generates database requests such as, for example, SQL statements. These SQL statements may be, for example, “insert” or “non-insert” statements, such as “read”, “select”, “delete”, etc. and result in retrieval or modifications of the stored data. The database requests such as SQL statements are processed by various components, such as the relational data system  10 , the data and index manager  11 , or the cache manager  12  and result in retrieval or modification of the data stored in a storage media subsystem such as a media manager  3  or storage media  4 . 
   In particular, the database requests are processed by an insert-processing module  110  for insert requests and by a non-insert processing module  111  for non-insert requests. The insert processing module  110  and the non-insert processing module  111  are components of the data and index manager  11 . In response to the database requests, e.g. SQL statements from the application program  2 , the conventional database management system  1  returns information on rows of a database table and status information. The conventional database management system  1  may also receive information on rows to add. 
   Data such as the content of a database table and a base index is stored on the storage media  4 . The storage media  4  comprises media such as, for example, disks or tapes. To store and retrieve data, the conventional database management system  1  uses the cache manager  12 . The cache manager  12  manages the cache  120 . The cache  120  is, for example, arranged as buffer pools. The cache manager  12  communicates with the media manager  3  by sending read or write pages requests and by receiving data and index pages. Pages (further referenced herein as blocks or physical blocks) are entities corresponding to the physical blocks of the storage media containing the data of the database. The media manager  3  provides pages by communicating with the storage media  4  via I/O programs addressing the physical blocks. 
   The relational data system  10  is arranged to perform tasks such as parsing, optimizing, predicate evaluation etc. 
   The database structure is illustrated in  FIG. 2  ( FIGS. 2A ,  2 B). There are shown a database table  20  where new data is entered as inserted database table rows such as, for example, row A,  201 , row B,  202 , and row C,  203 , (collectively referenced as rows  201 ,  202 ,  203 ) with information of various categories arranged in columns. A base index  21  of the database table  20  is organized as a tree. 
   For each of the inserted rows  201 ,  202 ,  203 , the base index  21  requires updating. An index update comprises adding an index entry such as, for example, an index entry A,  211 , an index entry B,  212 , an index entry C,  213 , (collectively referenced as entries  211 ,  212 ,  213 ) pointing to the respective rows  201 ,  202 ,  203 . Entries  211 ,  212 ,  213  are added into the base index  21  at an appropriate position determined by the index tree structure and the index key value. Only in the case of ever increasing key values, the inserted index entries are added at the end of the index resulting in no or few reads from the storage media. However, in general, an index entry requires insertion in a random fashion. Consequently, a large probability exists that the target index page is not in the database cache, resulting in a synchronous read from the storage media and, thus, a slow-down of the indexing process. 
   In  FIG. 2A , only one index  21  is illustrated. Usually, there are a multitude of further indexes indexing the database table  20  depending on different criteria.  FIG. 2B  illustrates indexes such as, for example, the base index  21 , a base index A,  22 , and a base index B,  23  (collectively referenced as indexes  21 ,  22 ,  23 ). The indexes  21 ,  22 ,  23 , each index the database table  20  according to a different column. Each of the indexes  21 ,  22 ,  23  requires updating if a row insert occurs. 
   If the conventional database management system  1  is implemented as a parallel database, i.e. a group of database systems managing the same data, the indexes require maintenance by all involved systems, adding an additional overhead due to contention of the indexes. 
   For each additional index there is an additional synchronous read, implying a large read wait time that results in overall insert performance degradation. Indexing is a performance booster for query processing and is further a choice for tuning query performance. The queries run in parallel with insert processing, so the indexes are required to exist all the time to provide access to the data. 
   In a special mode of operation, completion of massive insert processing is required in a given time interval. Furthermore, critical query processing must run concurrently on the same data, including newly inserted rows, with best possible performance. This is a common case because many applications include massive insert processing, usually concentrated at some period-closing times: end of the day, week, month, year, etc. These processes regularly require completion in a given time window, as subsequent business operations depend on the results of the processes. As the insert processing runs, the queries accessing the same data require good performance. For that good performance, the queries require access to the very indexes that are being updated and causing slow down of the insert operations. 
   An embodiment of the database management system according to the invention, a database management system  305 , is schematically illustrated in  FIG. 3 . The database management system  305  may be implemented, for example, as computer with an appropriate computer program product running on it. The computer may be a stand-alone device or be a member of a network with servers and clients. The database management system  305  comprises a modified data and index manager  310 . The modified data and index manager  310  comprises a modified insert processing module  315  and a modified non-insert processing module  320 . The modified data and index manager  310  further comprises an index increment building module  325  and an index increment merging module  330 . The insert processing module  315  and the non-insert processing module  320  are modified to efficiently cooperate with the index increment building module  325  and the index increment merging module  330 . 
   The insert processing of the modified data and index manager  310  is enhanced to insert index entries into an index increment rather than a base index. For non-insert operations, such as SQL queries, the modified data and index manager  310  accesses index entries from the base index and from the index increments. 
   The index increment building module  325  generates one or more index increments for inserting index entries corresponding to data rows being inserted into a database table. The index increment merging module  330  merges the one or more index increments with the one or more base indexes after the new data rows have been inserted. The index increment building module  325  and the index increment merging module  330  may be, for example, implemented as computer program product comprising computer programming code adapted to perform these tasks. The index increment building module  325  and the index increment merging module  330  comprise a software programming code or a computer program product that is typically embedded within, or installed on a computer. Alternatively, the index increment building module  325  and the index increment merging module  330  can be saved on a suitable storage medium such as a diskette, a CD, a hard drive, or like devices. 
   The modified insert processing module  315  inserts index entries into an index increment rather than in a base index, if an index increment exists. The non-insert processing module  320  looks up data one or more base indexes and in one or more index increments to process queries or delete data. 
     FIG. 4  ( FIGS. 4A ,  4 B,  4 C,  4 D) schematically illustrates the indexing process according to the modified data and index manager  310 . Once a pattern of massive inserts is detected, a new index tree, i.e. an index increment  45  is spawned for a base index  41  that exists on a database table  40  (see  FIG. 4A ). With incremental indexing provided by the modified data and index manager  310 , each database system can maintain its “own” index increments for each non-partitioning index. This isolation is complete, thus resulting in drastic reduction of cost of sharing data. 
   The data table  40  is illustrated with new data rows such as, for example, a row  1 ,  401 , a row  2 ,  402 , and a row  3 ,  403  (collectively referenced as rows  401 ,  402 ,  403 ). By using the index increment  45  for indexing the newly inserted rows  401 ,  402 ,  403 , a much smaller index tree requires updating. Updating starts with a single page only (equivalent of one physical block of storage space) and grows with new inserts. The likelihood of target index pages being cached is much higher than in the case of updating a large monolithic base index. 
     FIG. 4B  illustrates how a query is processed during incremental indexing or before the index increment  45  has been merged with the base index  41 . The query processing, in the present example “select”, takes into account that a chosen index is not necessarily monolithic, but could have one or more increments. Thus, the base index  41  and the index increment  45  are scanned for the rows to be selected. In general, scanning the base index  41  and the index increment  45  increase in the cost of index scan can be minimized if parallel index scan is implemented. This increase in cost is offset many times by superior insert performance. The scan of the active index increment  45 , i.e. the index increment  45  being inserted at the time, is likely to complete without any read from the storage medium, as the concerned pages are likely cached. 
   The index increment  45  is merged with the base index  41  after insertion of one or more rows  401 ,  402 ,  403 . The actual time for merging can be determined automatically or merging can explicitly started by a user. The merging time is selected to minimize impeding other processes such as, for example, queries. 
   As illustrated in  FIG. 4C , incremental indexing can be adapted to additional base indexes such as, for example, the base index  41 , a base index A,  42 , and a base index B,  43  (collectively referenced as base indexes  41 ,  42 ,  43 ). Each of the base indexes  41 ,  42 ,  43 , index the database table  40  according to different criteria. As illustrated in  FIG. 4C , an incremental index such as, for example, the index increment  45 , an index increment A,  46 , and an index increment B,  47  (collectively referenced as index increments  45 ,  46 ,  47 ) is generated for each of the base indexes  41 ,  42 ,  43 , when rows  401 ,  402 ,  403  are inserted. Accordingly, if a query is to be processed, for example “select”, the base indexes  41 ,  42 ,  43  and associated index increments  45 ,  46 ,  47  are scanned. 
   As illustrated in  FIG. 4D , one or more index increments such as, for example, the index increment  45 , an index increment C,  48 , and an index increment D,  49  (collectively referenced as index increments  45 ,  48 ,  49 ) are provided per base index such as the base index  41 . For example, inserting may occur in several batches before merging. Consequently, separate index increments  45 ,  48 ,  49 , can be generated for each batch. If separate index increments  45 ,  48 ,  49 , are generated, an index increment too large to be memory-resident or cache-resident is avoided. In the example illustrated in  FIG. 4D , prior inserts to the database table  40  are indexed in the index increment  45  and the index increment C,  48 . A present insert of row  404  is indexed in an active index increment represented as the index increment D,  49 . 
   The concept of more than one index increment can be adapted to additional indexes. Index increments such as the index increment  45  and the index increment C,  48 , can be merged with the base index  41  while the index increment D,  49  is active. 
     FIG. 5  illustrates a flowchart illustrating insert processing (step  501 ). A new row is inserted into a database table (step  503 ). For updating the base indexes, the modified insert processing module determines, for each base index (step  511 ), whether there are any index increments (step  505 ). If index increments exists, the index entry is inserted into the most recent index increment associated with the base index (step  507 ). Otherwise, the index entry in inserted into the base index (step  509 ). If now additional base indexes remain for processing (step  511 ), insert processing ends (step  513 ). 
     FIG. 6  illustrates a flowchart illustrating the process of building index increments as response to an insert statement (step  601 ). If a mass insert pattern is explicitly specified (e.g., by a setting on a specific session variable), or automatically detected (e.g., by monitoring the insert rate over a specified time interval) (step  603 ), the possibility of generating an index increment is considered. The index increment is not generated if one or more index increments already exist (step  605 ) or if the most recent index increment is small enough to be memory or cache resident (step  607 ). Otherwise, the index increment building module  325  creates a new index increment (step  609 ). This process is repeated for every index except for ever-increasing key indexes in non-data sharing environments (see step  609 ). After generating an index increment, the insert processing as explained in  FIG. 5  is continued (step  611 ). 
     FIG. 7  illustrates a flowchart illustrating a process of the modified non-insert processing module  320  with reference to the example of a query. In processing a query (step  701 ), the modified non-insert processing module  320  determines whether an index is to be used (step  703 ). Whenever the query uses an index to access the data, the modified non-insert processing module  320  determines whether there are index increments for each of the indexes (step  705 ). If there are index increments, the base indexes and the index increments are scanned (step  707 ). Scanning can be performed serially or in parallel. If there are no index increments, only the base indexes are scanned (step  709 ). Depending on the result of the index scans, the data is scanned and retrieved (step  711 ) and returned to the application program  2 , thus ending the query (step  713 ). 
   The query process takes into account that a chosen index is not necessarily monolithic, but may have one or more increments. In general, this will increase the cost of index scan, which can be minimized if parallel index scan is implemented. However the cost of the index scan is offset many times by superior insert performance. The scan of the active index scan, i.e. the one being updated at the time, is likely to complete without any read from the storage media, because these pages are likely cached. 
     FIGS. 8 and 9  illustrate flowcharts illustrating the merging of index increments with the base index. As illustrated in  FIG. 8 , the merge can be initiated implicitly (step  801 ), for example by a system agent that runs in the background and checks for some criteria indicating that merging is due. A possible criterion is, for example, the number of index increments (step  803 ) or a size of the index increments (step  805 ). Possible criteria further comprise an overall query response time or any other indicator. 
   As illustrated in  FIG. 9 , the merge can as well be initiated explicitly on administrator request (step  901 ). 
   Once the merge has been initiated, a check whether the merge process is already going on is performed (steps  807 ,  903 ). If yes, an appropriate message will be returned and no further action will be performed (steps  815 ,  911 ). If no, a check whether mass insert processing is currently running is performed (steps  809 ,  905 ). As merging during that process can be disruptive, the base indexes and the index increments excluding a most recent index increment are merged (steps  811 ,  907 ). If there is no mass insert processing occurring, the base index is merged with all index increments to create a new base index (steps  813 ,  909 ). 
   The step of merging may be performed according to any method known to a person skilled in the art, such as reorganization or rebuilding. To simplify processing and improve query performance, the merging process occurs before a next mass insert process to avoid creating more than one index increment per base index. 
   The methods of the modified data and index manager  310 , as described with reference to  FIGS. 5 to 9 , may be readily modified to account for multiple indexes. 
   It is to be understood that the specific embodiments of the invention that have been described are merely illustrative of certain applications of the principle of the present invention. Numerous modifications may be made to the present invention described herein without departing from the spirit and scope of the present invention.

Technology Classification (CPC): 6