Selection of a set of optimal n-grams for indexing string data in a DBMS system under space constraints introduced by the system

• US 7,478,081 B2
• Filed: 11/05/2004
• Issued: 01/13/2009
• Est. Priority Date: 11/05/2004
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mehrotra, Sharad, Hacigumus, Vahit Hakan, Iyer, Balakrishna Raghavendra
• Primary Examiner(s): Saeed; Usmaan
• Application Number:
  US10/981,895
• Publication Number:
  US 20060101000A1
• Time in Patent Office: 1,530 Days
• Field of Search: 707 2- 7, 707100-102
• US Class Current: 1/1
• CPC Class Codes: G06F 16/316 Indexing structures
• CPC Class Codes: G06F 16/322 Trees
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99937 Sorting
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

The present invention provides a computer-readable medium and system for selecting a set of n-grams for indexing string data in a DBMS system. Aspects of the invention include providing a set of candidate n-grams, each n-gram comprising a sequence of characters; identifying sample queries having character strings containing the candidate n-grams; and based on the set of candidate n-grams, the sample queries, database records, and an n-gram space constraint, automatically selecting, given the space constraint, a minimal set of an n-grams from the set of candidate n-grams that minimizes the number of false hits for the set of sample queries had the sample queries been executed against the database records.

Claims

1. A method for selecting a set of n-grams for indexing string data in a database management system (DBMS) in relation to resources available to the DBMS, comprising:

providing a set of candidate n-grams, each n-gram comprising a sequence of characters;

receiving an n-gram space constraint to define an amount “

k”

of the set of candidate n-grams eligible for a minimal set of n-grams, the n-gram space constraint based on resources available to the DBMS;

comparing each of the candidate n-grams from the provided set of candidate n-grams with sample queries and database records to determine a benefit associated with the candidate n-grams in reducing false hits;

selecting the minimal set of n-grams, the minimal set of n-grams having a highest total benefit and being subject to the n-gram space constraint;

selecting an updated minimal set of n-grams responsive to receiving an updated n-gram space constraint, the updated minimal set of n-grams having a highest total benefit and being subject to the updated n-gram space constraint, wherein the updated minimal set of n-grams consists of no more than “

k”

n-grams; and

,

generating an index, based on the minimal set of selected n-grams or the updated minimal set of n-grams, that indexes string data contained in the database records.

2. The method of claim 1, further including:

using the index to service incoming queries.

3. The method of claim 1 wherein the n-gram selection is a problem that is NP-hard, the method further including:

formulating n-gram selection as a graph model, and solving the problem using an approximation algorithm.

4. The method of claim 3 further including:

providing the approximation algorithm with a provable ratio bound of an optimal solution to the n-gram selection problem.

5. The method of claim 3 further including:

implementing the approximation algorithm as a utility of the DBMS.

6. The method of claim 1 wherein the DBMS is a SQL-based DBMS, further including:

identifying SQL “

LIKE”

queries containing the candidate n-grams.

7. A method for selecting a set of n-grams for indexing string data in a database management system (DBMS), wherein the DBMS includes a set of candidate n-grams, a set of sample queries, a set of database records, and an input space constraint ‘

k’

related to resources allocated to the DBMS, the method comprising;

a) determining for each sample query from the set of sample queries, which n-grams in the candidate set are a substring of the sample query, and in response, forming a connection between the sample query and the n-gram;

b) determining for each database record from the set of database records, which n-grams do not exist as a substring of the database record, and in response forming a connection between the database record and the n-gram;

c) receiving the input space constraint ‘

k’

the input space constraint ‘

k’

directly related to resources allocated to the DBMS;

d) calculating a benefit of each n-gram in the candidate set, wherein the benefit of each n-gram is computed as a number of previously uncovered connections between the queries and the database records that are made through the n-gram, wherein a connection made through an n-gram between a query and a database record comprises a query-record pair;

e) identifying the n-gram with the highest computed benefit, and storing the identified n-gram in a selected n-gram set;

f) recomputing the benefits of remaining n-grams in the candidate set by performing steps d) and (e) ‘

k’

times, thereby resulting in the selected n-gram set having ‘

k’

n-grams, such that the number of query-record pairs connected through best n-grams is a maximum over all possible sets of best n-gram sets;

g) generating an index, based on the selected n-gram set;

h) using the generated index by the DBMS to service incoming queries, whereby the generated index created from the selected n-gram set minimizes false hits because the selected n-gram set maximizes reachability among unique query-record pairs and maximizes rejections.

8. The method of claim 7 further comprising:

implementing an approximation algorithm as a utility of the DBMS.

9. The method of claim 8 wherein the approximation algorithm provides a near optimal solution to an NP-hard n-gram selection problem, the method further comprising:

providing the approximation algorithm with a definable ratio bound of the optimal solution.

10. The method of claim 9 wherein the definable ratio bound is:

11. The method of claim 8 wherein the DBMS is a relational database system.