1. Field of the Invention
The present invention generally relates to data processing and more particularly to query optimization by executing queries in a backup environment.
2. Description of the Related Art
Databases are computerized information storage and retrieval systems. A relational database management system is a computer database management system (DBMS) that uses relational techniques for storing and retrieving data. The most prevalent type of database is the relational database, a tabular database in which data is defined so that it can be reorganized and accessed in a number of different ways. A distributed database is one that can be dispersed or replicated among different points in a network. An object-oriented programming database is one that is congruent with the data defined in object classes and subclasses.
Regardless of the particular architecture, in a DBMS, a requesting entity (e.g., an application or the operating system) demands access to a specified database by issuing a database access request. Such requests may include, for instance, simple catalog lookup requests or transactions and combinations of transactions that operate to read, change and add specified records in the database. These requests are made using high-level query languages such as the Structured Query Language (SQL). Illustratively, SQL is used to make interactive queries for getting information from and updating a database such as International Business Machines' (IBM) DB2, Microsoft's SQL Server, and database products from Oracle, Sybase, and Computer Associates. The term “query” denominates a set of commands for retrieving data from a stored database. Queries take the form of a command language that lets programmers and programs select, insert, update, find out the location of data, and so forth.
Generally, the DBMS includes a query optimizer component configured to determine the manner in which queries will be processed. The primary task of the optimizer is to determine the most efficient way to execute each particular query against a database. To this end, the optimizer determines an access plan for use in executing the query against the database. In general, the access plan contains low-level information indicating precisely what steps the system is to take to execute the query (e.g., using an index, a hash table, bit map, etc.). For any given query, there are a large number of possible access plans that may be chosen. Conventional optimizers are generally configured to determine the best access plan for each query they encounter, based on cost comparisons (i.e., estimated resource requirements, typically in terms of time and space) of available access plans. In selecting the access plan (and comparing associated costs), the optimizer may explore various ways to execute the query. For example, the optimizer may determine if an index may be used to speed a search, whether a search condition should be applied to a first table prior to joining the first table to a second table or whether to join the tables first. In determining the best access plan, optimizers may also group queries based on similarities and use the same access plan for queries that are similar.
In processing simple queries, choosing an access plan may be a rather simple task. However, as queries become increasingly complex, the complexity of choosing an access plan may increase accordingly, as the optimizer may have to take account of many different variables to determine the most efficient access plan. Even so, when optimizing large and complex queries, due to processing limitations of the optimizer, the access plan selected by the optimizer may not in actuality be the most efficient access plan. In fact, unless the queries are actually run with the different access plans to examine their execution time, there may be no definite way of determining the best access plan.
Accordingly, there is a need for an improved method of optimizing query execution, preferably that involves the actual execution of queries using different access plans to determine the most efficient one.
USPTO Backgrounds
USPTO Backgrounds