Abstract: Provided are techniques for progressive optimization for implicit CAST predicates. In response to receiving a query with an original predicate comparing a character value of a character data type to a literal value of a numeric data type, a number of iterations is set to a length of the character data type. For each of the number of iterations, prefix predicates are generated based on that iteration and processed to identify a qualified index key in an index. Once the iterations are completed, the character value and the literal value are normalized. The original predicate with the normalized character value and the normalized literal value is applied starting at the qualified index key identified in a last iteration to generate a result set for the query. The result set is returned.

Abstract: Provided are techniques for progressive optimization for implicit CAST predicates. In response to receiving a query with an original predicate comparing a character value of a character data type to a literal value of a numeric data type, a number of iterations is set to a length of the character data type. For each of the number of iterations, prefix predicates are generated based on that iteration and processed to identify a qualified index key in an index. Once the iterations are completed, the character value and the literal value are normalized. The original predicate with the normalized character value and the normalized literal value is applied starting at the qualified index key identified in a last iteration to generate a result set for the query. The result set is returned.

Abstract: In an approach for optimizing query processing within a relational database management environment, one or more computer processors construct a first data structure for an access path operation. The first data structure is an interpretable data structure. The one or more computer processors determine whether the first data structure can be optimized with machine code. Responsive to determining the first data structure can be optimized with machine code, the one or more computer processors generate machine code to perform at least one operation of the first data structure.

Abstract: A method for generating an execution plan for updating and retrieving data from a database in a single process includes: receiving a statement by a server to update a database with a first set of data and to retrieve a second set of data from the database; building a first execution plan to update the database with the first set of data; building a second execution plan to retrieve the second set of data from the database; and building a single execution plan including a combination of the first and second execution plans. The single execution plan allows for the updating and retrieval of data with a single crossing of an interface between a client and the database. By performing both functions in this manner, the efficiency of performing such tasks on the database is significantly increased.

Abstract: A method for conversion between a decimal floating-point number and an order-preserving format has been disclosed. The method encodes numbers in the decimal floating-point format into a format which preserves value ordering. This encoding allows for fast and direct string comparison of two values. Such an encoding provides normalized representations for decimal floating-point numbers and supports type-insensitive comparisons. Type-insensitive comparisons are often used in database management systems, where the data type is not specified for values to compare. In addition, the original decimal floating-point format can be recovered from the order-preserving format.

Abstract: A method, system, or mechanism for providing diagnostic information for a data request in a distributed data system where the distributed data system includes a plurality of interconnected data request processing devices and where only the one data request processing device of the plurality of interconnected data request processing devices that fulfills the data request appends request fulfillment diagnostic information to the fulfilled data request, each interconnected data request processing devices that participates in the processing of the data request appends data request processing device condition information diagnostics to the data request, and each data request processing device that forms a connection between another data request processing device while processing the data request appends connection information diagnostics to the fulfilled data request related to the connection between the data request processing device and the another data request processing device.

Abstract: A method, apparatus and article of manufacture for computer implemented method of efficiently executing built-in functions is defined. Function modules are defined to process a single data type class and to process as many functions as possible before returning to the caller. Functions related to a query are each assigned a key, a type of code, to indicate the data type class to which the function belongs. The functions are then ordered so that a particular module scope can be held as long as possible. Further, data fields, another type of code containing optimization information, can be added to the functions to further enable the holding of module scope. Finally, the functions are executed at runtime. During execution, the database system looks ahead at upcoming functions in an attempt anticipate the next course of action by examining the keys and data fields. Various additional optimization techniques can then be used to enhance runtime performance.