Abstract: A query method and a query device, where the method includes determining N execution plans respectively corresponding to N query requests according to the received N query requests, determining at least two same first sub-plans, generating a first sub-query result corresponding to any one of the at least two same first sub-plans, and in a process of generating, according to the N query requests, a query result corresponding to each of the N query requests, the same first sub-query result corresponding to any one of the first sub-plans is used for all the same first sub-plans. Hence, a large amount of repeated calculation can be reduced, database system resources are reduced, and query efficiency and a throughput of a database system in a large-scale concurrent query application scenario are improved.

Abstract: A method and an apparatus for determining a structured query language (SQL) execution plan are provided to optimize determining of the SQL execution plan and improve execution efficiency of the SQL execution plan. The SQL execution plan corresponds to at least one relation table. During an Nth iteration, the method includes obtaining a first iteration parameter generated after a first plan tree is executed on the at least one relation table during an (N?1)th iteration, where N is a natural number greater than 1, establishing a second plan tree according to the first iteration parameter, and determining the first plan tree or the second plan tree as the SQL execution plan when a difference between the second plan tree and the first plan tree is not greater than a first threshold.

Abstract: An information processing includes a kernel of a database management system that obtains target information, and determines creation information of a model of the target information according to the target information, where the model of the target information is used to estimate an execution cost of the target information. The creation information includes use information and training algorithm information of the model. The kernel sends a training instruction to an external trainer, and the external trainer then performs machine learning training on the data in the database according to the target information and the creation information of the model to obtain a first model of the target information.

Abstract: A query method and a query device, where the method includes determining N execution plans respectively corresponding to N query requests according to the received N query requests, determining at least two same first sub-plans, generating a first sub-query result corresponding to any one of the at least two same first sub-plans, and in a process of generating, according to the N query requests, a query result corresponding to each of the N query requests, the same first sub-query result corresponding to any one of the first sub-plans is used for all the same first sub-plans. Hence, a large amount of repeated calculation can be reduced, database system resources are reduced, and query efficiency and a throughput of a database system in a large-scale concurrent query application scenario are improved.

Abstract: A method and an apparatus for determining a structured query language (SQL) execution plan are provided to optimize determining of the SQL execution plan and improve execution efficiency of the SQL execution plan. The SQL execution plan corresponds to at least one relation table. During an Nth iteration, the method includes obtaining a first iteration parameter generated after a first plan tree is executed on the at least one relation table during an (N?1)th iteration, where N is a natural number greater than 1, establishing a second plan tree according to the first iteration parameter, and determining the first plan tree or the second plan tree as the SQL execution plan when a difference between the second plan tree and the first plan tree is not greater than a first threshold.