International Business Machines Corporation

Chen Xin Yu

Shuo Li

Xin Yang

Ke Wei Wei

Xin Peng Liu

Xiaobo Wang

Meng Wan

Ping Liang

Wei Liu

Shu Hua Liu

Xiong Zhao

Xiao Di Deng

Chong Yuan Yin

A processor within a networked distributed drafting platform generates a public key-value context file that includes initial default key-value mappings between keywords and values for use in a distributed drafting project. Refined project-level key-value mappings are elected by considering differences between the initial default key-value mappings and personal key-value mappings within a set of distributed personal key-value context files each maintained by different drafters of the distributed drafting project. The initial default key-value mappings of the public key-value context file are updated with the elected refined project-level key-value mappings within the networked distributed drafting platform.

Distributed key-value consistency and mapping

A database processing system includes a coordinator agent controller and a virtual node data base. The coordinator agent controller detects a request to access a database by an application program and to extracts database objects from a database protocol stream based on a requirement requested by the application program. The virtual node database is generated according to the extracted database objects. The virtual node database includes memory dump storage that stores the database objects extracted from the database protocol stream, and based on the database objects the virtual node database generates virtual database objects corresponding to the database protocol stream. The extraction of database objects is performed directly on the database protocol stream without communicating with a target real database.

Database process with virtual nodes

Aspects of the present disclosure relate to an approach for generating query execution plans for a database query. A computer-implemented method comprises determining whether a size of a file to be generated during execution of a database query is variable in response to obtaining the database query. The method further comprises determining a plurality of ranges for the size of the file in response to determining that the size of the file is variable. The method further comprises generating a plurality of query execution plans corresponding to the plurality of ranges. Accordingly, a plurality of query execution plans corresponding to different file sizes can be generated for the database query, and an efficient and cost effective query execution plan may be selected based on the actual file size during the execution of the database query.

Generation of query execution plans

A method for dynamically updating database statistics and a plurality of access paths associated with at least one database table is provided. The method may include identifying at least one dynamically changing column associated with the at least one database table. The method may further include determining at least one predicate pattern associated with the identified at least one dynamically changing column. Additionally, the method may include dynamically detecting at least one range change associated with the determined at least one predicate pattern based on at least one record insert. The method may also include updating the plurality of database statistics associated with the identified at least one dynamically changing column based on the dynamically detected at least one range change. The method may further include determining at least one filter factor based on the updated plurality of database statistics associated with the identified at least one dynamically changing column.

Determining dynamic statistics based on key value patterns

Optimization of a multi-index database access at runtime. A processor receives a query. A processor determines a plan and a record identifier (RID) results threshold for the plan, wherein the plan includes an access to the index. A processor determines a static risk threshold, a static risk for the access, and whether the static risk exceeds the static risk threshold. Responsive to the static risk exceeding the static risk threshold, a processor determines a risk bound for the access, and links the access to the risk bound. A processor accesses the index with the key. Responsive to the access being linked to a risk bound, a processor determines a dynamic risk for the access. A processor receives one or more RID results during the execution of the plan. A processor aborts the execution of the plan if a quantity of the RID results is less than the RID results threshold.

Runtime optimization for multi-index access

Optimization of a multi-index database access at runtime. A processor receives a query. A processor determines a plan and an RID results threshold for the plan, wherein the plan includes an access to the index. A processor determines a static risk threshold, a static risk for the access, and whether the static risk exceeds the static risk threshold. Responsive to the static risk exceeding the static risk threshold, a processor determines a risk bound for the access, and links the access to the risk bound. A processor accesses the index with the key. Responsive to the access being linked to a risk bound, a processor determines a dynamic risk for the access. A processor receives one or more RID results during the execution of the plan. A processor aborts the execution of the plan if a quantity of the RID results is less than the RID results threshold.

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Beijing, China

Chen Xin Yu