Abstract: Computer-readable media, methods, and systems are disclosed for proactively compiling in-memory database management system (DBMS) query plans upon startup of the in-memory DBMS. During normal operation of the in-memory DBMS, alternative query plans having associated execution statistics are collected and captured. Thereafter, the alternative query plans are selectively persisted and in response to detecting performance regressions, the regressed query plan is compared with prior query plans. In response to determining that a prior query plan performs better, the regressed query plan is replaced with the prior query plan. Upon a restart of the in-memory DBMS, a selected portion of the plurality of alternative query execution plans is loaded, and the plurality of alternative query execution plans are compiled. New queries are received and executed based on the proactively compiled query plans.

Abstract: Computer-readable media, methods, and systems are disclosed for proactively compiling in-memory database management system (DBMS) query plans upon startup of the in-memory DBMS. During normal operation of the in-memory DBMS, alternative query plans having associated execution statistics are collected and captured. Thereafter, the alternative query plans are selectively persisted and in response to detecting performance regressions, the regressed query plan is compared with prior query plans. In response to determining that a prior query plan performs better, the regressed query plan is replaced with the prior query plan. Upon a restart of the in-memory DBMS, a selected portion of the plurality of alternative query execution plans is loaded, and the plurality of alternative query execution plans are compiled. New queries are received and executed based on the proactively compiled query plans.

Abstract: A computer implemented method can receive a request for a fallback query execution plan of a query in a database system. The query involves an object of the database system. The object is associated with a captured object. The method can evaluate whether the object and the captured object have the same logical structure. Responsive to an indication that the object and the captured object have the same logical structure, the method can reuse the fallback query execution plan to execute the query. The evaluating includes identifying a logical structure of the captured object stored in an object definition table, obtaining a current logical structure of the object, and comparing the logical structure of the captured object with the current logical structure of the object.

Abstract: Methods and apparatus are disclosed for staged query compilation. One or more intermediate plans between a query and its execution plan are stored according to a common specification for plan data structures. Data sources, a plan flow, and annotations can be stored in respective fields of the plan data structure, which can be extended with a field for a serialized execution plan. Plan data structures provide a stable interface for integration of local and external software modules, and decouple plan representation from plan optimization. Use cases are disclosed for integrating offline optimization with inline software modules, for integrating local query handling with external services, for caching intermediate plans, and for archiving plans across version changes of optimizers. A hub architecture flexibly supports numerous compilation workflows. Disclosed technologies are suitable for cloud deployments and for migration of databases into the cloud.

Abstract: A computer implemented method can execute a first query plan for a query, obtain statistics for internal nodes of a first query tree representing the first query plan, receive a second query tree representing a second query plan for the query, search for a matching internal node of the first query tree for a selected internal node of the second query tree, and responsive to finding the matching internal node of the first query tree, apply the statistics for the matching internal node of the first query tree to the selected internal node of the second query tree for estimating cost of the second query plan during query optimization of the query. Related systems and software for implementing the method are also disclosed.

Abstract: A computer implemented method can receive a request for a fallback query execution plan of a query in a database system. The query involves an object of the database system. The object is associated with a captured object. The method can evaluate whether the object and the captured object have the same logical structure. Responsive to an indication that the object and the captured object have the same logical structure, the method can reuse the fallback query execution plan to execute the query. The evaluating includes identifying a logical structure of the captured object stored in an object definition table, obtaining a current logical structure of the object, and comparing the logical structure of the captured object with the current logical structure of the object.

Abstract: A computer implemented method can execute a first query plan for a query, obtain statistics for internal nodes of a first query tree representing the first query plan, receive a second query tree representing a second query plan for the query, search for a matching internal node of the first query tree for a selected internal node of the second query tree, and responsive to finding the matching internal node of the first query tree, apply the statistics for the matching internal node of the first query tree to the selected internal node of the second query tree for estimating cost of the second query plan during query optimization of the query. Related systems and software for implementing the method are also disclosed.

Abstract: Methods, systems, and computer-readable storage media for receiving a query plan and a set of query parameters of the query plan, the query plan corresponding to a query submitted to a database system, and determining that the set of query parameters matches a filter in a set of filters, each parameter in a set of parameters of the filter matching a query parameter in the set of query parameters, and in response: providing the query plan to an abstract query plan generator that generates an abstract query plan based on the query plan, and storing the abstract query plan in an abstract query plan store.

Abstract: Methods and apparatus are disclosed for staged query compilation. One or more intermediate plans between a query and its execution plan are stored according to a common specification for plan data structures. Data sources, a plan flow, and annotations can be stored in respective fields of the plan data structure, which can be extended with a field for a serialized execution plan. Plan data structures provide a stable interface for integration of local and external software modules, and decouple plan representation from plan optimization. Use cases are disclosed for integrating offline optimization with inline software modules, for integrating local query handling with external services, for caching intermediate plans, and for archiving plans across version changes of optimizers. A hub architecture flexibly supports numerous compilation workflows. Disclosed technologies are suitable for cloud deployments and for migration of databases into the cloud.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a current database system, a query plan file representative of a captured query plan from a source database system, receiving, by the current database system, a set of definitions including one or more definitions, each definition in the set of definitions corresponding to an object that is implicated by the query plan, the object being included in a set of objects, and determining, by the current database system, that each definition in the set of definitions is identical to a respective definition of a corresponding object within the current database system, and in response: executing the captured query plan in the current database system to provide a query result.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a current database system, a query plan file representative of a captured query plan from a source database system, receiving, by the current database system, a set of definitions including one or more definitions, each definition in the set of definitions corresponding to an object that is implicated by the query plan, the object being included in a set of objects, and determining, by the current database system, that each definition in the set of definitions is identical to a respective definition of a corresponding object within the current database system, and in response: executing the captured query plan in the current database system to provide a query result.

Abstract: Methods, systems, and computer-readable storage media for receiving a query plan and a set of query parameters of the query plan, the query plan corresponding to a query submitted to a database system, and determining that the set of query parameters matches a filter in a set of filters, each parameter in a set of parameters of the filter matching a query parameter in the set of query parameters, and in response: providing the query plan to an abstract query plan generator that generates an abstract query plan based on the query plan, and storing the abstract query plan in an abstract query plan store.

Abstract: A query is parsed and positions of symbols of the query are determined. A parse tree including the positions of the symbols is generated based on the parsed query. The parse tree is sent to a DBMS optimizer. The parse tree is transformed into an optimizer tree. The optimizer tree includes the positions of the symbols of the query. Based on the optimizer tree, a query execution plan is generated for the execution of the query. The positions of the symbols of the query is copied from the optimizer tree into the query execution plan. The query execution plan is sent to a query execution engine. The query is executed in accordance with the query execution plan. When a runtime error is detected, an exception message associated with the runtime error is displayed. The error message includes an error code and the positions of the symbols of the query.

Abstract: A query is parsed and positions of symbols of the query are determined. A parse tree including the positions of the symbols is generated based on the parsed query. The parse tree is sent to a DBMS optimizer. The parse tree is transformed into an optimizer tree. The optimizer tree includes the positions of the symbols of the query. Based on the optimizer tree, a query execution plan is generated for the execution of the query. The positions of the symbols of the query is copied from the optimizer tree into the query execution plan. The query execution plan is sent to a query execution engine. The query is executed in accordance with the query execution plan. When a runtime error is detected, an exception message associated with the runtime error is displayed. The error message includes an error code and the positions of the symbols of the query.