Abstract: Systems and methods that generate specialized plans for compiling SQL queries. A plan generator component scans the query representation for parameter sensitive predicates and evaluates each predicate individually based on the parameter values. Accordingly, queries can be identified not only based on their structures, but also based on their parameter conditions. The specialized plans are more efficient for particular values, wherein queries that employ such values are optimally executed.

Abstract: A suggested query execution plan is used as a constraint on a guided optimization process such that all execution plans that do not conform to the suggested execution plan are eliminated as possible alternatives. If the guided optimization process successfully generates a resulting execution plan, then the result will conform to the suggested execution plan. If the guided optimization process fails to generate a resulting execution plan, then it may be determined that the suggested execution plan is invalid.

Abstract: Systems and methods are provided to increase the scalability of subscriptions in an electronic database environment. In an illustrative implementation, a computing application comprises at least one instruction set to cooperate with a data environment to optimize the processing of subscriptions by the data environment when communicating with cooperating services and/or applications. In operation, a subscription is identified. A subscription template is created for the subscription and the subscription template is parameterized to create a parameter table containing parameters (e.g. subscription constants). A join is then performed between the parameters of the parameter table and the parameterized subscription templates to generate application and/or service data required by the cooperating services and/or applications. The data is then processed by the applications and/or services.

Abstract: A database system and method allows a user to write program code in a high-level programming language that implements a class that defines the structure of a user-defined aggregate and methods that can be invoked on instances of the user-defined aggregate. The class is then registered with the database system, which enforces a specific contract for user-defined aggregates against the class. The contract comprises the following requirements. First, the class must specify one of a plurality of different formats for persisting instances of the user-defined aggregate in a database store. Second, the class must comprise certain specified methods that can be invoked on an instance of the class. Once these requirements are satisfied, the database system enables instances of the user-defined aggregate to be created. Preferably, the database system stores metadata about the user-defined aggregate for subsequent use in creating instances of the aggregate.

Abstract: Indexed views or materialized views are used as a secondary index on a base table with multi-valued attributes. This provides for using the index to search in the nested data. Moreover, indexing is provided on the result of an unnest operation. Indexing a view on the result of an unnesting operation provides the ability to index the contents of a nested collection. One such unnesting operation is “cross apply unnest”. This provides additional options for a query execution plan, leading to a more optimized query. A back-join is provided from the indexed view to the base table to allow fields from the base table that are not present in the indexed view to be included in a result of a query on the table which is processed using the indexed view as an access path. This provides a means of including columns in the query result that are not in the indexed view but are in the base table.

Abstract: Indexed views or materialized views are used as a secondary index on a base table with multi-valued attributes. This provides for using the index to search in the nested data. Moreover, indexing is provided on the result of an unnest operation. Indexing a view on the result of an unnesting operation provides the ability to index the contents of a nested collection. One such unnesting operation is “cross apply unnest”. This provides additional options for a query execution plan, leading to a more optimized query. A back-join is provided from the indexed view to the base table to allow fields from the base table that are not present in the indexed view to be included in a result of a query on the table which is processed using the indexed view as an access path. This provides a means of including columns in the query result that are not in the indexed view but are in the base table.

Abstract: Validation of large numbers of alternative execution plans for a database query, either an exhaustive enumeration of the complete space of alternatives, or else an unbiased random sample, is performed by efficiently constructing execution trees from a data structure having groups alternative operators that are ranked in a directory. Each global rank of a plan identifies that plan uniquely among all the alternative plans. The operators are unranked from the directory according to a specification that characterizes the desired plans.

Abstract: Indexed views or materialized views are used as a secondary index on a base table with multi-valued attributes. This provides for using the index to search in the nested data. Moreover, indexing is provided on the result of an unnest operation. Indexing a view on the result of an unnesting operation provides the ability to index the contents of a nested collection. One such unnesting operation is “cross apply unnest”. This provides additional options for a query execution plan, leading to a more optimized query. A back-join is provided from the indexed view to the base table to allow fields from the base table that are not present in the indexed view to be included in a result of a query on the table which is processed using the indexed view as an access path. This provides a means of including columns in the query result that are not in the indexed view but are in the base table.

Abstract: Indexed views or materialized views are used as a secondary index on a base table with multi-valued attributes. This provides for using the index to search in the nested data. Moreover, indexing is provided on the result of an unnest operation. Indexing a view on the result of an unnesting operation provides the ability to index the contents of a nested collection. One such unnesting operation is “cross apply unnest”. This provides additional options for a query execution plan, leading to a more optimized query. A back-join is provided from the indexed view to the base table to allow fields from the base table that are not present in the indexed view to be included in a result of a query on the table which is processed using the indexed view as an access path. This provides a means of including columns in the query result that are not in the indexed view but are in the base table.

Abstract: When two or more scalar subtrees in an execution plan are directed towards the same data set, but request different data from the data set, the two subtrees are replaced in the execution plan with a new subtree which queries the data set only once. This new query to the data set covers all data required by the different subtrees. A pivoting step then is used to separate the data which would have been sought by each subtree. The pivoting step also yields data in the same form as would have resulted from the original subtrees.

Abstract: A method of accumulating and aggregating statistics concerning the use of database table indexes includes using a plurality of counters to register index use. The plurality of counters allow multiple instances of index usage to be recorded simultaneously. A missing index may be detected using an optimal index in a query plan. The optimal index is compared against the available indexes to determine if an index is missing. Statistics may be gathered against the used and missing indexes.

Abstract: Validation of large numbers of alternative execution plans for a database query, either an exhaustive enumeration of the complete space of alternatives, or else an unbiased random sample, is performed by efficiently constructing execution trees from a data structure having groups alternative operators that are ranked in a directory. Each global rank of a plan identifies that plan uniquely among all the alternative plans. The operators are unranked from the directory according to a specification that characterizes the desired plans.

Abstract: A client submits a subscription to a database specifying selected data within a data set. A subscription plan is generated based on the subscription. A query is submitted to the database changing selected data within the data set. A query plan is generated based on the query. The subscription is matched to the query based on the data set, and the query plan is supplemented with the subscription plan to generate a notification of the change to the client.

Abstract: Validation of large numbers of alternative execution plans for a database query, either an exhaustive enumeration of the complete space of alternatives, or else an unbiased random sample, is performed by efficiently constructing execution trees from a data structure having groups alternative operators that are ranked in a directory. Each global rank of a plan identifies that plan uniquely among all the alternative plans. The operators are unranked from the directory according to a specification that characterizes the desired plans.

Abstract: During query execution, statistics associated with expressions are observed. Such observed statistics preferably include the cardinality of each expression. The observed statistics are submitted to an expression manager as feedback from the executed query. The statistics are preferably stored for use in estimating the cardinality of execution plans for future queries.

Abstract: A partial pre-aggregation database operation improves processing efficiency of database queries by reducing the number of records input into a subsequent database operation, provided the query includes a final aggregation. A query optimizer is provided to determine when it is economical to partially pre-aggregate data records and when it is not. The partial pre-aggregation creates a record store in memory as input records are received. The record store is then used by another database operator, which saves the other database operator from having to re-create the record store.

Abstract: A suggested query execution plan is used as a constraint on a guided optimization process such that all execution plans that do not conform to the suggested execution plan are eliminated as possible alternatives. If the guided optimization process successfully generates a resulting execution plan, then the result will conform to the suggested execution plan. If the guided optimization process fails to generate a resulting execution plan, then it may be determined that the suggested execution plan is invalid.

Abstract: A system and method for creation, modification and/or use of plan guide(s) is provided. Plan guide(s) can be employed to optimize the performance of query(ies) when it is not possible and/or desirable to change the text of the query directly. Plan guides can be useful, for example, when a small subset of queries in a database application deployed from a third-party vendor is not performing as expected. Plan guides influence optimization of queries by attaching query hints to them. In accordance with an aspect of the subject invention, a query plan execution system is provided. The system includes an execution component, a query optimizer, and, a plan cache. Plan guides and other associated metadata are stored in a plan guide metadata store.

Abstract: Validation of large numbers of alternative execution plans for a database query, either an exhaustive enumeration of the complete space of alternatives, or else an unbiased random sample, is performed by efficiently constructing execution trees from a data structure having groups alternative operators that are ranked in a directory. Each global rank of a plan identifies that plan uniquely among all the alternative plans. The operators are unranked from the directory according to a specification that characterizes the desired plans.

Abstract: Validation of large numbers of alternative execution plans for a database query, either an exhaustive enumeration of the complete space of alternatives, or else an unbiased random sample, is performed by efficiently constructing execution trees from a data structure having groups alternative operators that are ranked in a directory. Each global rank of a plan identifies that plan uniquely among all the alternative plans. The operators are unranked from the directory according to a specification that characterizes the desired plans.