Abstract: A database system receives a request from a user. The request invokes a data set function (DSF) and uses a property to be provided by the DSF. The database system determines that a function descriptor is available for the DSF. The function descriptor is expressed as markup language instructions. The function descriptor defines the property of the DSF. The database system uses the function descriptor to define a property for the DSF.

Abstract: Execution of a query invoking an analytical function (AF) is optimized. The query includes a join operation between an AF table and an AuxiliaryTable. A determination is made that the AF includes a plurality of AF properties. Query-level properties about the query are inferred. A determination is made to change an order of the join operation from the plurality of AF properties and query-level properties.

Abstract: Hyperparameter tuning for a machine learning model is performed in a massively parallel database system. A computer system comprised of a plurality of compute units executes a relational database management system (RDBMS), wherein the RDBMS manages a relational database comprised of one or more tables storing data. One or more of the compute units perform the hyperparameter tuning for the machine learning model, wherein the hyperparameters are control parameters used in construction of the model, and the tuning of the hyperparameters is implemented as an operation in the RDBMS that accepts training and scoring data for the model, constructs the model using the hyperparameters and the training data, and generates goodness metrics for the model using the scoring data.

Abstract: As an abstract representation, a set of equivalent logical structures representative of multiple execution plans for execution of a database query can be used to optimize a database query. A logical structure can include one or more logical operators each representing multiple physical operators for executing the database query. Group and Operator Rules can be applied as rules to the set of equivalent logical structures to obtain additional equivalent logical structures and logical operator until no additional logical operators can be obtained. A set of possible implementation plans for the total number of the obtained logical operators can be obtained, for example, based on physical and/or implementation context.

Abstract: As an abstract representation, a set of equivalent logical structures representative of multiple execution plans for execution of a database query can be used to optimize a database query. A logical structure can include one or more logical operators each representing multiple physical operators for executing the database query. Group and Operator Rules can be applied as rules to the set of equivalent logical structures to obtain additional equivalent logical structures and logical operator until no additional logical operators can be obtained. A set of possible implementation plans for the total number of the obtained logical operators can be obtained, for example, based on physical and/or implementation context.

Abstract: The execution of the one or more database queries can be optimized by using a multi-platform cost model that take into account the respective cost of execution in each one of the multiple execution platforms. The respective costs of the execution can, for example, include cost associated with one or more operators for executing the one or more database queries in each one of the multiple execution platforms and/or the costs of exchanging data between the multiple execution platforms.

Abstract: A database system receives a request from a user. The request invokes a data set function (DSF) and uses a property to be provided by the DSF. The database system determines that a function descriptor is available for the DSF. The function descriptor is expressed as markup language instructions. The function descriptor defines the property of the DSF. The database system uses the function descriptor to define a property for the DSF.

Abstract: Execution of a query invoking an analytical function (AF) is optimized. The query includes a join operation between an AF table and an AuxiliaryTable and includes determining that the AF includes a plurality of AF properties. Query-level properties about the query are inferred. It is determined to change an order of the join operation from the plurality of AF properties and query-level properties.

Abstract: As an abstract representation, a set of equivalent logical structures representative of multiple execution plans for execution of a database query can be used to optimize a database query. A logical structure can include one or more logical operators each representing multiple physical operators for executing the database query. Group and Operator Rules can be applied as rules to the set of equivalent logical structures to obtain additional equivalent logical structures and logical operator until no additional logical operators can be obtained. A set of possible implementation plans for the total number of the obtained logical operators can be obtained, for example, based on physical and/or implementation context.

Abstract: As an abstract representation, a set of equivalent logical structures representative of multiple execution plans for execution of a database query can be used to optimize a database query. A logical structure can include one or more logical operators each representing multiple physical operators for executing the database query. Group and Operator Rules can be applied as rules to the set of equivalent logical structures to obtain additional equivalent logical structures and logical operator until no additional logical operators can be obtained. A set of possible implementation plans for the total number of the obtained logical operators can be obtained, for example, based on physical and/or implementation context.

Abstract: The execution of the one or more database queries can be optimized by using a multi-platform cost model that take into account the respective cost of execution in each one of the multiple execution platforms. The respective costs of the execution can, for example, include cost associated with one or more operators for executing the one or more database queries in each one of the multiple execution platforms and/or the costs of exchanging data between the multiple execution platforms.