Abstract: Methods and systems are provided for converting a loop (e.g., a cursor loop) to a declarative Structured Query Language (SQL) query that invokes a custom aggregate function. The loop includes a select query and a loop body that includes a program fragment that can be evaluated over a result set of the select query one row at a time. The system verifies that the loop body does not modify a persistent state of the database. A custom aggregate function that expresses the loop body is automatically constructed according to a contract. An aggregate class comprising aggregation methods of the contract are used to construct the aggregate function based on results of static analysis. The select query is automatically rewritten to form a declarative SQL query that invokes the custom aggregate function. The declarative SQL query may be executed by a database management system (DBMS) SQL server.

Abstract: Systems, methods, and devices are described for performing scalable data processing operations. A queue that includes a translatable portion comprising indications of data processing operations translatable to data queries and a non-translatable portion comprising indications of non-translatable data processing operations is maintained. A determination that a first data processing operation of a first code block statement is translatable to a database query is made. An indication of the first data processing operation is included in the translatable portion of the queue. Responsive to a determination that a second data processing operation of a second code block statement is undeferrable, the translatable portion of the queue is compiled into a database query. An execution of the database query to be executed by a database engine to generate a query result is caused. A result dataset corresponding to the query result is transmitted to an application configured to analyze the result dataset.

Abstract: Systems, methods, and devices are described for performing scalable data processing operations. A queue that includes a translatable portion comprising indications of data processing operations translatable to data queries and a non-translatable portion comprising indications of non-translatable data processing operations is maintained. A determination that a first data processing operation of a first code block statement is translatable to a database query is made. An indication of the first data processing operation is included in the translatable portion of the queue. Responsive to a determination that a second data processing operation of a second code block statement is undeferrable, the translatable portion of the queue is compiled into a database query. An execution of the database query to be executed by a database engine to generate a query result is caused. A result dataset corresponding to the query result is transmitted to an application configured to analyze the result dataset.

Abstract: Methods and systems are provided for converting a loop (e.g., a cursor loop) to a declarative Structured Query Language (SQL) query that invokes a custom aggregate function. The loop includes a select query and a loop body that includes a program fragment that can be evaluated over a result set of the select query one row at a time. The system verifies that the loop body does not modify a persistent state of the database. A custom aggregate function that expresses the loop body is automatically constructed according to a contract. An aggregate class comprising aggregation methods of the contract are used to construct the aggregate function based on results of static analysis. The select query is automatically rewritten to form a declarative SQL query that invokes the custom aggregate function. The declarative SQL query may be executed by a database management system (DBMS) SQL server.

Abstract: Methods and systems are provided for converting a loop (e.g., a cursor loop) to a declarative Structured Query Language (SQL) query that invokes a custom aggregate function. The loop includes a select query and a loop body that includes a program fragment that can be evaluated over a result set of the select query one row at a time. The system verifies that the loop body does not modify a persistent state of the database. A custom aggregate function that expresses the loop body is automatically constructed according to a contract. An aggregate class comprising aggregation methods of the contract are used to construct the aggregate function based on results of static analysis. The select query is automatically rewritten to form a declarative SQL query that invokes the custom aggregate function. The declarative SQL query may be executed by a database management system (DBMS) SQL server.

Abstract: Methods and systems are provided for converting a loop (e.g., a cursor loop) to a declarative Structured Query Language (SQL) query that invokes a custom aggregate function. The loop includes a select query and a loop body that includes a program fragment that can be evaluated over a result set of the select query one row at a time. The system verifies that the loop body does not modify a persistent state of the database. A custom aggregate function that expresses the loop body is automatically constructed according to a contract. An aggregate class comprising aggregation methods of the contract are used to construct the aggregate function based on results of static analysis. The select query is automatically rewritten to form a declarative SQL query that invokes the custom aggregate function. The declarative SQL query may be executed by a database management system (DBMS) SQL server.

Abstract: Processing a database query. A method includes receiving a database query from a user. The database query includes one or more imperative functions. The one or more imperative functions are converted to one or more declarative query representations. The one or more declarative query representations include standardized relational operators included in a relational query language. Further, the one or more declarative query representations are optimizable by a query optimizer of the database. The database query is optimized at the query optimizer to create a query plan by evaluating any declarative query representation originally in the database query received from the user and the one or more declarative query representations.

Abstract: Managing cluster resources for a cluster. The method includes identifying a plurality of quiescence policies. Each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities. The method further includes, for each quiescence policy, identifying an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy. The method further includes, for each quiescence policy, identifying an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities. The method further includes; selecting a quiescence policy based on comparing the reclaimed capacities and reserve capacities for the quiescence policies. The method further includes, booking cluster resources for cluster entities on the cluster according to the selected quiescence policy.

Abstract: Processing a database query. A method includes receiving a database query from a user. The database query includes one or more imperative functions. The one or more imperative functions are converted to one or more declarative query representations. The one or more declarative query representations include standardized relational operators included in a relational query language. Further, the one or more declarative query representations are optimizable by a query optimizer of the database. The database query is optimized at the query optimizer to create a query plan by evaluating any declarative query representation originally in the database query received from the user and the one or more declarative query representations.

Abstract: Managing cluster resources for a cluster. The method includes identifying a plurality of quiescence policies. Each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities. The method further includes, for each quiescence policy, identifying an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy. The method further includes, for each quiescence policy, identifying an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities. The method further includes; selecting a quiescence policy based on comparing the reclaimed capacities and reserve capacities for the quiescence policies.