Abstract: A system for assigning a workload to compute resources includes an interface and a processor. The interface is configured to receive a workload. The processor is configured to break the workload into a set of subproblems; and for a subproblem of the set of subproblems: determine whether the subproblem benefits from intersheet parallelism; determine whether the subproblem benefits from intrasheet parallelism; determine whether the subproblem benefits from directed acyclic graph (DAG) partitioning; and assign the subproblem, wherein assigning the subproblem utilizes optimization when appropriate based at least in part on benefits from the intersheet parallelism, the intrasheet parallelism, and the DAG partitioning.

Abstract: A query optimizer may receive a query block that includes a hint. The hint may include a unique object identifier to specify an object to which the hint applies. In some instances, the object may correspond to a nested query block. A query optimization plan may be determined based, at least in part, on the hint. The query execution plan may then be executed to query a data store.

Abstract: A query optimizer may receive a query (e.g., from a source that generated the query). Input that specifies both a query hint string and a hint may be received to a hint specification interface. The hint may be applied to the query, from outside the query, to optimize a query execution plan. Applying the hint may be based, at least in part, on a query hint string. For example, which query block is associated with the query hint string may be determined. Upon such a determination, the hint may be applied to the determined query block.

Abstract: A query optimizer may receive a query (e.g., from a source that generated the query). Input that specifies both a query hint string and a hint may be received to a hint specification interface. The hint may be applied to the query, from outside the query, to optimize a query execution plan. Applying the hint may be based, at least in part, on a query hint string. For example, which query block is associated with the query hint string may be determined. Upon such a determination, the hint may be applied to the determined query block.

Abstract: A query optimizer may receive a query (e.g., from a source that generated the query). Input that specifies both a query hint string and a hint may be received to a hint specification interface. The hint may be applied to the query, from outside the query, to optimize a query execution plan. Applying the hint may be based, at least in part, on a query hint string. For example, which query block is associated with the query hint string may be determined. Upon such a determination, the hint may be applied to the determined query block.

Abstract: In a system and method for order-independent stream query processing, one or more input streams of data are received, and the one or more input streams are analyzed to determine data which is older than an already emitted progress indicator. The data which is older than the already emitted progress indicator is partitioned into one or more partitions, and each of the one or more partitions are independently processed using out-of-order processing techniques. A query is received, rewritten and decomposed into one or more sub-queries that produce partial results for each of the one or more partitions, where each of the one or more sub-queries correspond to a partition. A view is also produced that consolidates the partial results for each partition. The partial results are consolidated at a consolidation time specified by the query to produce final results, and the final results are provided.

Abstract: A streaming database management system may provide support for creating a new continuous query operator for on-the-fly addition of a new query, e.g., a new SQL query and/or new continuous query operator, into a shared continuous query plan. Alternatively, the streaming database management system may associate the new query on-the-fly with an existing continuous query operator, such as a relational operator and expression evaluator, to reuse the existing continuous query operator. In some embodiments, multiple operators are grouped for on-the-fly addition to the shared continuous query plan. Alternatively, the streaming database management system may identify a group of multiple operators in the shared continuous query plan for reuse by the new query.

Abstract: Systems, methods, and media are disclosed herein that can be embodied in a traditional Relational Database Management System (RDBMS) in order to transform it into a Streaming Relational Database Management System (SRDBMS). An SRDBMS may provide functionality such as to manage and populate streams, tables, and archived stream histories and support the evaluation of continuous queries on streams and tables. Both continuous and snapshot queries support the full spectrum of the industry standard, widely used, Structured Query Language. The present technology can support a high number of concurrent continuous queries using a scalable and efficient shared query evaluation scheme, support on-the-fly addition of continuous queries into a mechanism that implements the shared evaluation scheme, reuse RDBMS modules such as relational operators and expression evaluators, and visualize results of continuous queries in real time.

Abstract: Systems, methods, and media are disclosed herein that can be embodied in a traditional Relational Database Management System (RDBMS) in order to transform it into a Streaming Relational Database Management System (SRDBMS). An SRDBMS may provide functionality such as to manage and populate streams, tables, and archived stream histories and support the evaluation of continuous queries on streams and tables. Both continuous and snapshot queries support the full spectrum of the industry standard, widely used, Structured Query Language. The present technology can support a high number of concurrent continuous queries using a scalable and efficient shared query evaluation scheme, support on-the-fly addition of continuous queries into a mechanism that implements the shared evaluation scheme, reuse RDBMS modules such as relational operators and expression evaluators, and visualize results of continuous queries in real time.

Abstract: In a system and method for order-independent stream query processing, one or more input streams of data are received, and the one or more input streams are analyzed to determine data which is older than an already emitted progress indicator. The data which is older than the already emitted progress indicator is partitioned into one or more partitions, and each of the one or more partitions are independently processed using out-of-order processing techniques. A query is received, rewritten and decomposed into one or more sub-queries that produce partial results for each of the one or more partitions, where each of the one or more sub-queries correspond to a partition. A view is also produced that consolidates the partial results for each partition. The partial results are consolidated at a consolidation time specified by the query to produce final results, and the final results are provided.

Abstract: In a system and method for order-independent stream query processing, one or more input streams of data are received, and the one or more input streams are analyzed to determine data which is older than an already emitted progress indicator. The data which is older than the already emitted progress indicator is partitioned into one or more partitions, and each of the one or more partitions are independently processed using out-of-order processing techniques. A query is received, rewritten and decomposed into one or more sub-queries that produce partial results for each of the one or more partitions, where each of the one or more sub-queries correspond to a partition. A view is also produced that consolidates the partial results for each partition. The partial results are consolidated at a consolidation time specified by the query to produce final results, and the final results are provided.

Abstract: Systems, methods, and media are disclosed herein that can be embodied in a traditional Relational Database Management System (RDBMS) in order to transform it into a Streaming Relational Database Management System (SRDBMS). An SRDBMS may provide functionality such as to manage and populate streams, tables, and archived stream histories and support the evaluation of continuous queries on streams and tables. Both continuous and snapshot queries support the full spectrum of the industry standard, widely used, Structured Query Language.

Abstract: Systems, methods, and media are disclosed herein that can be embodied in a traditional Relational Database Management System (RDBMS) in order to transform it into a Streaming Relational Database Management System (SRDBMS). An SRDBMS may provide functionality such as to manage and populate streams, tables, and archived stream histories and support the evaluation of continuous queries on streams and tables. Both continuous and snapshot queries support the full spectrum of the industry standard, widely used, Structured Query Language.

Abstract: In a system and method for order-independent stream query processing, one or more input streams of data are received, and the one or more input streams are analyzed to determine data which is older than an already emitted progress indicator. The data which is older than the already emitted progress indicator is partitioned into one or more partitions, and each of the one or more partitions are independently processed using out-of-order processing techniques. A query is received, rewritten and decomposed into one or more sub-queries that produce partial results for each of the one or more partitions, where each of the one or more sub-queries correspond to a partition. A view is also produced that consolidates the partial results for each partition. The partial results are consolidated at a consolidation time specified by the query to produce final results, and the final results are provided.

Abstract: Systems, methods, and media are disclosed herein that can be embodied in a traditional Relational Database Management System (RDBMS) in order to transform it into a Streaming Relational Database Management System (SRDBMS). An SRDBMS may provide functionality such as to manage and populate streams, tables, and archived stream histories and support the evaluation of continuous queries on streams and tables. Both continuous and snapshot queries support the full spectrum of the industry standard, widely used, Structured Query Language.

Abstract: A streaming database management system may provide support for creating a new continuous query operator for on-the-fly addition of a new query, e.g., a new SQL query and/or new continuous query operator, into a shared continuous query plan. Alternatively, the streaming database management system may associate the new query on-the-fly with an existing continuous query operator, such as a relational operator and expression evaluator, to reuse the existing continuous query operator. In some embodiments, multiple operators are grouped for on-the-fly addition to the shared continuous query plan. Alternatively, the streaming database management system may identify a group of multiple operators in the shared continuous query plan for reuse by the new query.