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 an embodiment, a method for distributing and processing streams over wide area networks comprises receiving, at a unified data processing node, a continuous query; determining a parallel portion of the continuous query; sending the parallel portion to a plurality of distributed data processing nodes located in a plurality of data centers; at each distributed node in the plurality of distributed nodes, locally executing the parallel portion against independent data partitions, producing a partial summary data, sending the partial summary data to the unified node; continuously receiving, at the unified node, in real-time, the partial summary data.

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: A local database cache enabling persistent, adaptive caching of either full or partial content of a remote database is provided. Content of tables comprising a local cache database is defined on per-table basis. A table is either: defined declaratively and populated in advance of query execution, or is determined dynamically and asynchronously populated on-demand during query execution. Based on a user input query originally issued against a remote DBMS and referential cache constraints between tables in a local database cache, a Janus query plan, comprising local, remote, and probe query portions is determined. A probe query portion of a Janus query plan is executed to determine whether up-to-date results can be delivered by the execution of a local query portion against a local database cache, or whether it is necessary to retrieve results from a remote database by executing a remote query portion of Janus query plan.

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.

Abstract: A local database cache enabling persistent, adaptive caching of either full or partial content of a remote database is provided. Content of tables comprising a local cache database is defined on per-table basis. A table is either: defined declaratively and populated in advance of query execution, or is determined dynamically and asynchronously populated on-demand during query execution. Based on a user input query originally issued against a remote DBMS and referential cache constraints between tables in a local database cache, a Janus query plan, comprising local, remote, and probe query portions is determined. A probe query portion of a Janus query plan is executed to determine whether up-to-date results can be delivered by the execution of a local query portion against a local database cache, or whether it is necessary to retrieve results from a remote database by executing a remote query portion of Janus query plan.

Abstract: A local database cache enabling persistent, adaptive caching of either full or partial content of a remote database is provided. Content of tables comprising a local cache database is defined on per-table basis. A table is either: defined declaratively and populated in advance of query execution, or is determined dynamically and asynchronously populated on-demand during query execution. Based on a user input query originally issued against a remote DBMS and referential cache constraints between tables in a local database cache, a Janus query plan, comprising local, remote, and probe query portions is determined. A probe query portion of a Janus query plan is executed to determine whether up-to-date results can be delivered by the execution of a local query portion against a local database cache, or whether it is necessary to retrieve results from a remote database by executing a remote query portion of Janus query plan.

Abstract: Provided is a method, system, and an article of manufacture for transferring structured data between different data stores. Data stores include a type identifier with every instance of a structured data type. A typeID-typeName map within each data store includes the mapping between the type identifiers and the type names of the structured data types. The typeID-typeName map is sent as metadata while transferring data from a source database to a target database. An application replaces the type identifiers of the source database with the corresponding type identifiers of the target database.

Abstract: A local database cache enabling persistent, adaptive caching of either full or partial content of a remote database is provided. Content of tables comprising a local cache database is defined on per-table basis. A table is either: defined declaratively and populated in advance of query execution, or is determined dynamically and asynchronously populated on-demand during query execution. Based on a user input query originally issued against a remote DBMS and referential cache constraints between tables in a local database cache, a Janus query plan, comprising local, remote, and probe query portions is determined. A probe query portion of a Janus query plan is executed to determine whether up-to-date results can be delivered by the execution of a local query portion against a local database cache, or whether it is necessary to retrieve results from a remote database by executing a remote query portion of Janus query plan.

Abstract: A method, apparatus, and article of manufacture for providing to a signature hash for checking versions of abstract data types. An identifier is constructed for the abstract data type that is substantially unique to the abstract data type, wherein the identifier comprises a concatenation of various attributes for the abstract data type. The constructed identifier is hashed to generate a signature hash value for the abstract data type, which is then stored both in the database and a class definition for the abstract data type. When the class definition is instantiated as a library function, it accesses the abstract data type from the database, and compares the signature hash value from the database and the signature hash value from the class definition in order to verify that the class definition is not outdated. The class definition is outdated when the abstract data type has been altered without the signature hash value being re-generated and re-stored in the database and the class definition.

Abstract: Provided is a method, system, and an article of manufacture for transferring structured data between different data stores. Data stores include a type identifier with every instance of a structured data type. A typeID-typeName map within each data store includes the mapping between the type identifiers and the type names of the structured data types. The typeID-typeName map is sent as metadata while transferring data from a source database to a target database. An application replaces the type identifiers of the source database with the corresponding type identifiers of the target database.

Abstract: A method, apparatus, and article of manufacture for providing for persistence of Java™ objects. A Java™ object is instantiated from its corresponding Java™ class definition and then loaded into a Java™ virtual machine. The class definition corresponding to the Java™ object can be derived using either the Java™ Reflection API. Once the class definition is derived, it can be used to inspect the contents of the Java™ object. A structured type instance is then generated from the inspected contents of the Java™ object, wherein the structured type instance is stored in a column of a table of a relational database managed by a relational database management system. As a result of these steps, the Java™ object is persistently stored in the database, yet the persistence semantics for storing the object are not specified as part of the class definition of the object, which means that the persistence semantics are orthogonal to the class definition.