Abstract: A system and method for determining optimal query plans within distributed database system employing table operators for performing analytic operations for storing and processing multi-structured data. The optimization of a query plan proceeds through a collaborative exchange between a database system optimizer, or planner, and a table operator, wherein multiple communications between said optimizer and said table operator are conducted to exchange input and output information relevant to optimizing execution of the query and table operator.

Abstract: A system and method for determining optimal query plans within distributed database system employing table operators for performing analytic operations for storing and processing multi-structured data. The optimization of a query plan proceeds through a collaborative exchange between a database system optimizer, or planner, and a table operator, wherein multiple communications between said optimizer and said table operator are conducted to exchange input and output information relevant to optimizing execution of the query and table operator.

Abstract: A data mashup system having information extraction capabilities for receiving multiple streams of textual data, at least one of which contains unstructured textual data. A repository stores annotators that describe how to analyze the streams of textual data for specified unstructured data components. The annotators are applied to the data streams to identify and extract the specified data components according to the annotators. The extracted data components are tagged to generate structured data components and the specified unstructured data components in the input data streams are replaced with the tagged data components. The system then combines the tagged data from the multiple streams to form a mashup output data stream.

Abstract: A data mashup system having information extraction capabilities for receiving multiple streams of textual data, at least one of which contains unstructured textual data. A repository stores annotators that describe how to analyze the streams of textual data for specified unstructured data components. The annotators are applied to the data streams to identify and extract the specified data components according to the annotators. The extracted data components are tagged to generate structured data components and the specified unstructured data components in the input data streams are replaced with the tagged data components. The system then combines the tagged data from the multiple streams to form a mashup output data stream.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for processing a federated query in a federated database system. A federated query is received at a federated database server. A federated query execution plan is generated based on the received federated query. The federated query execution plan defines one or more source servers of the federated database and a unique subquery to be executed on each of the source servers. The subqueries are distributed to the source servers in accordance with the federated query execution plan. The respective subqueries are executed asynchronously at the source servers. The subquery results are passed to a first designated source server defined in the federated query execution plan. The subquery results are joined and aggregated at the first designated source server into a final query result. The final query result is returned to the federated database server.

Abstract: Methods and systems for improving a data transformation operation that converts a source data instance containing repeating elements into a target data instance having a user-specified structure, based solely on a user's specification of a target template. The methods and systems derive and calculate sub-iteration contexts by applying a selected heuristic to the source data instance and the target template, and use these sub-iteration contexts to create a target data instance having a repeating structure that agrees with the user-specified target template. The methods and systems can be customized by the selection of heuristic, and by the specification of explicit sub-iteration contexts that may override the derived contexts.

Abstract: A method and system for automatically and adaptively determining query execution plans for parametric queries. A first classifier trained by an initial set of training points is generated. A query workload and/or database statistics are dynamically updated. A new set of training points is collected off-line. Using the new set of training points, the first classifier is modified into a second classifier. A database query is received at a runtime subsequent to the off-line phase. The query includes predicates having parameter markers bound to actual values. The predicates are associated with selectivities. A mapping of the selectivities into a plan determines the query execution plan. The determined query execution plan is included in an augmented set of training points, where the augmented set includes the initial set and the new set.

Abstract: Methods and systems for improving a data transformation operation that converts a source data instance containing repeating elements into a target data instance having a user-specified structure, based solely on a user's specification of a target template. The methods and systems derive and calculate sub-iteration contexts by applying a selected heuristic to the source data instance and the target template, and use these sub-iteration contexts to create a target data instance having a repeating structure that agrees with the user-specified target template. The methods and systems can be customized by the selection of heuristic, and by the specification of explicit sub-iteration contexts that may override the derived contexts.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for processing a federated query in a federated database system. A federated query is received at a federated database server. A federated query execution plan is generated based on the received federated query. The federated query execution plan defines one or more source servers of the federated database and a unique subquery to be executed on each of the source servers. The subqueries are distributed to the source servers in accordance with the federated query execution plan. The respective subqueries are executed asynchronously at the source servers. The subquery results are passed to a first designated source server defined in the federated query execution plan. The subquery results are joined and aggregated at the first designated source server into a final query result. The final query result is returned to the federated database server.

Abstract: A method and system for automatically and adaptively determining query execution plans for parametric queries. A first classifier trained by an initial set of training points is generated. A query workload and/or database statistics are dynamically updated. A new set of training points is collected off-line. Using the new set of training points, the first classifier is modified into a second classifier. A database query is received at a runtime subsequent to the off-line phase. The query includes predicates having parameter markers bound to actual values. The predicates are associated with selectivities. A mapping of the selectivities into a plan determines the query execution plan. The determined query execution plan is included in an augmented set of training points, where the augmented set includes the initial set and the new set.

Abstract: A method for automatically and adaptively determining query execution plans for parametric queries. A first classifier trained by an initial set of training points is generated using a set of random decision trees (RDTs). A query workload and/or database statistics are dynamically updated. A new set of training points collected off-line is used to modify the first classifier into a second classifier. A database query is received at a runtime subsequent to the off line phase. The query includes predicates having parameter markers bound to actual values. The predicates are associated with selectivities. The query execution plan is determined by identifying an optimal average of posterior probabilities obtained across a set of RDTs and mapping the selectivities to a plan. The determined query execution plan is included in an augmented set of training points that includes the initial set and the new set.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: A method, system, and computer program product to make query processing more robust in the face of optimization errors. The invention validates the statistics and assumptions used for compiling a query as the query is executed and, when necessary, progressively re-optimizes the query in mid-execution based on the knowledge learned during its partial execution. The invention selectively places a number of CHECK operators in a query execution plan to validate the optimizer's cardinality estimates against actual cardinalities. Errors beyond a threshold trigger re-optimization, and the optimizer decides whether the old plan is still optimal and whether to re-use previously computed results. The invention addresses arbitrary SQL queries whose plans can contain sub-queries, updates, trigger checking, and view maintenance operations.

Abstract: A reverse routing system optimizes execution of a query that accesses data stored in one or more materialized query tables in a database of a computer system. The system receives a query directly referencing the materialized query table. The system identifies the referenced materialized query tables in a catalogue of materialized query tables and a defining query associated with the referenced materialized query table. The system substitutes the defining query for the referenced materialized query table in the received query. The system adds the referenced materialized query table to the set of eligible materialized query tables that are selected using query matching algorithms so that they can be considered for routing by the query optimizer.

Abstract: A system, method and computer readable medium for sampling data from a relational database are disclosed, where an information processing system chooses rows from a table in a relational database for sampling, wherein data values are arranged into rows, rows are arranged into pages, and pages are arranged into tables. Pages are chosen for sampling according to a probability P and rows in a selected page are chosen for sampling according to a probability R, so that the overall probability of choosing a row for sampling is Q=PR. The probabilities P and R are based on the desired precision of estimates computed from a sample, as well as processing speed. The probabilities P and R are further based on either catalog statistics of the relational database or a pilot sample of rows from the relational database.

Abstract: A system, method and computer readable medium for sampling data from a relational database are disclosed, where an information processing system chooses rows from a table in a relational database for sampling, wherein data values are arranged into rows, rows are arranged into pages, and pages are arranged into tables. Pages are chosen for sampling according to a probability P and rows in a selected page are chosen for sampling according to a probability R, so that the overall probability of choosing a row for sampling is Q=PR. The probabilities P and R are based on the desired precision of estimates computed from a sample, as well as processing speed. The probabilities P and R are further based on either catalog statistics of the relational database or a pilot sample of rows from the relational database.

Abstract: A system and method for a relational database system for identifying star joins in a query and for breaking the query down for bitmap ANDing. The fact table of the star join is located, and cycles between and within dimension tables are broken. Then, the minimal set of tables necessary to execute the star join is identified, and the dimension tables that should appear in the bitmap ANDing plan are also identified. A bitmap ANDing plan is then generated, or, if the query does not qualify for bitmap ANDing, a conventional execution plan is generated.

Abstract: An automated methodology, and an apparatus for practicing the methodology, which enables the power and flexibility inherent in shared nothing parallel database systems (MPP) to be utilized on complex queries which have, heretofore, contained query elements requiring local computation or local coordination of data computation performed across the nodes of the distributed system. The present invention provides these features and advantages by identifying and marking the subgraphs containing these types of query elements as "no TQ zones" in the preparation phase prior to optimization. When the optimizer sees the markings, it builds a plan that will force the computation of the marked subgraphs to be in the same section. This preparation phase also provides the partitioning information for all inputs to the "no TQ zones". This allows the bottom-up optimizer to correctly plan the partitioning for the "no TQ zones".

Abstract: Unwieldy star/join queries are performed more efficiently using a filtered fact table. Suitable queries include star/join queries with a large fact table joined with multiple subsidiary dimension tables, where indices exist over fact table join columns. The query is analyzed to prepare a query plan for the dimension table accesses. This plan is supplemented by adding nested loop join operations, where the inner table is a dimension table plan and the outer table is an index scan performed over a fact table index of the join column with the dimension table. The plan is also supplemented by filtering records resulting from the nested loop joins using a sequence of dynamic bit vectors, ultimately yielding a list of probable fact table records. The plan is further supplemented by fetching these records to construct a distilled fact which is used, instead of the large original table, to execute the query in considerably less time.