Abstract: Embodiments are disclosed for a method. The method includes receiving a plurality of local deltas for a query execution against a corresponding plurality of data sources hosted by a corresponding plurality of distributed nodes of a dynamic distributed network. The method also includes generating a combined delta by combining the local deltas. Additionally, the method includes generating a determined delta result by performing additional processing on the combined delta. Further, the method includes providing the determined delta for one of the distributed nodes.

Abstract: Embodiments are disclosed for a method. The method includes parsing a distributed database query into component queries corresponding to distributed nodes. The method also includes matching component queries to central cache to determine whether the component queries can be satisfied. This matching generates matched and unmatched component queries. The method further includes transforming the matched component query to a cache query and local delta query for a first node. Additionally, the method includes executing the cache query to generate a cache result. Also, the method includes providing the local delta query for the first node to generate a local delta. Further, the method includes providing the unmatched component query for a second node to generate a remote result. The method also includes generating a global delta based on the local delta. The method additionally includes generating a result by combining the cache result, local delta, and remote result.

Abstract: Embodiments are disclosed for a method. The method includes parsing a distributed database query into component queries corresponding to distributed nodes. The method also includes matching component queries to central cache to determine whether the component queries can be satisfied. This matching generates matched and unmatched component queries. The method further includes transforming the matched component query to a cache query and local delta query for a first node. Additionally, the method includes executing the cache query to generate a cache result. Also, the method includes providing the local delta query for the first node to generate a local delta. Further, the method includes providing the unmatched component query for a second node to generate a remote result. The method also includes generating a global delta based on the local delta. The method additionally includes generating a result by combining the cache result, local delta, and remote result.

Abstract: Embodiments are disclosed for a method. The method includes receiving a plurality of local deltas for a query execution against a corresponding plurality of data sources hosted by a corresponding plurality of distributed nodes of a dynamic distributed network. The method also includes generating a combined delta by combining the local deltas. Additionally, the method includes generating a determined delta result by performing additional processing on the combined delta. Further, the method includes providing the determined delta for one of the distributed nodes.

Abstract: A method, system and computer program product includes receiving and parsing an SQL query, identifying at least one common sub expression, or sub-query, or combination thereof, used multiple times within the SQL query, constructing for the at least one common sub expression, or sub-query, or combination thereof, a query execution plan that maintains as part of an initial result set a bit vector for a fact table, storing a result bit vector and an indicator that tracks a last valid tuple processed to produce the result bit vector when a TEMP operation is indicated in the query execution plan, reassessing a TEMP result in other portions of the query execution plan, priming a list of tuples using the TEMP result, and retrieving respective columns for further processing in the query execution plan.

Abstract: A method, system and computer program product includes receiving and parsing an SQL query, identifying at least one common sub expression, or sub-query, or combination thereof, used multiple times within the SQL query, constructing for the at least one common sub expression, or sub-query, or combination thereof, a query execution plan that maintains as part of an initial result set a bit vector for a fact table, storing a result bit vector and an indicator that tracks a last valid tuple processed to produce the result bit vector when a TEMP operation is indicated in the query execution plan, reassessing a TEMP result in other portions of the query execution plan, priming a list of tuples using the TEMP result, and retrieving respective columns for further processing in the query execution plan.

Abstract: Embodiments of the invention provide a method for reducing stack space consumption via a head-call optimization. When compiling the source code of a computer application, a compiler application may be configured to analyze program flow to identify a “head-call” within any functions included in the program source code. Once identified, the “head-call” may be removed during program compilation. Doing so may reduce the number of elements pushed onto a program's stack space during program execution.

Abstract: The scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: The scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: Embodiments of the invention provide a method for reducing stack space consumption via a head-call optimization. When compiling the source code of a computer application, a compiler application may be configured to analyze program flow to identify a “head-call” within any functions included in the program source code. Once identified, the “head-call” may be removed during program compilation. Doing so may reduce the number of elements pushed onto a program's stack space during program execution.

Abstract: In an information retrieval system, a query optimization method transforms maximum or minimum function aggregation predicates on a non-indexed column into a single sort function. The method evaluates the query to identify a table and a predicate equating a column of the table to a sub-query that applies a maximum or minimum aggregation function to the column to return an aggregate value for the column. The aggregate value is used for selecting rows from the table to produce a query result. A determination is then made whether an index has not been created using the column of the table. In response to these steps of evaluating and determining, the method reforms the query as a sort function on the column. The sort function scans the table once to provide the query result.

Abstract: The scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: A method for the scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: The scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: A method, system, and data structure for the scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: An information retrieval system is adapted to process a query having an associated plan that includes applying predicates comprising local predicates and a join predicate, to at least two tables. Index ANDing is used to construct a filter for filtering a first of the tables in accordance with the local predicates. The join predicate is applied to the tables for determining row identifiers of rows satisfying the join predicate. The row identifiers are used to probe the filter for determining whether the rows satisfying the join predicate also satisfy the local predicates. The rows that satisfy both the join and local predicates are fetched and the join predicate is completed. Results of the join predicate are then returned.

Abstract: The present system improves the performance of a query in a database system when a plan for the query comprises sorting an input that is at least partially sorted such that a slow materialization sort can be applied. The invention applies the slow materialization sort by determining a sequence of subsets in accordance with the partially sorted input. As each of the subsets is determined, the subset is output for further processing. Advantageously, the invention reduces the waiting period for obtaining results from a sorting operation under certain circumstances.

Abstract: A method, system, and data structure for the scaling down of data is provided. At least two blocks of transformed data samples representing at least two blocks of original data samples are received. One of at least two tables of constants is selected wherein each table of constants is capable of reducing the number of transformed data samples by a different factor. The constants taken from the selected table are applied to the at least two blocks of transformed data samples to produce one block of transformed data samples representing one block of final data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale down factor. Scaling down by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: A method, system, and data structure for the scaling up of data is provided. A block of transformed data samples is received wherein the transformed data samples represent original data samples. One of at least two tables of constants is selected wherein each table of constants is capable of increasing the number of data samples by a different factor. The constants taken from the selected table are applied to the block of transformed data samples to produce at least two blocks of transformed data samples representing at least two blocks of original data samples. The data is processed one dimension at a time by multiplying the data in one dimension with selected constants taken from previously developed tables corresponding to the desired scale up factor. Scaling up by different factors in each dimension as well as scaling down in one dimension and scaling up in the other dimension may be achieved.

Abstract: The present system improves the performance of a query in a database system when a plan for the query comprises sorting an input that is at least partially sorted such that a slow materialization sort can be applied. The invention applies the slow materialization sort by determining a sequence of subsets in accordance with the partially sorted input. As each of the subsets is determined, the subset is output for further processing. Advantageously, the invention reduces the waiting period for obtaining results from a sorting operation under certain circumstances.