Abstract: Provided herein are techniques for processing a database query aggregating data. Data tuples of a database object each including a grouping element and a data element are analyzed to determine a length of the data element for each data tuple. A plurality of tables each accommodate a successively greater length for the data element. A corresponding table of the plurality of tables to store each data tuple is determined based on the length of the data element of that data tuple relative to the accommodated lengths of the plurality of tables. Each data tuple in the determined corresponding table is stored to group the data tuples within each of the plurality of tables based on the grouping element, and an indication of corresponding tables containing members for each group is provided. The groups are combined across the plurality of tables to aggregate the data tuples for a database query.

Abstract: Although many techniques provide ways to answer queries very quickly by either avoiding joins and/or aggregation or avoiding expression computations in order to apply filtering predicates, these techniques have significant potential overhead for maintenance, and require a great deal of storage space. The present invention discloses the use of synopsis or zone tables to expressions to provide powerful filtering capabilities to base tables across joins, and aggregations on join results, thus allowing for highly effective region or stride filtering and ordering aggregate ranges to select the most likely candidate tuples for joining to produce top-N or bottom-N result sets for queries.

Abstract: Although many techniques provide ways to answer queries very quickly by either avoiding joins and/or aggregation or avoiding expression computations in order to apply filtering predicates, these techniques have significant potential overhead for maintenance, and require a great deal of storage space. The present invention discloses the use of synopsis or zone tables to expressions to provide powerful filtering capabilities to base tables across joins, and aggregations on join results, thus allowing for highly effective region or stride filtering and ordering aggregate ranges to select the most likely candidate tuples for joining to produce top-N or bottom-N result sets for queries.

Abstract: A database query comprising predicates may be received. Each predicate may operate on database columns. The database query may be determined to comprise strict operators. An upper bound neural network may be defined for calculating an adjacent upper bound and a lower bound neural network may be defined for calculating an adjacent lower bound. The upper bound neural network and the lower bound neural network may be trained using a selected value from data of a database table associated with the database query to be executed through the upper bound neural network and the lower bound neural network. The upper bound neural network and the lower bound neural network may be adjusted by passing in an expected value using an error found in expressions. The adjacent lower bound and the adjacent upper bound may be calculated in response to completion of initial training for the database columns.

Abstract: Embodiments of the present invention provide systems and methods for data management. Synopsis tables have been found to be more effective for maintaining a high level of system performance while answering analytical queries. Synopsis tables, which contain MAX, MIN, and Bloom filter columns, may be modified by dropping ineffective data content within these columns and regenerating dropped data when beneficial. By automatically modifying data, database queries may be optimized.

Abstract: Responding to relational database queries (for example, SQL queries) in a new way. More specifically, qualifying queries are written (for example, written by a human individual) in a way so that a join operation precedes a row limiting operation. Notwithstanding the fact that the join operation precedes the row limiting operation, when responding to the query, machine logic (for example, software) performs the row limiting operation before the join operation. This can improve time and processing efficiency.

Abstract: A database query comprising predicates may be received. Each predicate may operate on database columns. The database query may be determined to comprise strict operators. An upper bound neural network may be defined for calculating an adjacent upper bound and a lower bound neural network may be defined for calculating an adjacent lower bound. The upper bound neural network and the lower bound neural network may be trained using a selected value from data of a database table associated with the database query to be executed through the upper bound neural network and the lower bound neural network. The upper bound neural network and the lower bound neural network may be adjusted by passing in an expected value using an error found in expressions. The adjacent lower bound and the adjacent upper bound may be calculated in response to completion of initial training for the database columns.

Abstract: Embodiments of the present invention provide systems and methods for data management. Synopsis tables have been found to be more effective for maintaining a high level of system performance while answering analytical queries. Synopsis tables, which contain MAX, MIN, and Bloom filter columns, may be modified by dropping ineffective data content within these columns and regenerating dropped data when beneficial. By automatically modifying data, database queries may be optimized.

Abstract: Although many techniques provide ways to answer queries very quickly by either avoiding joins and/or aggregation or avoiding expression computations in order to apply filtering predicates, these techniques have significant potential overhead for maintenance, and require a great deal of storage space. The present invention discloses the use of synopsis or zone tables to expressions to provide powerful filtering capabilities to base tables across joins, and aggregations on join results, thus allowing for highly effective region or stride filtering and ordering aggregate ranges to select the most likely candidate tuples for joining to produce top-N or bottom-N result sets for queries.

Abstract: Merging adjacent rows of a synopsis table so as to increase the effectiveness of the synopsis table regarding data skipping. Adjacent rows for merging are identified based on statistics regarding: (i) queries of the database; (ii) effectiveness of the synopsis table for data skipping; and (iii) usage of predicates in queries of the database. Once merged, the synopsis table is smaller, and more effective with respect to data skipping, while fewer computing resources (administrative, maintenance, memory, clock cycles, storage space, etc.) are needed to process the database queries.

Abstract: Merging adjacent rows of a synopsis table so as to increase the effectiveness of the synopsis table regarding data skipping. Adjacent rows for merging are identified based on statistics regarding: (i) queries of the database; (ii) effectiveness of the synopsis table for data skipping; and (iii) usage of predicates in queries of the database. Once merged, the synopsis table is smaller, and more effective with respect to data skipping, while fewer computing resources (administrative, maintenance, memory, clock cycles, storage space, etc.) are needed to process the database queries.

Abstract: A method, computer program product, and computer system for optimizing query processing is provided. An asynchronously updated index is provided for a main dataset. A time-sequences log of data modifications to the main dataset is provided. A query of the main dataset is received. The main dataset is joined with the time-sequenced log data resulting in a first intermediate result. The query is processed by keeping one or more entries satisfying the query by emulating a function of the asynchronously updated index resulting in a second intermediate result. Updated, deleted dataset entries are deleted from the asynchronously updated index. The query is processed resulting in a third intermediate result. A union of the second intermediate result and third intermediate result is built defining a final result.

Abstract: Techniques are disclosed for generating statistical views in a database system. In one embodiment, a request is received to execute a database workload. One or more constraints pertaining to executing the database workload is retrieved. The database workload is evaluated to generate multiple statistical view candidates. The statistical view candidates are refined based on the one or more constraints. One or more statistical views are then generated based on the refined statistical view candidates.

Abstract: A method, computer program product, and computer system for optimizing query processing is provided. An asynchronously updated index is provided for a main dataset. A time-sequences log of data modifications to the main dataset is provided. A query of the main dataset is received. The main dataset is joined with the time-sequenced log data resulting in a first intermediate result. The query is processed by keeping one or more entries satisfying the query by emulating a function of the asynchronously updated index resulting in a second intermediate result. Updated, deleted dataset entries are deleted from the asynchronously updated index. The query is processed resulting in a third intermediate result. A union of the second intermediate result and third intermediate result is built defining a final result.

Abstract: Various ways of storing data in tabular form such that some records are stored in a row oriented manner and some data is stored in a column oriented manner. The records respectively stored in the row and column oriented manners may, or may not, overlap (in whole or in part. Some embodiments accomplish this dual orientation of data by: (i) using a range partition; (ii) using a union all view command; and/or (iii) using a first table, a staging table and a materialized query table.

Abstract: Although many techniques provide ways to answer queries very quickly by either avoiding joins and/or aggregation or avoiding expression computations in order to apply filtering predicates, these techniques have significant potential overhead for maintenance, and require a great deal of storage space. The present invention discloses the use of synopsis or zone tables to expressions to provide powerful filtering capabilities to base tables across joins, and aggregations on join results, thus allowing for highly effective region or stride filtering and ordering aggregate ranges to select the most likely candidate tuples for joining to produce top-N or bottom-N result sets for queries.

Abstract: Responding to relational database queries (for example, SQL queries) in a new way. More specifically, qualifying queries are written (for example, written by a human individual) in a way so that a join operation precedes a row limiting operation. Notwithstanding the fact that the join operation precedes the row limiting operation, when responding to the query, machine logic (for example, software) performs the row limiting operation before the join operation. This can improve time and processing efficiency.

Abstract: A computer-implemented method includes receiving an artefact and a problem pattern, transforming the artefact into an abstracted artefact structure, and transforming the problem pattern into a query. The query is matched against the abstracted artefact structure. Any matched portions of the abstracted artefact structure are related back to corresponding result portions of the artefact. The corresponding result portions of the artefact are returned. The method may be embodied in a corresponding computer system or computer program product.

Abstract: A computer-implemented method includes receiving an artefact and a problem pattern, transforming the artefact into an abstracted artefact structure, and transforming the problem pattern into a query. The query is matched against the abstracted artefact structure. Any matched portions of the abstracted artefact structure are related back to corresponding result portions of the artefact. The corresponding result portions of the artefact are returned. The method may be embodied in a corresponding computer system or computer program product.

Abstract: Various ways of storing data in tabular form such that some records are stored in a row oriented manner and some data is stored in a column oriented manner. The records respectively stored in the row and column oriented manners may, or may not, overlap (in whole or in part. Some embodiments accomplish this dual orientation of data by: (i) using a range partition; (ii) using a union all view command; and/or (iii) using a first table, a staging table and a materialized query table.