Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: A workload specification is obtained for the database. Based on the workload specification, candidate ones of the tables are identified and ranked. Compression impact is evaluated for the candidate ones of the tables. A design for the database is developed, specifying at least one of: (i) which of the tables should be compressed, and (ii) which of the tables should not be compressed.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: A system and method of evaluating queries in distributed databases with MQTs comprises deriving MQTs; replicating the derived MQTs from a local server to at least one remote server; and distributing data and replicated derived MQTs to a plurality of other remote servers, wherein the distributing increases overall query execution efficiency. The databases may comprise heterogeneous databases. The query execution efficiency comprises observed response time at a frontend database and associated costs comprising computational central processing unit costs, input/output costs, and network communication costs. All of the associated costs comprise statistically estimated costs. The method further comprises running a MQT advisor at a frontend database, and considering the costs of at least one MQT placed at the frontend database. The method further comprises running a MQT advisor at a non-frontend database.

Abstract: A workload specification is obtained for the database. Based on the workload specification, candidate ones of the tables are identified and ranked. Compression impact is evaluated for the candidate ones of the tables. A design for the database is developed, specifying at least one of: (i) which of the tables should be compressed, and (ii) which of the tables should not be compressed.

Abstract: A workload specification is obtained for the database. Based on the workload specification, candidate ones of the tables are identified and ranked. Compression impact is evaluated for the candidate ones of the tables. A design for the database is developed, specifying at least one of: (i) which of the tables should be compressed, and (ii) which of the tables should not be compressed.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: A workload specification, detailing specific queries and a frequency of execution of each of the queries, and a set of partitions, are obtained for the database, as inputs. A number of candidate tables are identified for the database, the tables having a plurality of attributes. A chosen attribute is allocated for each of the tables, to obtain a set of tables and a set of appropriate partitions for each of the tables.

Abstract: The present invention provides a method, system and program for optimizing compression of a workload processed by a database management system. In an embodiment of the present invention a method of optimizing the compression of database workloads is provided. Initially, an estimate of a cost of execution for each query according to a defined metric such as execution time or memory consumption is determined. A sub-set of queries is then selected from the workload in order of the most costly to least costly relative to the defined metric for compression according to either a predetermined compression threshold percentage or a threshold percentage derived from an allotted workload execution time. Compression is then performed on the selected sub-set of queries (i.e. those that will benefit the most from the compression) to achieve a net beneficial trade-off between the cost of workload compression and the cost of workload execution.