Abstract: A method for optimizing query compilation by tuning memory across a database cluster is provided. The method may include receiving, by a global memory tuner, memory configuration information from a plurality of nodes within the database cluster. The method may also include determining a node within the plurality of nodes having a least available memory value relative to a remainder of nodes within the plurality of nodes based on the received memory configuration information. The method may then include calculating a globally tuned memory value based on a memory value associated with the determined node. The method may further include determining a memory distribution based on the calculated globally tuned memory value. The method may also include sending the determined memory distribution to the plurality of nodes.

Abstract: A method, computer system, and a computer program product for resource scaling is provided. The present invention may include receiving a request for resources. The present invention may include receiving a request for a plurality of resources from a virtual device. The present invention may then include estimating a resource allocation based on a predetermined level of service based on the received request. The present invention may also include estimating a benefit curve of a workload for a plurality of tiers of resources based on the estimated resource allocation. The present invention may further include estimating a performance cost of the workload for the plurality of tiers of resources based on the estimated benefit curve.

Abstract: A current minimum memory requirement for each memory consumer of one or more memory consumers of a primary database system is received. A current memory allocation for a standby database system is received. A set of benefit-to-cost metrics is received. A benefit-to-cost metric is a measure of whether each memory consumer would benefit or would not benefit from additional memory. The set of benefit-to-cost metrics is applied to the standby database system to define an upper bound memory allocation of the standby database system to function in the event of a failover from the primary database system. A scaling factor is determined. In response to receiving an indication of a failover of the primary database system to the standby database system, a ramp up of the standby database system is monitored. The ramp up of the standby database system uses the set of benefit-to-cost metrics and the determined scaling factor.

Abstract: A current minimum memory requirement for each memory consumer of one or more memory consumers of a primary database system is received. A current memory allocation for a standby database system is received. A set of benefit-to-cost metrics is received. A benefit-to-cost metric is a measure of whether each memory consumer would benefit or would not benefit from additional memory. The set of benefit-to-cost metrics is applied to the standby database system to define an upper bound memory allocation of the standby database system to function in the event of a failover from the primary database system. A scaling factor is determined. In response to receiving an indication of a failover of the primary database system to the standby database system, a ramp up of the standby database system is monitored. The ramp up of the standby database system uses the set of benefit-to-cost metrics and the determined scaling factor.

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: 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: 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 for optimizing query compilation by tuning memory across a database cluster is provided. The method may include receiving, by a global memory tuner, memory configuration information from a plurality of nodes within the database cluster. The method may also include determining a node within the plurality of nodes having a least available memory value relative to a remainder of nodes within the plurality of nodes based on the received memory configuration information. The method may then include calculating a globally tuned memory value based on a memory value associated with the determined node. The method may further include determining a memory distribution based on the calculated globally tuned memory value. The method may also include sending the determined memory distribution to the plurality of nodes.

Abstract: A method for optimizing query compilation by tuning memory across a database cluster is provided. The method may include receiving, by a global memory tuner, memory configuration information from a plurality of nodes within the database cluster. The method may also include determining a node within the plurality of nodes having a least available memory value relative to a remainder of nodes within the plurality of nodes based on the received memory configuration information. The method may then include calculating a globally tuned memory value based on a memory value associated with the determined node. The method may further include determining a memory distribution based on the calculated globally tuned memory value. The method may also include sending the determined memory distribution to the plurality of nodes.

Abstract: A current minimum memory requirement for each memory consumer of one or more memory consumers of a primary database system is received. A current memory allocation for a standby database system is received. A set of benefit-to-cost metrics is received. A benefit-to-cost metric is a measure of whether each memory consumer would benefit or would not benefit from additional memory. The set of benefit-to-cost metrics is applied to the standby database system to define an upper bound memory allocation of the standby database system to function in the event of a failover from the primary database system. A scaling factor is determined. In response to receiving an indication of a failover of the primary database system to the standby database system, a ramp up of the standby database system is monitored. The ramp up of the standby database system uses the set of benefit-to-cost metrics and the determined scaling factor.

Abstract: A current minimum memory requirement for each memory consumer of one or more memory consumers of a primary database system is received. A current memory allocation for a standby database system is received. A set of benefit-to-cost metrics is received. A benefit-to-cost metric is a measure of whether each memory consumer would benefit or would not benefit from additional memory. The set of benefit-to-cost metrics is applied to the standby database system to define an upper bound memory allocation of the standby database system to function in the event of a failover from the primary database system. A scaling factor is determined. In response to receiving an indication of a failover of the primary database system to the standby database system, a ramp up of the standby database system is monitored. The ramp up of the standby database system uses the set of benefit-to-cost metrics and the determined scaling factor.

Abstract: A computer-implemented method includes assigning a threshold value to a memory consumer and assigning a bias value to the threshold value. The ability to free memory of the consumer by the consumer is monitored. In response to a determination to reclaim the memory, the consumer is directed to reclaim the memory. The threshold value is transformed responsive to whether the reclaiming exhibits at least one of time-out or completion of reclaim after a predetermined time. Per memory consumer control values are updated and the memory is logically partitioned according to a defined ratio into at least a first portion and a second portion. Subsequent to directing the consumer to reclaim the memory, the memory is reclaimed from the second portion and, subsequently, the second portion is replenished from the first portion in a manner that maintains the defined ratio. A corresponding computer system and computer program product are also disclosed.

Abstract: A computer-implemented method includes assigning a threshold value to a memory consumer and assigning a bias value to the threshold value. The ability to free memory of the consumer by the consumer is monitored. In response to a determination to reclaim the memory, the consumer is directed to reclaim the memory. The threshold value is transformed responsive to whether the reclaiming exhibits at least one of time-out or completion of reclaim after a predetermined time. Per memory consumer control values are updated and the memory is logically partitioned according to a defined ratio into at least a first portion and a second portion. Subsequent to directing the consumer to reclaim the memory, the memory is reclaimed from the second portion and, subsequently, the second portion is replenished from the first portion in a manner that maintains the defined ratio. A corresponding computer system and computer program product are also disclosed.

Abstract: The method includes identifying at least one of a minimum value, a maximum value, and a Bloom filter value for a row of data in a metadata table, wherein the metadata table contains metadata corresponding to a row of data in a main table. The method includes adjusting at least one of an identified first minimum value to a second minimum value, an identified first maximum value to a second maximum value, and an identified first Bloom filter value to a second Bloom filter value.

Abstract: The method includes identifying at least one of a minimum value, a maximum value, and a Bloom filter value for a row of data in a metadata table, wherein the metadata table contains metadata corresponding to a row of data in a main table. The method includes adjusting at least one of an identified first minimum value to a second minimum value, an identified first maximum value to a second maximum value, and an identified first Bloom filter value to a second Bloom filter value.