Abstract: A tiered machine learning-based infrastructure comprises a first machine learning (ML) tier configured to execute within an enterprise network environment and that learns statistics for a set of use cases locally, and to alert deviations from the learned distributions. Use cases typically are independent from one another. A second machine learning tier executes external to the enterprise network environment and provides further learning support, e.g., by determining a correlation among multiple independent use cases that are running locally in the first tier. Preferably, the second tier executes in a cloud compute environment for scalability and performance.

Abstract: A tiered machine learning-based infrastructure comprises a first machine learning (ML) tier configured to execute within an enterprise network environment and that learns statistics for a set of use cases locally, and to alert deviations from the learned distributions. Use cases typically are independent from one another. A second machine learning tier executes external to the enterprise network environment and provides further learning support, e.g., by determining a correlation among multiple independent use cases that are running locally in the first tier. Preferably, the second tier executes in a cloud compute environment for scalability and performance.

Abstract: A method and system for distributing tasks from an external application among concurrent database application server instances in a database system for optimum load balancing, based on consensus among the instances. Each application instance identifies a task partition ownership by those in a membership group based on a time window and generates a new membership group and partition ownership based on the current partition ownership. The instance makes the new membership group and partition ownership known to other members by recoding them in the membership table and partition map. Each participation by an instance in the membership group is identified by a random number. The new membership group and partition ownership are generated and adjusted based on an average partition allocation to achieve consensus among the instances.

Abstract: A method and system for distributing tasks from an external application among concurrent database application server instances in a database system for optimum load balancing, based on consensus among the instances. Each application instance identifies a task partition ownership by those in a membership group based on a time window and generates a new membership group and partition ownership based on the current partition ownership. The instance makes the new membership group and partition ownership known to other members by recoding them in the membership table and partition map. Each participation by an instance in the membership group is identified by a random number. The new membership group and partition ownership are generated and adjusted based on an average partition allocation to achieve consensus among the instances.

Abstract: A method and system for distributing tasks from an external application among concurrent database application server instances in a database system for optimum load balancing, based on consensus among the instances. Each application instance identifies a task partition ownership by those in a membership group based on a time window and generates a new membership group and partition ownership based on the current partition ownership. The instance makes the new membership group and partition ownership known to other members by recoding them in the membership table and partition map. Each participation by an instance in the membership group is identified by a random number. The new membership group and partition ownership are generated and adjusted based on an average partition allocation to achieve consensus among the instances.

Abstract: A method and system for distributing tasks from an external application among concurrent database application server instances in a database system for optimum load balancing, based on consensus among the instances. Each application instance identifies a task partition ownership by those in a membership group based on a time window and generates a new membership group and partition ownership based on the current partition ownership. The instance makes the new membership group and partition ownership known to other members by recoding them in the membership table and partition map. Each participation by an instance in the membership group is identified by a random number. The new membership group and partition ownership are generated and adjusted based on an average partition allocation to achieve consensus among the instances.

Abstract: Provided are techniques for partitioning a physical index into one or more physical partitions; assigning each of the one or more physical partitions to a node in a cluster of nodes; for each received document, assigning an assigned-doc-ID comprising an integer document identifier; and, in response to assigning the assigned-doc-ID to a document, determining a cut-off of assignment of new documents to a current virtual-index-epoch comprising a first set of physical partitions and placing the new documents into a new virtual-index-epoch comprising a second set of physical partitions by inserting each new document to a specific one of the physical partitions in the second set using one or more functions that direct the placement based on one of the assigned-doc-id, a field value derived from a set of fields obtained from the document, and a combination of the assigned-doc-id and the field value.

Abstract: A method and system for distributing tasks from an external application among concurrent database application server instances in a database system for optimum load balancing, based on consensus among the instances. Each application instance identifies a task partition ownership by those in a membership group based on a time window and generates a new membership group and partition ownership based on the current partition ownership. The instance makes the new membership group and partition ownership known to other members by recoding them in the membership table and partition map. Each participation by an instance in the membership group is identified by a random number. The new membership group and partition ownership are generated and adjusted based on an average partition allocation to achieve consensus among the instances.

Abstract: A system for improved data sharing within a cluster of nodes having a database management system. The system defines a virtual replicated table as being useable in a hybrid of a shared-cache and shared-nothing architecture. The virtual replicated table is a physically single table sharable among a plurality of cluster nodes for data read operations and not sharable with other cluster nodes for data modification operations. Default owner node is assigned for each virtual replicated table to ensure the page validity and provide requested pages to the requesting node.

Abstract: A method and system for distributing tasks from an external application among concurrent database application server instances in a database system for optimum load balancing, based on consensus among the instances. Each application instance identifies a task partition ownership by those in a membership group based on a time window and generates a new membership group and partition ownership based on the current partition ownership. The instance makes the new membership group and partition ownership known to other members by recoding them in the membership table and partition map. Each participation by an instance in the membership group is identified by a random number. The new membership group and partition ownership are generated and adjusted based on an average partition allocation to achieve consensus among the instances.

Abstract: A system for improved data sharing within a cluster of nodes having a database management system. The system defines a virtual replicated table as being useable in a hybrid of a shared-cache and shared-nothing architecture. The virtual replicated table is a physically single table sharable among a plurality of cluster nodes for data read operations and not sharable with other cluster nodes for data modification operations. Default owner node is assigned for each virtual replicated table to ensure the page validity and provide requested pages to the requesting node.

Abstract: A method for improved data sharing within a cluster of nodes having a database management system. The method defines a virtual replicated table as being useable in a hybrid of a shared-cache and shared-nothing architecture. The virtual replicated table is a physically single table sharable among a plurality of cluster nodes for data read operations and not sharable with other cluster nodes for data modification operations. Default owner node is assigned for each virtual replicated table to ensure the page validity and provide requested pages to the requesting node.

Abstract: A method, apparatus and article of manufacture, implementing the method, accesses rows in a range-clustered table in a database management system. A table stores data that is organized into rows and columns. At least one column is designated as a key column. A particular row in the table is accessed based on a relationship between a specified key value and a predetermined range of key values associated with the key column. The table has slots for storing rows, and the slots are organized in accordance with the values of the predetermined range.

Abstract: A method, apparatus and article of manufacture, implementing the method, accesses rows in a range-clustered table in a database management system. A table stores data that is organized into rows and columns. At least one column is designated as a key column. A particular row in the table is accessed based on a relationship between a specified key value and a predetermined range of key values associated with the key column. The table has slots for storing rows, and the slots are organized in accordance with the values of the predetermined range.

Abstract: A computer implemented method for generating a response to a join. Two tables are divided into fragments. A join fragment map identifies, for each respective fragment from the first table, the fragments from the second table which contain a record that satisfies the join predicate with a record from the respective fragment from the first table. The map is used to eliminate fragments which cannot satisfy the join predicate.