International Business Machines Corporation

Tobias Kevin Fränzel

Aaron K Baughman

Martin Oberhofer

Oliver Schiller

James L Finnie

Thomas Schwarz

Dennis Butterstein

Vassil Radkov Dimov

Toni Bollinger

Basem Elasioty

Wieland Philipp Hoffmann

Kareem Amin

Stephane Rodet

Cornelius Wiehl

Alexander Merschel

Nehal Dudani

Thomas Friedhelm Böhme

A method, computer system, and a computer program product for storing a graph is provided. The present invention may include providing a key-value store. The present invention may include storing a graph in the key-value store, wherein storing a specific node of the graph in the key-value store comprises: storing, as a key, identifiers of the specific node and of k-hop neighborhood of the specific node, and as value of the key, attribute values of the specific node, wherein the k-hop neighborhood of the specific node comprises a set of neighboring nodes that are reachable from the specific node within k edges.

Storing graph data in a key-value store

Aspects of the invention include techniques for providing a query and data adaptive synopsis table. A non-limiting example method includes building a first synopsis table containing metadata for a database table. Information from queries executed against the database table is collected. The collected information is analyzed, responsive to a number of queries executed against the database table exceeding a query collection threshold, to identify one or more queries for which the first synopsis table was suboptimal. The method includes building, for each of the one or more queries for which the first synopsis table was suboptimal, a second synopsis table.

Query and data adaptive synopsis table

A computer-implemented method for detecting a change in a meta-environment is disclosed. The method comprises collecting historic parameter values from at least one actor being active in the meta-environment, wherein each of the at least one actors has a set of abilities represented by parameters relating to the collected parameter values, collecting current parameter values from the at least one actor being active in the meta-environment, determining weight values of the collected historic parameters and weight values of the collected current parameters, and upon a value of a function of the determined weight values of the historic parameters and the weight values of the collected current parameters being greater than a predefined threshold value, determining a detection of the change in the meta-environment.

Detecting meta-environment changes

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Tuebingen, Germany

Tobias Kevin Fränzel