Gerrit Kazmaier

DBSCAN clustering analyses can be improved by pre-processing of a data set using a Hilbert curve to intelligently identify the centers for initial partitional analysis by a partitional clustering algorithm such as CLARANS. Partitions output by the partitional clustering algorithm can be process by DBSCAN running in parallel before intermediate cluster results are merged.

A query of spatial data is received by a database comprising a columnar data store storing data in a column-oriented structure. Thereafter, a minimal bounding rectangle associated with the query is identified using a tree-order scanning technique. A spatial data set that corresponds to the received query is then mapped to the physical storage in the database using the identified minimal bounding rectangle. Next, the spatial data set is then retrieved. Related apparatus, systems, techniques and… Mehr zeigen

A query of spatial data is received by a database comprising a columnar data store storing data in a column-oriented structure. Thereafter, a minimal bounding rectangle associated with the query is identified using a tree-order scanning technique. A spatial data set that corresponds to the received query is then mapped to the physical storage in the database using the identified minimal bounding rectangle. Next, the spatial data set is then retrieved. Related apparatus, systems, techniques and articles are also described. Weniger anzeigen

According to one aspect of systems and methods for dynamic recreation of multidimensional analytical data, lost sets of calculation scenarios that provide multidimensional analytical data results after aggregations and transformations of the multidimensional analytical data are recreated in the volatile storage of an in-memory computing engine. A multidimensional analytical data view (MDAV) compiler is triggered to read the MDAV metadata stored in an intermediate buffer in the MDAV compiler… Mehr zeigen

According to one aspect of systems and methods for dynamic recreation of multidimensional analytical data, lost sets of calculation scenarios that provide multidimensional analytical data results after aggregations and transformations of the multidimensional analytical data are recreated in the volatile storage of an in-memory computing engine. A multidimensional analytical data view (MDAV) compiler is triggered to read the MDAV metadata stored in an intermediate buffer in the MDAV compiler. The read MDAV metadata is compiled into a calculation scenario including calculation view metadata. The calculation view metadata is stored in the intermediate buffer. The recreated set of calculation scenarios is deployed on the in-memory computing engine. Weniger anzeigen

A database query of point data among two or more axes of a database is received. The database stores point data in distinct integer vectors with a shared dictionary. Thereafter, the dictionary is scanned to determine boundaries for each axis specified by the query. In response, results characterizing data responsive to the query within the determined boundaries for each axis are returned. Related apparatus, systems, techniques and articles are also described.