Sap Se

Sap Ag

Gerrit Simon Kazmaier

Lars Volker

Christoph Weyerhaeuser

Tobias Mindnich

Daniel Baeumges

Hinnerk Gildhoff

Tim Grouisborn

Edward-Robert Tyercha

Isil Pekel

Ulrich Bestfleisch

Sebastian Schroetel

Nadine Sachs

Boris Gruschko

Florian Foebel

Nico Licht

Christian Lahmer

Torsten Abraham

Marcus Lieberenz

Baré Said

Wolfgang Pfeifer

Udo Peter Klein

Gregor Karl Frey

Jan Teichmann

Reinhold Kautzleben

Satishkumar Sekharan

Karl-Peter Nos

Stefan Kraus

Dirk Baumgaertel

Bernhard Jaecksch

Jan Rittinger

Christian Baeck

Sarah Menard

Peter Tillert

Tahar El Idrissi-Lamghari

Daniel Merkel

Stefan Uhrig

Yeonghee Choi

A method may include generating, based on text associated with an interaction between a user and an application, a query corresponding to an intent of the interaction. The query may be generated by applying one or more machine learning models trained to determine the intent of the interaction and to generate the query by mapping, to a corresponding slot in a template query, one or more named entities included in the first text. The query may be sent to an analytics engine not associated with the application to retrieve, from a database associated with the analytics engine, data relevant to the interaction between the user and the application. A data presentation providing a visual representation of the data retrieved from the database may be generated for display at a client associated with the user. Related systems and articles of manufacture are also provided.

Machine learning based plug-in for providing access to cloud-based analytics engine

A query of spatial data is received by a database comprising a columnar data store storing data in a column-oriented structure. Thereafter, a spatial data set is mapped to physical storage in the database using a space-filling curve. The spatial data set is then compacted and such compacted data can be used to retrieve data from the database that is responsive to the query. Related apparatus, systems, techniques and articles are also described.

Managing and querying spatial point data in column stores

A data set of spatial data having a plurality of dimensions and including linestrings can be processing by decomposing each linestring of the plurality of linestrings into a plurality of line segments. Each coordinate dimension appears in at least one line segment of the plurality of line segments can be listed in one of a plurality of dimensional dictionaries that each correspond to a dimension of the plurality of dimensions. A linestring of the plurality of linestrings can be represented as a set of the line segments using the plurality of dimensional dictionaries.

Column store optimization using telescope columns

Data is received that is derived from a plurality of geo-spatial sensors that respectively generate data characterizing a plurality of sources within a zone of interest. The data includes series time-stamped frames for each of the sensors and at least one of the sources has two or more associated sensors. The received data can be sorted and processed, for each sensor on a sensor-by-sensor basis, using a sliding window. The sorted and processed data can then be correlated and written into a data storage application. Related apparatus, systems, techniques and articles are also described.

Pre-processing of geo-spatial sensor data

A range k-nearest neighbor search query of a database is processed by first defining an inner rectangle bounded within a circle around a center point specified by the range k-nearest neighbor search query. Thereafter, a distance to the center point is calculated for each point within the inner rectangle. Query results are returned if k or more points are within the inner rectangle. Otherwise, at least one additional query is executed. Related apparatus, systems, techniques and articles are also described.

Columnwise range k-nearest neighbors search queries

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 grid order scanning technique. The spatial data set corresponding to the received query is then mapped to physical storage in the database using the identified minimal bounding rectangle so that the spatial data set can be retrieved. Related apparatus, systems, techniques and articles are also described.

Querying spatial data in column stores using grid-order scans

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.

Hilbert curve partitioning for parallelization of DBSCAN

A query is received, and in response, an initial data flow graph is generated that includes a plurality of nodes for executing the query with at least one of the nodes having at least one associated hint. The initial data flow graph is subsequently optimized using a model optimizer having a rules engine using a plurality rules to optimize the initial data flow graph. The at least one associated hint is used by the model optimizer to change how at least one of the plurality of rules is applied. Thereafter, execution of the query is initiated using the optimized data flow graph. Related apparatus, systems, techniques and articles are also described.

Augmented query optimization by data flow graph model optimizer

According to some embodiments, input data may be received from a data source in an enterprise database in accordance with an enterprise performance management planning model, stored by a processor at the enterprise database. An operation may then be performed on the input data to produce a result. The result may then be stored in a data target, wherein the data target points to a data holding entity in an instantiation of a plan data container at the enterprise database.

Enterprise performance management planning operations at an enterprise database

Polygons can be simplified from an original, higher resolution to a simplified, lower resolution such that the simplified versions of the polygons do not introduce errors and also do not render boundaries shared with other polygons invalid.

Polygon simplification

Correlated and processed data is received that is derived from a plurality of geo-spatial sensors that respectively generate data characterizing a plurality of sources within a zone of interest. The data includes a series of time-stamped frames for each of the sensors. Subsequently, events of interest are identified, in real-time, based on relative positions of the sources within the zone of interest prior to the data being written to a data storage application. Data can then be provided (e.g., loaded, stored, displayed, transmitted, etc.), in real-time, that characterize the events of interest. Related apparatus, systems, techniques and articles are also described.

Processing of geo-spatial athletics sensor data

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Heidelberg, Germany

Gerrit Simon Kazmaier