Amazon Technologies, Inc.

Databricks Inc.

Menelaos Karavelas

Hinnerk Gildhoff

Nemanja Boric

Ioanna Tsalouchidou

Desmond Cheong Zhi Xi

Eric Javier Biagioli

A data processing service generates for iteratively applying a geospatial function to geospatial data. The generated code includes at least a first iterative loop and a second iterative loop. The data processing service compiles the generated code to generate compiled code that vectorized at least the second iterative loop. The data processing service receives a request from a client device to perform one or more data processing operations including applying the geospatial function to a data table of geospatial cell indices. The data processing service compiles the request into one or more tasks including at least a vectorized operation based on the compiled code and executes the one or more tasks by at least invoking the vectorized operation on the set of worker nodes.

Efficiently vectorized implementation of operations in a global grid indexing library

A system, technique, or computer program product generates a simplified version of a geometry, based on a target number of points to be included in the output. A first plurality of points, representative of a geometry, is received. The simplified version of the geometry is generated by, at least, expanding a segment of a simplified version of the geometry. The segment is identified for expanding by determining that a point associated with the segment is at a distance from the segment that exceeds a tolerance value, and is includable in the simplified version of the geometry without causing the simplified version of the geometry to exceed the target size.

Spatial data simplification and storage

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San Ramon, CA, United States of America

Menelaos Karavelas