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For quick look-up on multidimensional points you need to create a R-tree index (http://en.wikipedia.org/wiki/R-tree) or any of its variants (http://en.wikipedia.org/wiki/Spatial_index#Spatial_index).

From wikipedia: R-trees are tree data structures used for spatial access methods, i.e., for indexing multi-dimensional information such as geographical coordinates, rectangles or polygons.

The key idea of the data structure is to group nearby objects and represent them with their minimum bounding rectangle in the next higher level of the tree; the "R" in R-tree is for rectangle. Since all objects lie within this bounding rectangle, a query that does not intersect the bounding rectangle also cannot intersect any of the contained objects.

For quick look-up on multidimensional points you need to create a R-tree index (http://en.wikipedia.org/wiki/R-tree) or any of its variants (http://en.wikipedia.org/wiki/Spatial_index#Spatial_index).

For quick look-up on multidimensional points you need to create a R-tree index (http://en.wikipedia.org/wiki/R-tree) or any of its variants (http://en.wikipedia.org/wiki/Spatial_index#Spatial_index).

From wikipedia: R-trees are tree data structures used for spatial access methods, i.e., for indexing multi-dimensional information such as geographical coordinates, rectangles or polygons.

The key idea of the data structure is to group nearby objects and represent them with their minimum bounding rectangle in the next higher level of the tree; the "R" in R-tree is for rectangle. Since all objects lie within this bounding rectangle, a query that does not intersect the bounding rectangle also cannot intersect any of the contained objects.

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source | link

For quick look-up on multidimensional points you need to create a R-tree index (http://en.wikipedia.org/wiki/R-tree) or any of its variants (http://en.wikipedia.org/wiki/Spatial_index#Spatial_index).