com.bigdata.gis.GISStore Maven / Gradle / Ivy
/*
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*/
/*
* Created on May 19, 2008
*/
package com.bigdata.gis;
/**
*
* This is a placeholder for a GIS design. While GIS systems are typically
* R-trees, I am considering an approach that leverages the existing scale-out
* B+-Tree architecture using a design similar in many ways to the triple store.
*
*
* There would be a feature dictionary with a foward and reverse map assigning
* feature identifiers. The feature identifiers should problably reserve the
* lower 2-3 bits for coarse coding of broad feature categories so that they may
* be filtered on those categories without having to resolve them against the
* feature dictionary - filtering on the feature dictionary is a scattered read.
*
*
* The core indices would use keys formed as lat, lon, alt, feature.
* The feature needs to show up in the key since there can be more than one
* feature at the same spatial location. Alternative indices would provide for
* different access paths for the same key, but the feature would always appear
* in the last key position giving 3 indices (unless scan of all locations for a
* feature is common in which case this gives 6 indices, much like a quad
* store).
*
*
* The value for the coordinate indices could either be unusued or could be a
* row identifier, much like the sid of the triple store, for making metadata
* statements about a specific {coordinate,feature} tuple. Other flags might
* also be carried on the value, but note that the value is replicated on each
* coordinate access path.
*
*
* If coordinates are entered into the database as of their "event" time then
* this design would make it easy to obtain the set of spatial features for a
* given moment in time using a historical read for that event time. However,
* this is likely to prove difficult when aggregating historical data so the
* temporary dimension may also need to enter into the key:
* lat, lon, alt, time, feature
*
*
* I am assuming that latitude, longitude, altitude, and time can all be 64-bit
* long values assigned from a standard representation such as decimal degrees,
* meters above/below sea-level, and UTC milliseconds. Equally the (X,Y,Z) could
* be a polar coordinate system. This is really one level above the data model.
* Regardless, and unlike the triple store, this means that most of the tuple is
* directly generated from "natural" units without the aid of a dictionary. Only
* the feature identifiers are assigned by a dictionary.
*
*
* Features need to be extensible metadata that can be used to link together the
* spatial extent of both stationary and moving "objects" (tracks). Features
* could doubtless be related together in additional ways, e.g., through
* part-whole relations, either within the GIS or in an external metadata
* database.
*
*
* The basic queries would be things such as "Find me all features F of category
* X within REGION (X,Y,Z) between TIME (T1,T2)." This would be coded as a JOIN
* of the various coordinate indices with a filter (where appropriate) on the
* bits coding coarse feature categories within the identifier and a scatter
* query doing fine-grained filtering against the reverse map of the feature
* dictionary.
*
*
* @todo impl. sketch using refactor of the triple store.
*
* @todo comparison with R-tree based approaches and practical GIS designs.
*
* @todo consideration to metadata mashups.
*
* @todo consideration to data sources and visualization tool chains for demo
* purposes.
*
* @todo consideration to reconcilation of feature identity and spatial-temporal
* locator error for reporting of tracks.
*
* @todo consideration to very high concurrency for read/write, including
* "consistent" writes, read-behind from consistent database states, and
* large #ofs tracks (10^6) with no less than 60 seconds update periods.
*
* @author Bryan Thompson
* @version $Id$
*/
public class GISStore {
}