Geo Indexes
This is an introduction to ArangoDB's geo indexes.
Geo Indexes
ArangoDB uses Hilbert curves to implement geo-spatial indexes. See this blog for details.
A geo-spatial index assumes that the latitude is between -90 and 90 degree and the longitude is between -180 and 180 degree. A geo index will ignore all documents which do not fulfill these requirements.
A geo-spatial constraint makes the same assumptions, but documents not fulfilling these requirements are rejected.
Accessing Geo Indexes from the Shell
collection.ensureGeoIndex(location)Creates a geo-spatial index on all documents using location as path to the coordinates. The value of the attribute must be a list with at least two double values. The list must contain the latitude (first value) and the longitude (second value). All documents, which do not have the attribute path or with value that are not suitable, are ignored.
In case that the index was successfully created, the index identifier is returned.
collection.ensureGeoIndex(location, true)As above which the exception, that the order within the list is longitude followed by latitude. This corresponds to the format described in
http://geojson.org/geojson-spec.html#positions
collection.ensureGeoIndex(latitude, longitude)Creates a geo-spatial index on all documents using latitude and longitude as paths the latitude and the longitude. The value of the attribute latitude and of the attribute longitude must a double. All documents, which do not have the attribute paths or which values are not suitable, are ignored.
In case that the index was successfully created, the index identifier is returned.
Examples
Create an geo index for a list attribute:
arango> db.geo.ensureGeoIndex("loc");
{ "id" : "127629/47772301", "type" : "geo1", "geoJson" : false, "fields" : ["loc"], "isNewlyCreated" : true }
arango> for (i = -90; i <= 90; i += 10) {
.......> for (j = -180; j <= 180; j += 10) {
.......> db.geo.save({ name : "Name/" + i + "/" + j,
.......> loc: [ i, j ] });
.......> }
.......> }
arango> db.geo.count();
703
arango> db.geo.near(0,0).limit(3).toArray();
[ { "_id" : "154092:24861164", "_rev" : 24861164, "name" : "Name/0/0", "loc" : [0, 0]},
{ "_id" : "154092:24926700", "_rev" : 24926700, "name" : "Name/0/10", "loc" : [0, 10]},
{ "_id" : "154092:22436332", "_rev" : 22436332, "name" : "Name/-10/0", "loc" : [-10, 0]}]
arango> db.geo.near(0,0).count();
100
Create an geo index for a hash array attribute:
arango> db.geo2.ensureGeoIndex("location.latitude", "location.longitude");
{ "id" : "87612/1070652", "type" : "geo2", "fields" : ["location.latitude", "location.longitude"], "isNewlyCreated" : true }
arango> for (i = -90; i <= 90; i += 10) {
.......> for (j = -180; j <= 180; j += 10) {
.......> db.geo2.save({ name : "Name/" + i + "/" + j,
.......> location: { latitude : i,
.......> longitude : j } });
.......> }
.......> }
arango> db.geo2.near(0,0).limit(3).toArray();
[{
"_id" : "48126444:72964588",
"_rev" : 72964588,
"location" : { "latitude" : 0, "longitude" : 0},
"name" : "Name/0/0"
},
{
"_id" : "48126444:73030124",
"_rev" : 73030124,
"location" : { "latitude" : 0, "longitude" : 10},
"name" : "Name/0/10"
},
{
"_id" : "48126444:70539756",
"_rev" : 70539756,
"location" : { "latitude" : -10, "longitude" : 0},
"name" : "Name/-10/0"
}]
collection.ensureGeoConstraint(location, ignore-null)collection.ensureGeoConstraint(location, true, ignore-null)collection.ensureGeoConstraint(latitude, longitude, ignore-null)Works like
ensureGeoIndex but requires that the documents contain a valid geo definition. If ignore-null is true, then documents with a null in location or at least one null in latitude or longitude are ignored.
collection.geo(location)The next near or within operator will use the specific geo-spatial index.
collection.geo(location, true)The next near or within operator will use the specific geo-spatial index.
collection.geo(latitude, longitude)The next near or within operator will use the specific geo-spatial index.
Examples
Assume you have a location stored as list in the attribute home and a destination stored in the attribute work. Than you can use the geo operator to select, which coordinates to use in a near query.
arango> for (i = -90; i <= 90; i += 10) {
.......> for (j = -180; j <= 180; j += 10) {
.......> db.complex.save({ name : "Name/" + i + "/" + j,
.......> home : [ i, j ],
.......> work : [ -i, -j ] });
.......> }
.......> }
arango> db.complex.near(0, 170).limit(5);
exception in file '/simple-query' at 1018,5: an geo-index must be known
arango> db.complex.ensureGeoIndex("home");
arango> db.complex.near(0, 170).limit(5).toArray();
[ { _id : 48834092:74655276, _rev : 74655276, name : Name/0/170, home : [ 0, 170 ], work : [ 0, -170 ] },
{ _id : 48834092:74720812, _rev : 74720812, name : Name/0/180, home : [ 0, 180 ], work : [ 0, -180 ] },
{ _id : 48834092:77080108, _rev : 77080108, name : Name/10/170, home : [ 10, 170 ], work : [ -10, -170 ] },
{ _id : 48834092:72230444, _rev : 72230444, name : Name/-10/170, home : [ -10, 170 ], work : [ 10, -170 ] },
{ _id : 48834092:72361516, _rev : 72361516, name : Name/0/-180, home : [ 0, -180 ], work : [ 0, 180 ] } ]
arango> db.complex.geo("work").near(0, 170).limit(5);
exception in file '/simple-query' at 1018,5: an geo-index must be known
arango> db.complex.ensureGeoIndex("work");
arango> db.complex.geo("work").near(0, 170).limit(5).toArray();
[ { _id : 48834092:72427052, _rev : 72427052, name : Name/0/-170, home : [ 0, -170 ], work : [ 0, 170 ] },
{ _id : 48834092:72361516, _rev : 72361516, name : Name/0/-180, home : [ 0, -180 ], work : [ 0, 180 ] },
{ _id : 48834092:70002220, _rev : 70002220, name : Name/-10/-170, home : [ -10, -170 ], work : [ 10, 170 ] },
{ _id : 48834092:74851884, _rev : 74851884, name : Name/10/-170, home : [ 10, -170 ], work : [ -10, 170 ] },
{ _id : 48834092:74720812, _rev : 74720812, name : Name/0/180, home : [ 0, 180 ], work : [ 0, -180 ] } ]
collection.near(latitude, longitude)The default will find at most 100 documents near the coordinate (latitude, longitude). The returned list is sorted according to the distance, with the nearest document coming first. If there are near documents of equal distance, documents are chosen randomly from this set until the limit is reached. It is possible to change the limit using the limit operator.
In order to use the near operator, a geo index must be defined for the collection. This index also defines which attribute holds the coordinates for the document. If you have more then one geo-spatial index, you can use the geo operator to select a particular index.
- Note:
neardoes not support negative skips. However, you can still uselimitfollowed toskip.
collection.near(latitude, longitude).limit(limit)Limits the result to limit documents instead of the default 100.
- Note:
- Unlike with multiple explicit limits, limit will raise the implicit default limit imposed by
within.
collection.near(latitude, longitude).distance()This will add an attribute distance to all documents returned, which contains the distance between the given point and the document in meter.
collection.near(latitude, longitude).distance(name)This will add an attribute name to all documents returned, which contains the distance between the given point and the document in meter.
Examples
To get the nearst two locations:
arango> db.geo.near(0,0).limit(2).toArray();
[ { _id : 131840:24773376, _rev : 24773376, name : Name/0/0, loc : [ 0, 0 ] },
{ _id : 131840:22348544, _rev : 22348544, name : Name/-10/0, loc : [ -10, 0 ] } ]
If you need the distance as well, then you can use the distance operator:
arango> db.geo.near(0,0).distance().limit(2).toArray();
[ { _id : 131840:24773376, _rev : 24773376, distance : 0, name : Name/0/0, loc : [ 0, 0 ] },
{ _id : 131840:22348544, _rev : 22348544, distance : 1111949.3, name : Name/-10/0, loc : [ -10, 0 ] } ]
collection.within(latitude, longitude, radius)This will find all documents with in a given radius around the coordinate (latitude, longitude). The returned list is sorted by distance.
In order to use the within operator, a geo index must be defined for the collection. This index also defines which attribute holds the coordinates for the document. If you have more then one geo-spatial index, you can use the geo operator to select a particular index.
collection.within(latitude, longitude, radius) .distance()This will add an attribute _distance to all documents returned, which contains the distance between the given point and the document in meter.
collection.within(latitude, longitude, radius) .distance(name)This will add an attribute name to all documents returned, which contains the distance between the given point and the document in meter.
Examples
To find all documents within a radius of 2000 km use:
arango> db.geo.within(0, 0, 2000 * 1000).distance().toArray();
[ { _id : 131840:24773376, _rev : 24773376, distance : 0, name : Name/0/0, loc : [ 0, 0 ] },
{ _id : 131840:24707840, _rev : 24707840, distance : 1111949.3, name : Name/0/-10, loc : [ 0, -10 ] },
{ _id : 131840:24838912, _rev : 24838912, distance : 1111949.3, name : Name/0/10, loc : [ 0, 10 ] },
{ _id : 131840:22348544, _rev : 22348544, distance : 1111949.3, name : Name/-10/0, loc : [ -10, 0 ] },
{ _id : 131840:27198208, _rev : 27198208, distance : 1111949.3, name : Name/10/0, loc : [ 10, 0 ] },
{ _id : 131840:22414080, _rev : 22414080, distance : 1568520.6, name : Name/-10/10, loc : [ -10, 10 ] },
{ _id : 131840:27263744, _rev : 27263744, distance : 1568520.6, name : Name/10/10, loc : [ 10, 10 ] },
{ _id : 131840:22283008, _rev : 22283008, distance : 1568520.6, name : Name/-10/-10, loc : [ -10, -10 ] },
{ _id : 131840:27132672, _rev : 27132672, distance : 1568520.6, name : Name/10/-10, loc : [ 10, -10 ] } ]