Cartesian spatial traversals

The examples here use the following schema:

// SCHEMA
// POINT
schema.propertyKey('name').Text().create()
schema.propertyKey('point').Point().withBounds(-3, -3, 3, 3).create()
schema.vertexLabel('location').properties('name','point').create()
// LINESTRING
schema.propertyKey('line').Linestring().withBounds(-3, -3, 3, 3).create()
schema.vertexLabel('lineLocation').properties('name','line').create()
// POLYGON
schema.propertyKey('polygon').Polygon().withBounds(-3, -3, 3, 3).create()
schema.vertexLabel('polyLocation').properties('name','polygon').create()
// MATERIALIZED VIEW INDEXES
schema.vertexLabel('location').index('byname').materialized().by('name').add()
schema.vertexLabel('lineLocation').index('byname').materialized().by('name').add()
schema.vertexLabel('polyLocation').index('byname').materialized().by('name').add()
//SEARCH INDEX - ONLY WORKS FOR POINT AND LINESTRING
schema.vertexLabel('location').index('search').search().by('point').add()
schema.vertexLabel('lineLocation').index('search').search().by('line').add()

The example use the following data:

/// Create a point
graph.addVertex(label,'location','name','p0','point',Geo.point(0.5,0.5))
graph.addVertex(label,'location','name','p1','point',Geo.point(1,1))
graph.addVertex(label,'location','name','p2','point',Geo.point(-1,1))
graph.addVertex(label,'location','name','p3','point',Geo.point(-2,-2))
graph.addVertex(label,'location','name','p4','point',Geo.point(2,2))

// Create a linestring
graph.addVertex(label, 'lineLocation', 'name', 'l1', 'line', "LINESTRING(0 0, 1 1)")
graph.addVertex(label, 'lineLocation', 'name', 'l2', 'line', "LINESTRING(0 0, -1 1)")
graph.addVertex(label, 'lineLocation', 'name', 'l3', 'line', "LINESTRING(0 0, -2 -2)")
graph.addVertex(label, 'lineLocation', 'name', 'l4', 'line', "LINESTRING(0 0, 2 -2)")

// Create a polygon
graph.addVertex(label, 'polyLocation','name', 'g1', 'polygon',Geo.polygon(0,0,1,1,0,1,0,0))
graph.addVertex(label, 'polyLocation','name', 'g2', 'polygon',Geo.polygon(0,0,0,1,-1,1,0,0))
graph.addVertex(label, 'polyLocation','name', 'g3', 'polygon',Geo.polygon(0,0,-2,0,-2,-2,0,0))
graph.addVertex(label, 'polyLocation','name', 'g4', 'polygon',Geo.polygon(0,0,2,0,2,-2,0,0))

Find the stored data that matches a point mapped to the specified (x, y):

g.V().
has('location','point', Geo.point(0.5, 0.5)).
valueMap()

results in:

{name=[p0], point=[POINT (0.5 0.5)]}

Find the stored data that matches a line mapped to the specified points:

 g.V().
has('lineLocation','line',Geo.lineString(0, 0, 1, 1)).
valueMap()

results in:

{line=[LINESTRING (0 0, 1 1)], name=[l1]}

Find the stored data that matches a polygon mapped to the specified points:

 g.V().
has('polyLocation', 'polygon',Geo.polygon(0,0,1,1,0,1,0,0)).
valueMap()

results in:

{polygon=[POLYGON ((0 0, 1 1, 0 1, 0 0))], name=[g1]}

Find all the points within a radius from a particular point (centerpoint):

g.V().
has('location', 'point', Geo.inside(Geo.point(0, 0), 1)).
values('name')

lists:

==>p0

Centering the query on (0, 0) and searching within 1 unit returns one point, p0, from the dataset.

Find all the linestrings within a radius from a particular location (centerpoint):

 g.V().has('lineLocation', 'line', Geo.inside(Geo.point(0.0, 0.0), 1.415)).valueMap()

lists:

==>{line=[LINESTRING (0 0, 1 1)], name=[l1]}
==>{line=[LINESTRING (0 0, -1 1)], name=[l2]}

Centering the query on (0,0) and searching within 1.415 units returns two stored linestrings: l1 and l2.

Find all points within a specified Cartesian spatial polygon:

g.V().
has('location', 'point', Geo.inside(Geo.polygon(0, 0, 1, 0, 1, 1, 0, 1, 0, 0))).
values('name')

lists:

==>p0

find linestrings within a polygon

g.V().
has('lineLocation', 'line', Geo.inside(Geo.polygon(0, 0, 1, 0, 1, 1, 0, 1, 0, 0))).
values('name')

lists:

==>l1

The examples here use the following schema:

///SCHEMA
// PROPERTY KEYS
// Check for previous creation of property key with ifNotExists()
schema.propertyKey('name').Text().ifNotExists().create()
schema.propertyKey('address').Text().ifNotExists().create()
schema.propertyKey('location').Point().withBounds(-100,-100,100,100).ifNotExists().create()
// VERTEX LABELS
schema.vertexLabel('person').properties('name').ifNotExists().create()
schema.vertexLabel('home').properties('address','location').ifNotExists().create()
schema.vertexLabel('store').properties('name','location').ifNotExists().create()
schema.vertexLabel('ingredient').properties('name').ifNotExists().create()
// EEDGE LABELS
schema.edgeLabel('livesIn').connection('person','home').ifNotExists().create()
schema.edgeLabel('isStockedWith').connection('store','ingredient').multiple().ifNotExists().create()

// SEARCH INDEXES
schema.vertexLabel('person').index('search').search().by('name').asString().ifNotExists().add()
schema.vertexLabel('home').index('search').search().by('name').by('location').add();
schema.vertexLabel('store').index('search').search().by('name').by('location').add();
schema.vertexLabel('ingredient').index('search').search().by('name').add();

The examples use the following data:

//VERTICES
// PERSON VERTICES
pam = graph.addVertex(label, 'person', 'name','Pam')
les = graph.addVertex(label, 'person', 'name','Les')
paul = graph.addVertex(label, 'person', 'name','Paul')
victoria = graph.addVertex(label, 'person', 'name','Victoria')
terri = graph.addVertex(label, 'person', 'name','Terri')

// HOME VERTICES
home1 = graph.addVertex(label, 'home', 'address', '555 4th St',  'location', Geo.point(7,2));
home2 = graph.addVertex(label, 'home', 'address', '1700 Coyote Rd',  'location', Geo.point(-2,1));
home3 = graph.addVertex(label, 'home', 'address', '99 Mountain Pass Hwy',  'location', Geo.point(0,0));

// STORE VERTICES
store1 = graph.addVertex(label, 'store', 'name', 'ZippyMart',  'location', Geo.point(1,5));
store2 = graph.addVertex(label, 'store', 'name', 'Quik Station',  'location', Geo.point(7,-1));
store3 = graph.addVertex(label, 'store', 'name', 'Mamma's Grocery',  'location', Geo.point(-3,-3));

// INGREDIENT VERTICES
celery = graph.addVertex(label, 'ingredient','name', 'celery');
milk = graph.addVertex(label, 'ingredient','name', 'milk');
bokChoy = graph.addVertex(label, 'ingredient','name', 'bok choy');
steak = graph.addVertex(label, 'ingredient','name', 'steak');
carrots = graph.addVertex(label, 'ingredient','name', 'carrots');
porkChops = graph.addVertex(label, 'ingredient','name', 'pork chops');

// PERSON - HOME EDGES
pam.addEdge('livesIn', home1);
les.addEdge('livesIn', home1);
paul.addEdge('livesIn',home3);
victoria.addEdge('livesIn',home3);
terri.addEdge('livesIn',home2);

// STORE - INGREDIENT EDGES
store1.addEdge('isStockedWith', milk);
store1.addEdge('isStockedWith', bokChoy);
store1.addEdge('isStockedWith', steak);
store2.addEdge('isStockedWith', steak);
store2.addEdge('isStockedWith', carrots);
store2.addEdge('isStockedWith', porkChops);
store3.addEdge('isStockedWith', milk);
store3.addEdge('isStockedWith', carrots);
store3.addEdge('isStockedWith', celery);

Paul is the student whose home we'll use as the starting point. First, list all stores within the given radius (10 units of distance) from Paul's home (the centerpoint):

g.V().has('store', 'location', Geo.inside(Geo.point(0,0),10)).
values('name')

results in:

==>ZippyMart
==>Quik Station
==>Mamma's Grocery

Note that this exercise is using Cartesian coordinates and distances calculated between Cartesian points, but a similar exercises can use geospatial data.

Now list the stores within a 10 unit radius from Paul's home that have celery:

g.V().has('store', 'location', Geo.inside(Geo.point(0,0),10)).as('Store').
out().has('name','celery').as('Ingred').
select('Store', 'Ingred').
by('name').
by('name')

finds:

==>{Store=ZippyMart, Ingred=celery}
==>{Store=Quik Station, Ingred=celery}
==>{Store=Mamma's Grocery, Ingred=celery}

This query uses methods that are common, such as as(), out(), and select() that are explained in Simple Traversals to narrow the query.

Finally, list the stores within a 10 unit radius of Paul's home that have celery, and sort them by the distance from Paul's home:

// List store name, location, and ingredient in order by distance from the store
g.V().has('store', 'location', Geo.inside(Geo.point(0,0),25)).as('Store').
order().by{it.value('location').getOgcGeometry().distance(Geo.point(0,0).getOgcGeometry())}.
as('Location').
out().has('name','celery').as('Ingred').
select('Store', 'Location','Ingred').
by('name').
by('location').
by('name')

==>{Store=Mamma's Grocery, Location=POINT (-3 -3), Ingred=celery}
==>{Store=ZippyMart, Location=POINT (1 5), Ingred=celery}
==>{Store=Quik Station, Location=POINT (7 -1), Ingred=celery}

This query adds the method order() to sort the results; it is also explained in Simple Traversals. The query must also use a method that must be imported in order for the query to succeed: getOgcGeometry() and distance(). Importing the library is accomplished in the original script using:

import com.esri.core.geometry.ogc.OGCGeometry;