The Compare enum specifies the following comparison predicates used for index query construction and used in the examples above:

All comparison predicates are supported by String, numeric, Date and Instant data types. Boolean and UUID data types support the eq and neq comparison predicates.

eq and neq can be used on Boolean and UUID.

The Text enum specifies the search operator used to query for matching text or string values. We differentiate between two types of predicates:

See Section 24.1, “Full-Text Search” for more information about full-text and string search.

The Geo enum specifies geo-location predicates.

See Section 24.2, “Geo Mapping” for more information about geo search.

The following query examples demonstrate some of the predicates on the tutorial graph.

g.V().has("name", "hercules")
// 2) Find all vertices with an age greater than 50
g.V().has("age", gt(50))
// or find all vertices between 1000 (inclusive) and 5000 (exclusive) years of age and order by increasing age
g.V().has("age", inside(1000, 5000)).order().by("age", incr)
// which returns the same result set as the following query but in reverse order
g.V().has("age", inside(1000, 5000)).order().by("age", decr)
// 3) Find all edges where the place is at most 50 kilometers from the given latitude-longitude pair
g.E().has("place", geoWithin(Geoshape.circle(37.97, 23.72, 50)))
// 4) Find all edges where reason contains the word "loves"
g.E().has("reason", textContains("loves"))
// or all edges which contain two words (need to chunk into individual words)
g.E().has("reason", textContains("loves")).has("reason", textContains("breezes"))
// or all edges which contain words that start with "lov"
g.E().has("reason", textContainsPrefix("lov"))
// or all edges which contain words that match the regular expression "br[ez]*s" in their entirety
g.E().has("reason", textContainsRegex("br[ez]*s"))
// or all edges which contain words similar to "love"
g.E().has("reason", textContainsFuzzy("love"))
// 5) Find all vertices older than a thousand years and named "saturn"
g.V().has("age", gt(1000)).has("name", "saturn")

While JanusGraph’s composite indexes support any data type that can be stored in JanusGraph, the mixed indexes are limited to the following data types.

Additional data types will be supported in the future.

The Geoshape data type supports representing a point, circle, box, line, polygon, multi-point, multi-line and multi-polygon. Index backends currently support indexing points, circles, boxes, lines, polygons, multi-point, multi-line, multi-polygon and geometry collection. Geospatial index lookups are only supported via mixed indexes.

To construct a Geoshape use the following methods:

 //lat, lng
Geoshape.point(37.97, 23.72)
//lat, lng, radius in km
Geoshape.circle(37.97, 23.72, 50)
//SW lat, SW lng, NE lat, NE lng
Geoshape.box(37.97, 23.72, 38.97, 24.72)
//WKT
Geoshape.fromWkt("POLYGON ((35.4 48.9, 35.6 48.9, 35.6 49.1, 35.4 49.1, 35.4 48.9))")
//MultiPoint
Geoshape.geoshape(Geoshape.getShapeFactory().multiPoint().pointXY(60.0, 60.0).pointXY(120.0, 60.0)
  .build())
//MultiLine
Geoshape.geoshape(Geoshape.getShapeFactory().multiLineString()
  .add(Geoshape.getShapeFactory().lineString().pointXY(59.0, 60.0).pointXY(61.0, 60.0))
  .add(Geoshape.getShapeFactory().lineString().pointXY(119.0, 60.0).pointXY(121.0, 60.0)).build())
//MultiPolygon
Geoshape.geoshape(Geoshape.getShapeFactory().multiPolygon()
  .add(Geoshape.getShapeFactory().polygon().pointXY(59.0, 59.0).pointXY(61.0, 59.0)
    .pointXY(61.0, 61.0).pointXY(59.0, 61.0).pointXY(59.0, 59.0))
  .add(Geoshape.getShapeFactory().polygon().pointXY(119.0, 59.0).pointXY(121.0, 59.0)
    .pointXY(121.0, 61.0).pointXY(119.0, 61.0).pointXY(119.0, 59.0)).build())
//GeometryCollection
Geoshape.geoshape(Geoshape.getGeometryCollectionBuilder()
  .add(Geoshape.getShapeFactory().pointXY(60.0, 60.0))
  .add(Geoshape.getShapeFactory().lineString().pointXY(119.0, 60.0).pointXY(121.0, 60.0).build())
  .add(Geoshape.getShapeFactory().polygon().pointXY(119.0, 59.0).pointXY(121.0, 59.0)
    .pointXY(121.0, 61.0).pointXY(119.0, 61.0).pointXY(119.0, 59.0)).build())

In addition, when importing a graph via GraphSON the geometry may be represented by GeoJSON:

 //string
"37.97, 23.72"
//list
[37.97, 23.72]
//GeoJSON feature
{
  "type": "Feature",
  "geometry": {
    "type": "Point",
    "coordinates": [125.6, 10.1]
  },
  "properties": {
    "name": "Dinagat Islands"
  }
}
//GeoJSON geometry
{
  "type": "Point",
  "coordinates": [125.6, 10.1]
}

GeoJSON may be specified as Point, Circle, LineString or Polygon. Polygons must be closed. Note that unlike the JanusGraph API GeoJSON specifies coordinates as lng lat.

If you are using Elasticsearch then you can index properties with SET and LIST cardinality. For instance:

mgmt = graph.openManagement()
nameProperty = mgmt.makePropertyKey("names").dataType(String.class).cardinality(Cardinality.SET).make()
mgmt.buildIndex("search", Vertex.class).addKey(nameProperty, Mapping.STRING.asParameter()).buildMixedIndex("search")
mgmt.commit()
//Insert a vertex
person = graph.addVertex()
person.property("names", "Robert")
person.property("names", "Bob")
graph.tx().commit()
//Now query it
g.V().has("names", "Bob").count().next() //1
g.V().has("names", "Robert").count().next() //1