6.2. Index Basics

GeoMesa will create various indices for a given SimpleFeatureType schema (see Index Overview). This allows us to answer a variety of queries in a optimized manner. GeoMesa will make a best effort to determine the attributes used for indexing. The attributes to use can also be specified as part of the SimpleFeatureType.

6.2.1. Spatial Index (Z2/XZ2)

If the SimpleFeatureType has a Geometry-type attribute (Point, LineString, Polygon, etc), GeoMesa will create a spatial index on that attribute. If there is more than one Geometry-type attribute, the default one will be used. The default geometry is generally specified with a * prefix in the SimpleFeatureType string, and is the one returned by SimpleFeatureType.getGeometryDescriptor.

6.2.2. Spatio-temporal Index (Z3/XZ3)

If the SimpleFeatureType has both a Geometry-type attribute and a Date attribute, GeoMesa will create a spatio-temporal index on those attributes. The Geometry-type attribute used is the same as for the spatial index, above. The Date attribute selected will be the first one declared, or can be set explicitly. See Setting the Indexed Date Attribute for details on setting the indexed date.

6.2.3. ID Index

GeoMesa will always create an ID index on SimpleFeature.getID().

6.2.4. Attribute Index

Some queries are slow to answer using the default indices. For example, with twitter data you might want to return all tweets for a given user. To speed up this type of query, any attribute in your simple feature type may be indexed individually.

To index an attribute, add an index hint to the attribute descriptor with a value of true. To set the cardinality of an attribute, use the hint cardinality with a value of high or low (see below for a description of cardinality hints).


Accumulo data stores have an additional option to create reduced ‘join’ attribute indices, and will use the reduced format by default. See Accumulo Attribute Indices for details.

Setting the hint can be done in multiple ways. If you are using a string to indicate your simple feature type (e.g. through the command line tools, or when using SimpleFeatureTypes.createType), you can append the hint to the attribute to be indexed, like so:

// append the hint after the attribute type, separated by a colon
String spec = "name:String:index=true:cardinality=high,age:Int:index=true,dtg:Date,*geom:Point:srid=4326"
SimpleFeatureType sft = SimpleFeatureTypes.createType("mySft", spec);

If you have an existing simple feature type, or you are not using SimpleFeatureTypes.createType, you may set the hint directly in the feature type:

// set the hint directly
SimpleFeatureType sft = ...
sft.getDescriptor("name").getUserData().put("index", "true");
sft.getDescriptor("name").getUserData().put("cardinality", "high");
sft.getDescriptor("age").getUserData().put("index", "true");

If you are using TypeSafe configuration files to define your simple feature type, you may include the hint in the attribute field:

geomesa {
  sfts {
    "mySft" = {
      attributes = [
        { name = name, type = String, index = true, cardinality = high }
        { name = age,  type = Int,    index = true                     }
        { name = dtg,  type = Date                                     }
        { name = geom, type = Point,  srid = 4326                      }

If you are using the GeoMesa SftBuilder, you may call the overloaded attribute methods:

// scala example
import org.locationtech.geomesa.utils.geotools.SftBuilder.SftBuilder
import org.locationtech.geomesa.utils.stats.Cardinality

val sft = new SftBuilder()
    .stringType("name", Opts(index = true, cardinality = Cardinality.HIGH))
    .intType("age", Opts(index = true))
    .geometry("geom", default = true)
    .build("mySft") Cardinality Hints

GeoMesa has a query planner that tries to find the best strategy for answering a given query. In general, this means using the index that will filter the result set the most, before considering the entire query filter on the reduced data set. For simple queries, there is often only one suitable index. However, for mixed queries, there can be multiple options.

For example, given the query bbox(geom, -120, -60, 120, 60) AND IN('id-01'), we could try to execute against the spatial index using the bounding box, or we could try to execute against the ID index using the feature ID. In this case, we know that the ID filter will match at most one record, while the bbox filter could match many records, so we will choose the ID index.

Attributes that are know to have many distinct values, i.e. a high cardinality, are likely to filter out many false positives through the index structure, and thus a query against the attribute index will touch relatively few records. Conversely, in the worst case, a Boolean attribute (for example), with only two distinct values, would likely require scanning half of the entire data set.

Cardinality hints may be used to influence the query planner when considering attribute indices. If an attribute is marked as having a high cardinality, the attribute index will be prioritized. Conversely, if an attribute is marked with low cardinality, the attribute index will be de-prioritized.