Geospatial index and query

Use Aerospike geospatial storage and indexing to enable fast queries on points within a region, on a region containing points, and points within a radius.

Underlying technologies

The Aerospike geospatial feature relies on these technologies:

• GeoJSON format to specify and store GeoJSON geometry objects, and achieve data standardization and interoperability. See the GeoJSON Format Specification and GeoJSON IETF WG.
• The Aerospike AeroCircle data type extends the GeoJSON format to store circles as well as polygons.
• S2 Spherical Geometry Library to map points and regions in single-dimension, 64-bit CellID representation.

Note

The S2 Geometry Library is a spherical geometry library, very useful for manipulating regions on a sphere (commonly on Earth) and indexing geographic data. The S2 blog provides more details about S2, Hilbert Curve, and geospatial mapping.

• Aerospike secondary indexes and queries to achieve performance and scale for index inserts/updates and queries.

Use cases

• Vehicle tracking systems that require high-throughput updates of vehicle location and frequently query vehicles within a region.
• A mapping application could find different amenities within a certain distance of a given location.
• Location-targeted bidding transactions to discover persons or devices within the location with an active ad campaign.

See these Aerospike examples.

Geospatial data

Aerospike supports the GeoJSON geospatial data type. All geospatial functionality (indexing and querying) only execute on GeoJSON data types.

GeoJSON data incurs this additional processing on data reads:

• GeoJSON text is parsed for validity and support (see GeoJSON Parsing).
• GeoJSON text is converted into S2 CellID coverings.
• Aerospike saves both the covering CellIDs and the original GeoJSON in the database.
• Only GeoJSON data is accessible to the application through the client APIs and the UDF subsystem.

Store GeoJSON data

Store GeoJSON Point and Polygon objects in bins using each client’s GeoJSON data type.

Java

Key key = new Key("test", "geo", "loc1");
String point = "{\"type\": \"Point\", \"coordinates\": [-122.0862, 37.4220]}";
client.put(null, key,
    new Bin("name", "Googleplex"),
    Bin.asGeoJSON("loc_bin", point));

Python

key = ("test", "geo", "loc1")
loc = aerospike.GeoJSON({
    "type": "Point",
    "coordinates": [-122.0862, 37.4220]
})
client.put(key, {"name": "Googleplex", "loc_bin": loc})

Go

key, _ := as.NewKey("test", "geo", "loc1")
point := as.NewGeoJSONValue(
    `{"type": "Point", "coordinates": [-122.0862, 37.4220]}`)
client.PutBins(nil, key,
    as.NewBin("name", "Googleplex"),
    as.NewBin("loc_bin", point))

C

as_key key;
as_key_init_str(&key, "test", "geo", "loc1");

as_record rec;
as_record_inita(&rec, 2);
as_record_set_str(&rec, "name", "Googleplex");
as_record_set_geojson_strp(&rec, "loc_bin",
    "{\"type\": \"Point\", \"coordinates\": [-122.0862, 37.4220]}", false);

aerospike_key_put(&as, &err, NULL, &key, &rec);
as_record_destroy(&rec);

C#

Key key = new Key("test", "geo", "loc1");
string point = "{\"type\": \"Point\", \"coordinates\": [-122.0862, 37.4220]}";
client.Put(null, key,
    new Bin("name", "Googleplex"),
    Bin.AsGeoJSON("loc_bin", point));

Node.js

const key = new Aerospike.Key("test", "geo", "loc1");
const point = new Aerospike.GeoJSON({
  type: "Point",
  coordinates: [-122.0862, 37.4220],
});
await client.put(key, { name: "Googleplex", loc_bin: point });

Geospatial index

In addition to integers and strings, Aerospike supports Geo2DSphere data types for indexes.

Use asadm to create and manage secondary indexes in an Aerospike cluster. For instructions, see Secondary Index (SI) Query.

The following command creates a secondary index called geo-index using geo2dsphere data on the namespace user-profile using the set name geo-set and the bin geo-bin.

Admin+> manage sindex create geo2dsphere geo-index ns user_profile set geo-set bin geo-bin

Indexes can also be created programmatically:

Java

IndexTask task = client.createIndex(null, "test", "geo", "geo-loc-idx",
    "loc_bin", IndexType.GEO2DSPHERE);
task.waitTillComplete();

Python

client.index_single_value_create(
    "test", "geo", "loc_bin",
    aerospike.INDEX_GEO2DSPHERE, "geo-loc-idx")

Go

task, _ := client.CreateIndex(nil, "test", "geo", "geo-loc-idx",
    "loc_bin", as.GEO2DSPHERE)
<-task.OnComplete()

C

as_index_task task;
aerospike_index_create(&as, &err, &task, NULL, "test", "geo",
    "loc_bin", "geo-loc-idx", AS_INDEX_GEO2DSPHERE);
aerospike_index_create_wait(&err, &task, 0);

C#

IndexTask task = client.CreateIndex(null, "test", "geo", "geo-loc-idx",
    "loc_bin", IndexType.GEO2DSPHERE);
task.Wait();

Node.js

await client.createIndex({
  ns: "test", set: "geo", bin: "loc_bin",
  index: "geo-loc-idx",
  datatype: Aerospike.indexDataType.GEO2DSPHERE,
});

Geospatial query

Aerospike supports two Geospatial queries:

• Points exist within a region (including circle)
• Region contains point

The following examples use these sample records, each containing a GeoJSON Point in loc_bin:

{ "name": "Googleplex",      "loc_bin": {"type": "Point", "coordinates": [-122.0862, 37.4220]} }
{ "name": "Ferry Building",  "loc_bin": {"type": "Point", "coordinates": [-122.3936, 37.7956]} }
{ "name": "UC Berkeley",     "loc_bin": {"type": "Point", "coordinates": [-122.2727, 37.8716]} }
{ "name": "NYC Times Sq",    "loc_bin": {"type": "Point", "coordinates": [-73.9857,  40.7580]} }

Points-within-region query

Find all points that fall within a given polygon. With the geo-loc-idx index on loc_bin, querying a Bay Area polygon returns the three California points but not New York.

Java

String region = "{\"type\": \"Polygon\", \"coordinates\": [[" +
    "[-122.500, 37.000], [-121.000, 37.000], " +
    "[-121.000, 38.080], [-122.500, 38.080], " +
    "[-122.500, 37.000]]]}";

Statement stmt = new Statement();
stmt.setNamespace("test");
stmt.setSetName("geo");
stmt.setFilter(Filter.geoWithinRegion("loc_bin", region));

RecordSet rs = client.query(null, stmt);
while (rs.next()) {
    System.out.println(rs.getRecord().getString("name"));
}
rs.close();

Python

region = aerospike.GeoJSON({
    "type": "Polygon",
    "coordinates": [[
        [-122.500, 37.000], [-121.000, 37.000],
        [-121.000, 38.080], [-122.500, 38.080],
        [-122.500, 37.000]
    ]]
})

query = client.query("test", "geo")
query.where(p.geo_within_geojson_region("loc_bin", region.dumps()))

for _, _, rec in query.results():
    print(rec["name"])

Go

region := `{"type": "Polygon", "coordinates": [[` +
    `[-122.500, 37.000], [-121.000, 37.000], ` +
    `[-121.000, 38.080], [-122.500, 38.080], ` +
    `[-122.500, 37.000]]]}`

stmt := as.NewStatement("test", "geo")
stmt.SetFilter(as.NewGeoWithinRegionFilter("loc_bin", region))

rs, _ := client.Query(nil, stmt)
for rec := range rs.Results() {
    fmt.Println(rec.Record.Bins["name"])
}

C

const char* region =
    "{\"type\": \"Polygon\", \"coordinates\": [["
    "[-122.500, 37.000], [-121.000, 37.000], "
    "[-121.000, 38.080], [-122.500, 38.080], "
    "[-122.500, 37.000]]]}";

as_query q;
as_query_init(&q, "test", "geo");
as_query_where_inita(&q, 1);
as_query_where(&q, "loc_bin", as_geo_within(region));

aerospike_query_foreach(&as, &err, NULL, &q, query_cb, NULL);
as_query_destroy(&q);

C#

string region = "{\"type\": \"Polygon\", \"coordinates\": [[" +
    "[-122.500, 37.000], [-121.000, 37.000], " +
    "[-121.000, 38.080], [-122.500, 38.080], " +
    "[-122.500, 37.000]]]}";

Statement stmt = new();
stmt.SetNamespace("test");
stmt.SetSetName("geo");
stmt.SetFilter(Filter.GeoWithinRegion("loc_bin", region));

RecordSet rs = client.Query(null, stmt);
while (rs.Next())
{
    Console.WriteLine(rs.Record.GetString("name"));
}
rs.Close();

Node.js

const region = new Aerospike.GeoJSON({
  type: "Polygon",
  coordinates: [[
    [-122.500, 37.000], [-121.000, 37.000],
    [-121.000, 38.080], [-122.500, 38.080],
    [-122.500, 37.000],
  ]],
});

const query = client.query("test", "geo");
query.where(Aerospike.filter.geoWithinGeoJSONRegion("loc_bin", region));

const stream = query.foreach();
stream.on("data", (rec) => console.log(rec.bins.name));

Points-within-radius query (circle)

Find all points within a given radius (in meters) of a longitude/latitude. The client constructs an AeroCircle GeoJSON internally. This example finds points within 50 km of the Googleplex.

Java

Statement stmt = new Statement();
stmt.setNamespace("test");
stmt.setSetName("geo");
stmt.setFilter(Filter.geoWithinRadius("loc_bin", -122.0862, 37.4220, 50000));

RecordSet rs = client.query(null, stmt);
while (rs.next()) {
    System.out.println(rs.getRecord().getString("name"));
}
rs.close();

Python

query = client.query("test", "geo")
query.where(p.geo_within_radius("loc_bin", -122.0862, 37.4220, 50000))

for _, _, rec in query.results():
    print(rec["name"])

Go

stmt := as.NewStatement("test", "geo")
stmt.SetFilter(as.NewGeoWithinRadiusFilter("loc_bin",
    -122.0862, 37.4220, 50000))

rs, _ := client.Query(nil, stmt)
for rec := range rs.Results() {
    fmt.Println(rec.Record.Bins["name"])
}

C

char circle[256];
snprintf(circle, sizeof(circle),
    "{\"type\": \"AeroCircle\", \"coordinates\": "
    "[[-122.0862, 37.4220], 50000]}");

as_query q;
as_query_init(&q, "test", "geo");
as_query_where_inita(&q, 1);
as_query_where(&q, "loc_bin", as_geo_within(circle));

aerospike_query_foreach(&as, &err, NULL, &q, query_cb, NULL);
as_query_destroy(&q);

C#

Statement stmt = new();
stmt.SetNamespace("test");
stmt.SetSetName("geo");
stmt.SetFilter(Filter.GeoWithinRadius("loc_bin", -122.0862, 37.4220, 50000));

RecordSet rs = client.Query(null, stmt);
while (rs.Next())
{
    Console.WriteLine(rs.Record.GetString("name"));
}
rs.Close();

Node.js

const query = client.query("test", "geo");
query.where(Aerospike.filter.geoWithinRadius("loc_bin",
    -122.0862, 37.4220, 50000));

const stream = query.foreach();
stream.on("data", (rec) => console.log(rec.bins.name));

Region-contains-point query

Find all stored regions that contain a given point. This requires a geo index on the bin storing the Polygon data.

Given these region records stored in rgn_bin:

{ "name": "SF Bay Area", "rgn_bin": {"type": "Polygon", "coordinates": [[[-122.500,37.000],[-121.000,37.000],[-121.000,38.080],[-122.500,38.080],[-122.500,37.000]]]} }
{ "name": "Downtown SF", "rgn_bin": {"type": "Polygon", "coordinates": [[[-122.420,37.770],[-122.390,37.770],[-122.390,37.800],[-122.420,37.800],[-122.420,37.770]]]} }

Query for regions containing a point in Downtown San Francisco. Both regions are returned because the point falls inside the smaller Downtown SF polygon, which is itself inside the larger Bay Area polygon.

Java

String point = "{\"type\": \"Point\", \"coordinates\": [-122.4000, 37.7900]}";

Statement stmt = new Statement();
stmt.setNamespace("test");
stmt.setSetName("geo");
stmt.setFilter(Filter.geoContains("rgn_bin", point));

RecordSet rs = client.query(null, stmt);
while (rs.next()) {
    System.out.println(rs.getRecord().getString("name"));
}
rs.close();

Python

point = aerospike.GeoJSON({
    "type": "Point",
    "coordinates": [-122.4000, 37.7900]
})

query = client.query("test", "geo")
query.where(p.geo_contains_geojson_point("rgn_bin", point.dumps()))

for _, _, rec in query.results():
    print(rec["name"])

Go

point := `{"type": "Point", "coordinates": [-122.4000, 37.7900]}`

stmt := as.NewStatement("test", "geo")
stmt.SetFilter(as.NewGeoRegionsContainingPointFilter("rgn_bin", point))

rs, _ := client.Query(nil, stmt)
for rec := range rs.Results() {
    fmt.Println(rec.Record.Bins["name"])
}

C

const char* point =
    "{\"type\": \"Point\", \"coordinates\": [-122.4000, 37.7900]}";

as_query q;
as_query_init(&q, "test", "geo");
as_query_where_inita(&q, 1);
as_query_where(&q, "rgn_bin", as_geo_contains(point));

aerospike_query_foreach(&as, &err, NULL, &q, query_cb, NULL);
as_query_destroy(&q);

C#

string point = "{\"type\": \"Point\", \"coordinates\": [-122.4000, 37.7900]}";

Statement stmt = new();
stmt.SetNamespace("test");
stmt.SetSetName("geo");
stmt.SetFilter(Filter.GeoContains("rgn_bin", point));

RecordSet rs = client.Query(null, stmt);
while (rs.Next())
{
    Console.WriteLine(rs.Record.GetString("name"));
}
rs.Close();

Node.js

const point = new Aerospike.GeoJSON({
  type: "Point",
  coordinates: [-122.4000, 37.7900],
});

const query = client.query("test", "geo");
query.where(Aerospike.filter.geoContainsGeoJSONPoint("rgn_bin", point));

const stream = query.foreach();
stream.on("data", (rec) => console.log(rec.bins.name));

Query filters

To extend the capabilities of geospatial queries, apply a filter expression to narrow down results. This example finds points within a 50 km radius that also have an amenity bin equal to "cafe".

Java

Statement stmt = new Statement();
stmt.setNamespace("test");
stmt.setSetName("geo");
stmt.setFilter(Filter.geoWithinRadius("loc_bin", -122.0862, 37.4220, 50000));

QueryPolicy queryPolicy = new QueryPolicy();
queryPolicy.filterExp = Exp.build(
    Exp.eq(Exp.stringBin("amenity"), Exp.val("cafe"))
);

RecordSet rs = client.query(queryPolicy, stmt);
while (rs.next()) {
    System.out.println(rs.getRecord().getString("name"));
}
rs.close();

Python

query = client.query("test", "geo")
query.where(p.geo_within_radius("loc_bin", -122.0862, 37.4220, 50000))

expr = exp.Eq(exp.StrBin("amenity"), exp.Val("cafe")).compile()
policy = {"expressions": expr}

for _, _, rec in query.results(policy):
    print(rec["name"])

Go

stmt := as.NewStatement("test", "geo")
stmt.SetFilter(as.NewGeoWithinRadiusFilter("loc_bin",
    -122.0862, 37.4220, 50000))

qp := as.NewQueryPolicy()
qp.FilterExpression = as.ExpEq(
    as.ExpStringBin("amenity"),
    as.ExpStringVal("cafe"),
)

rs, _ := client.Query(qp, stmt)
for rec := range rs.Results() {
    fmt.Println(rec.Record.Bins["name"])
}

C

char circle[256];
snprintf(circle, sizeof(circle),
    "{\"type\": \"AeroCircle\", \"coordinates\": "
    "[[-122.0862, 37.4220], 50000]}");

as_query q;
as_query_init(&q, "test", "geo");
as_query_where_inita(&q, 1);
as_query_where(&q, "loc_bin", as_geo_within(circle));

as_exp_build(filter,
    as_exp_cmp_eq(as_exp_bin_str("amenity"), as_exp_str("cafe")));

as_policy_query qp;
as_policy_query_init(&qp);
qp.base.filter_exp = filter;

aerospike_query_foreach(&as, &err, &qp, &q, query_cb, NULL);
as_exp_destroy(filter);
as_query_destroy(&q);

C#

Statement stmt = new();
stmt.SetNamespace("test");
stmt.SetSetName("geo");
stmt.SetFilter(Filter.GeoWithinRadius("loc_bin", -122.0862, 37.4220, 50000));

QueryPolicy queryPolicy = new()
{
    filterExp = Exp.Build(
        Exp.EQ(Exp.StringBin("amenity"), Exp.Val("cafe")))
};

RecordSet rs = client.Query(queryPolicy, stmt);
while (rs.Next())
{
    Console.WriteLine(rs.Record.GetString("name"));
}
rs.Close();

Node.js

const query = client.query("test", "geo");
query.where(Aerospike.filter.geoWithinRadius("loc_bin",
    -122.0862, 37.4220, 50000));

const exp = Aerospike.exp;
const queryPolicy = new Aerospike.QueryPolicy({
  filterExpression: exp.eq(exp.binStr("amenity"), exp.str("cafe")),
});

const stream = query.foreach(queryPolicy);
stream.on("data", (rec) => console.log(rec.bins.name));

Index on list/map

You can index and query GeoJSON elements stored inside list or map bins.

This example creates a geo index on list elements and queries for routes with stops inside a region:

Java

IndexTask task = client.createIndex(null, "test", "geo", "geo-points-idx",
    "stops", IndexType.GEO2DSPHERE, IndexCollectionType.LIST);
task.waitTillComplete();

String region = "{\"type\": \"Polygon\", \"coordinates\": [[" +
    "[-122.500, 37.000], [-121.000, 37.000], " +
    "[-121.000, 38.080], [-122.500, 38.080], " +
    "[-122.500, 37.000]]]}";

Statement stmt = new Statement();
stmt.setNamespace("test");
stmt.setSetName("geo");
stmt.setFilter(Filter.geoWithinRegion("stops", IndexCollectionType.LIST, region));

RecordSet rs = client.query(null, stmt);
while (rs.next()) {
    System.out.println(rs.getRecord().getString("name"));
}
rs.close();

Python

client.index_list_create(
    "test", "geo", "stops",
    aerospike.INDEX_GEO2DSPHERE, "geo-points-idx")

region = aerospike.GeoJSON({
    "type": "Polygon",
    "coordinates": [[
        [-122.500, 37.000], [-121.000, 37.000],
        [-121.000, 38.080], [-122.500, 38.080],
        [-122.500, 37.000]
    ]]
})

query = client.query("test", "geo")
query.where(p.geo_within_geojson_region(
    "stops", region.dumps(), aerospike.INDEX_TYPE_LIST))

for _, _, rec in query.results():
    print(rec["name"])

Go

task, _ := client.CreateComplexIndex(nil, "test", "geo",
    "geo-points-idx", "stops", as.GEO2DSPHERE, as.ICT_LIST)
<-task.OnComplete()

region := `{"type": "Polygon", "coordinates": [[` +
    `[-122.500, 37.000], [-121.000, 37.000], ` +
    `[-121.000, 38.080], [-122.500, 38.080], ` +
    `[-122.500, 37.000]]]}`

stmt := as.NewStatement("test", "geo")
stmt.SetFilter(as.NewGeoWithinRegionForCollectionFilter(
    "stops", as.ICT_LIST, region))

rs, _ := client.Query(nil, stmt)
for rec := range rs.Results() {
    fmt.Println(rec.Record.Bins["name"])
}

C

as_index_task task;
aerospike_index_create_complex(&as, &err, &task, NULL,
    "test", "geo", "stops", "geo-points-idx",
    AS_INDEX_TYPE_LIST, AS_INDEX_GEO2DSPHERE);
aerospike_index_create_wait(&err, &task, 0);

const char* region =
    "{\"type\": \"Polygon\", \"coordinates\": [["
    "[-122.500, 37.000], [-121.000, 37.000], "
    "[-121.000, 38.080], [-122.500, 38.080], "
    "[-122.500, 37.000]]]}";

as_query q;
as_query_init(&q, "test", "geo");
as_query_where_inita(&q, 1);
as_query_where(&q, "stops",
    AS_PREDICATE_RANGE, AS_INDEX_TYPE_LIST,
    AS_INDEX_GEO2DSPHERE, region);

aerospike_query_foreach(&as, &err, NULL, &q, query_cb, NULL);
as_query_destroy(&q);

C#

IndexTask task = client.CreateIndex(null, "test", "geo",
    "geo-points-idx", "stops",
    IndexType.GEO2DSPHERE, IndexCollectionType.LIST);
task.Wait();

string region = "{\"type\": \"Polygon\", \"coordinates\": [[" +
    "[-122.500, 37.000], [-121.000, 37.000], " +
    "[-121.000, 38.080], [-122.500, 38.080], " +
    "[-122.500, 37.000]]]}";

Statement stmt = new();
stmt.SetNamespace("test");
stmt.SetSetName("geo");
stmt.SetFilter(Filter.GeoWithinRegion("stops",
    IndexCollectionType.LIST, region));

RecordSet rs = client.Query(null, stmt);
while (rs.Next())
{
    Console.WriteLine(rs.Record.GetString("name"));
}
rs.Close();

Node.js

await client.createIndex({
  ns: "test", set: "geo", bin: "stops",
  index: "geo-points-idx",
  datatype: Aerospike.indexDataType.GEO2DSPHERE,
  type: Aerospike.indexType.LIST,
});

const region = new Aerospike.GeoJSON({
  type: "Polygon",
  coordinates: [[
    [-122.500, 37.000], [-121.000, 37.000],
    [-121.000, 38.080], [-122.500, 38.080],
    [-122.500, 37.000],
  ]],
});

const query = client.query("test", "geo");
query.where(Aerospike.filter.geoWithinGeoJSONRegion(
    "stops", region, Aerospike.indexType.LIST));

const stream = query.foreach();
stream.on("data", (rec) => console.log(rec.bins.name));

Aerospike GeoJSON extension

Use the Aerospike AeroCircle geometry object to store circles along with regular polygons.

This example specifies a circle with a radius of 300 meters at longitude/latitude -122.250629, 37.871022.

{"type": "AeroCircle", "coordinates": [[-122.250629, 37.871022], 300]}

GeoJSON parsing

On data insert/update, Aerospike only recognizes Point, Polygon, MultiPolygon, and AeroCircle GeoJSON geometry objects, which are indexable objects. Unsupported GeoJSON objects return an AEROSPIKE_ERR_GEO_INVALID_GEOJSON result code 160 (for example, LineString or MultiLineString fail on insert). Holes can be Polygon objects, per the GeoJSON Format Specification.

Note

Polygon loop definitions must wind counter-clockwise.

Aerospike supports the Feature operator, which allows groups of geometry objects and user-specified properties; however, Feature Collection is not supported.

Invalid GeoJSON objects are caught on insert/update. For example, an object defined as point instead of Point fails.

Per the GeoJSON IETF recommendation, the Coordinate System is WGS84. Explicit specification of a coordinate reference system (CRS) is ignored.

Configuration parameters

Parameter	Datatype	Default	Description
max-cells	Integer	8	Defines the maximum number of cells used in the approximation. Increasing this value improves accuracy but may affect query performance.
max-level	Integer	1	Defines the minimum size of the cell to be used in the approximation. Tuning this can make query results more accurate.
min-level	Integer	1	Defines the size of the maximum cell to be used in the approximation. Should generally be set to 1; increasing too much may cause queries to fail.
earth-radius-meters	Integer	6371000	Specifies Earth’s radius in meters. Used for geographical calculations.
level-mod	Integer	1	Specifies the multiple for levels to be used, effectively increasing the branching factor of the S2 Cell Id hierarchy.
strict	Boolean	true	When true, performs additional validation on results to ensure they fall within the query region. When false, returns results as-is, which may include points outside the query region.

max-cells visualization

Here’s an example that shows how RegionCoverer covers a specified region with max-cells set to different values. With a higher value of max-cells, the approximation becomes more accurate.

With max-cells = 10:

With max-cells = 30:

With max-cells = 100:

max-level visualization

Here’s an example to see RegionCoverer covering a specified region and how tuning max-level can make query results more accurate. For this example, min-level is set to 1, and max-cells is set to 10.

With max-level = 12,

With max-level = 30,

Create a geospatial application

To develop a geospatial application:

1. Install and configure the Aerospike server.
2. Create a Geo2DSphere index on a namespace-set-bin combination.
3. Construct and insert GeoJSON Point data.
4. Construct a Points-within-Region predicate (where clause), make a query request, and process the records returned.
5. (alternate) Construct and insert GeoJSON Polygon/MultiPolygon data.
6. (alternate) Construct a Region-contains-Point predicate, make a query request, and process the records returned.

Known limitations

• Using UDFs to insert or update GeoJSON data types is not supported.
• Duplicate records can be returned.
• For namespaces with data-in-memory true, GeoJSON particles allocate up to 2KB more than the reported particle size, which can lead to high memory consumption in some cases. This problem was corrected in Aerospike Database versions 4.9.0 and later.