Elasticsearch is a popular distributed search and analytics engine that enables complex search features in near real-time. Default field type mappings support string, numeric, boolean and date types and allow complex, hierarchical documents. Custom field type mappings can be defined for geospatial document fields. The geo_point type supports point geometries that can be specified through a coordinate string, geohash or coordinate array. The geo_shape type supports Point, LineString, Polygon, MultiPoint, MultiLineString, MultiPolygon and GeometryCollection GeoJSON types as well as envelope and circle types. Custom options allow configuration of the type and precision of the spatial index.
This data store allows features from an Elasticsearch index to be published through GeoServer. Both geo_point and geo_shape type mappings are supported. OGC filters are converted to Elasticsearch queries and can be combined with native Elasticsearch queries in WMS and WFS requests.
- Java: 1.8
- GeoServer: 2.14.x
- Elasticsearch: 2.4.x, 5.x, 6.x
Pre-compiled binaries can be found on the GitHub releases page.
Unpack zipfile and copy plugin file to the WEB_INF/lib directory of your GeoServer installation and then restart GeoServer.
Clone project:
$ git clone git@github.com:ngageoint/elasticgeo.git
Build and install plugin (requires GeoServer restart):
$ mvn clean install -DskipTests=true -Dskip.integration.tests=true $ cp gs-web-elasticsearch/target/elasticgeo*.jar GEOSERVER_HOME/WEB_INF/lib
Run default tests:
$ mvn verify -Dskip.integration.tests=true
Run default and integration tests (requires Docker):
$ mvn verify
Note running integration tests in an IDE development environment requires that a local Elasticsearch instance is running and accepting HTTP connections over port 9200 (see Elasticsearch documentation).
Once the Elasticsearch GeoServer extension is installed, Elasticsearch index will be an available vector data source format when creating a new data store.
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The Elasticsearch data store configuration panel includes standard connection parameters and search settings.
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Available data store configuration parameters are summarized in the following table:
| Parameter | Description |
| elasticsearch_host | Host (IP) for connecting to Elasticsearch. HTTP scheme and port can optionally be included to override the defaults. Multiple hosts can be provided. Examples: localhost localhost:9200 http://localhost http://localhost:9200 https://localhost:9200 https://somehost.somedomain:9200,https://anotherhost.somedomain:9200 |
| elasticsearch_port | Default HTTP port for connecting to Elasticsearch. Ignored if the hostname includes the port. |
| index_name | Index name or alias (wildcards supported) |
| ssl_enabled | Use https instead of http scheme by default. Ignored if the hostname includes the HTTP scheme. Use system properties to configure the SSL connection: javax.net.ssl.trustStore javax.net.ssl.trustStorePassword javax.net.ssl.keyStore javax.net.ssl.keyStorePassword |
| reject_unauthorized | Whether to validate the server certificate during the SSL handshake for https connections |
| default_max_features | Default used when maxFeatures is unlimited |
| source_filtering_enabled | Whether to enable filtering of the _source field |
| scroll_enabled | Enable the Elasticsearch scan and scroll API |
| scroll_size | Number of documents per shard when using the scroll API |
| scroll_time | Search context timeout when using the scroll API |
| array_encoding | Array encoding strategy. Allowed values are JSON (keep arrays) and CSV (keep first array element). |
| grid_size | Hint for Geohash grid size (numRows*numCols) |
| grid_threshold | Geohash grid aggregation precision will be the minimum necessary so that actual_grid_size/grid_size > grid_threshold |
System properties are supported for SSL/TLS configuration. See HttpClientBuilder documentation for available properties.
For example use javax.net.ssl.trustStore[Password] to validate server certificate:
$ export JAVA_OPTS="-Djavax.net.ssl.trustStore=/path/to/truststore.jks -Djavax.net.ssl.trustStorePassword=changeme $JAVA_OPTS "
The initial layer configuration panel for an Elasticsearch layer will include an additional pop-up showing a table of available fields.
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| Item | Description |
Use All |
Use all fields in the layer feature type |
Short Names |
For hierarchical documents with inner fields (e.g. parent.child.field_name), only use the base name
(field_name) in the schema. Note, full path will always be included when the base name is duplicated across fields. |
Use |
Used to select the fields that will make up the layer feature type |
Name |
Name of the field |
Type |
Type of the field, as derived from the Elasticsearch schema. For geometry types, you have the option to provide a more specific data type. |
Default Geometry |
Indicates if the geometry field is the default one. Useful if the documents contain more than one geometry field, as SLDs and spatial filters will hit the default geometry field unless otherwise specified |
Stored |
Indicates whether the field is stored in the index |
Analyzed |
Indicates whether the field is analyzed |
SRID |
Native spatial reference ID of the geometries. Currently only EPSG:4326 is supported. |
Date Format |
Date format used for parsing field values and printing filter elements |
To return to the field table after it has been closed, click the "Configure Elasticsearch fields" button below the "Feature Type Details" panel on the layer configuration page.
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Logging is configurable through Log4j. The data store includes logging such as the query object being sent to Elasticsearch, which is logged at a lower level than may be enabled by default. To enable these logs, add the following lines to the GeoServer logging configuration file (see GeoServer Global Settings):
log4j.category.mil.nga.giat.data.elasticsearch=DEBUG log4j.category.mil.nga.giat.process.elasticsearch=DEBUG
The logging configuration file will be in the logs subdirectory in the GeoServer data directory. Check GeoServer global settings for which file is being used (e.g. DEFAULT_LOGGING.properties, etc.).
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Filtering capabilities include OpenGIS simple comparisons, temporal comparisons, as well as other common filter comparisons. Elasticsearch natively supports numerous spatial filter operators, depending on the type:
geo_shapetypes natively support BBOX/Intersects, Within and Disjoint binary spatial operatorsgeo_pointtypes natively support BBOX and Within binary spatial operators, as well as the DWithin and Beyond distance buffer operators
Requests involving spatial filter operators not natively supported by Elasticsearch will include an additional filtering operation on the results returned from the query, which may impact performance.
Native Elasticsearch queries can be applied in WFS/WMS feature requests by including the q:{query_body} key:value pair in the viewparams parameter (see GeoServer SQL Views documentation for more information). If supplied, the query is combined with the query derived from the request bbox, CQL or OGC filter using the AND logical binary operator.
BBOX and CQL filter:
http://localhost:8080/geoserver/test/wms?service=WMS&version=1.1.0&request=GetMap
&layers=test:active&styles=&bbox=-1,-1,10,10&width=279&height=512
&srs=EPSG:4326&format=application/openlayers&maxFeatures=1000
&cql_filter=standard_ss='IEEE 802.11b'
BBOX and native query:
http://localhost:8080/geoserver/test/wms?service=WMS&version=1.1.0&request=GetMap
&layers=test:active&styles=&bbox=-1,-1,10,10&width=279&height=512
&srs=EPSG:4326&format=application/openlayers&maxFeatures=1000
&viewparams=q:{"term":{"standard_ss":"IEEE 802.11b"}}
Native query with BBOX filter:
http://localhost:8080/geoserver/test/wms?service=WMS&version=1.1.0&request=GetMap
&layers=test:active&styles=&bbox=-1,-1,10,10&width=279&height=512
&srs=EPSG:4326&format=application/openlayers&maxFeatures=1000
&viewparams=q:{"term":{"standard_ss":"IEEE 802.11b"}}
Note that commas in native queries must be escaped with a backslash.
Elasticsearch aggregations are supported through WFS/WMS requests by including the a:{aggregation_body} key:value pair in the viewparams parameter (see GeoServer SQL Views documentation for more information):
http://localhost:8080/geoserver/test/ows?service=WFS&version=1.0.0&request=GetFeature
&typeName=test:active&bbox=0.0,0.0,24.0,44.0
&viewparams=a:{"agg": {"geohash_grid": {"field": "geo"\, "precision": 3}}}
Aggregation WFS features will include a single attribute, _aggregation, containing the raw aggregation content. Note that size is set to zero when an aggregation is supplied so only aggregation features are returned (e.g. maxFeatures is ignored and there will be no search hit results). See FAQ for common issues using aggregations.
Geohash grid aggregation support includes dynamic precision updating and a custom rendering transformation for visualization. Geohash grid aggregation precision is updated dynamically to approximate the specified grid_size based on current bbox extent and the additional grid_threshold parameter as described above.
Geohash grid aggregation visualization is supported in WMS requests through a custom rendering transformation, vec:GeoHashGrid, which translates aggregation response data into a raster for display. By default raster values correspond to the aggregation bucket doc_count. The following shows an example GeoServer style that uses the GeoHashGrid rendering transformation:
<StyledLayerDescriptor version="1.0.0"
xsi:schemaLocation="http://www.opengis.net/sld StyledLayerDescriptor.xsd"
xmlns="http://www.opengis.net/sld"
xmlns:ogc="http://www.opengis.net/ogc"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<NamedLayer>
<Name>GeoHashGrid</Name>
<UserStyle>
<Title>GeoHashGrid</Title>
<Abstract>GeoHashGrid aggregation</Abstract>
<FeatureTypeStyle>
<Transformation>
<ogc:Function name="vec:GeoHashGrid">
<ogc:Function name="parameter">
<ogc:Literal>data</ogc:Literal>
</ogc:Function>
<ogc:Function name="parameter">
<ogc:Literal>gridStrategy</ogc:Literal>
<ogc:Literal>Basic</ogc:Literal>
</ogc:Function>
<ogc:Function name="parameter">
<ogc:Literal>pixelsPerCell</ogc:Literal>
<ogc:Literal>1</ogc:Literal>
</ogc:Function>
<ogc:Function name="parameter">
<ogc:Literal>outputBBOX</ogc:Literal>
<ogc:Function name="env">
<ogc:Literal>wms_bbox</ogc:Literal>
</ogc:Function>
</ogc:Function>
<ogc:Function name="parameter">
<ogc:Literal>outputWidth</ogc:Literal>
<ogc:Function name="env">
<ogc:Literal>wms_width</ogc:Literal>
</ogc:Function>
</ogc:Function>
<ogc:Function name="parameter">
<ogc:Literal>outputHeight</ogc:Literal>
<ogc:Function name="env">
<ogc:Literal>wms_height</ogc:Literal>
</ogc:Function>
</ogc:Function>
</ogc:Function>
</Transformation>
<Rule>
<RasterSymbolizer>
<Geometry>
<!-- Actual geometry property name in feature source -->
<ogc:PropertyName>geo</ogc:PropertyName></Geometry>
<Opacity>0.6</Opacity>
<ColorMap type="ramp" >
<ColorMapEntry color="#FFFFFF" quantity="0" label="nodata" opacity="0"/>
<ColorMapEntry color="#2851CC" quantity="1" label="values"/>
<ColorMapEntry color="#211F1F" quantity="2" label="label"/>
<ColorMapEntry color="#EE0F0F" quantity="3" label="label"/>
<ColorMapEntry color="#AAAAAA" quantity="4" label="label"/>
<ColorMapEntry color="#6FEE4F" quantity="5" label="label"/>
<ColorMapEntry color="#DDB02C" quantity="10" label="label"/>
</ColorMap>
</RasterSymbolizer>
</Rule>
</FeatureTypeStyle>
</UserStyle>
</NamedLayer>
</StyledLayerDescriptor>
Example WMS request including Geohash grid aggregation with the above custom style:
http://localhost:8080/geoserver/test/wms?service=WMS&version=1.1.0&request=GetMap
&layers=test:active&styles=geohashgrid&bbox=0.0,0.0,24.0,44.0&srs=EPSG:4326
&width=418&height=768&format=application/openlayers
&viewparams=a:{"agg": {"geohash_grid": {"field": "geo"\, "precision": 3}}}
gridStrategy: Parameter to identify the mil.nga.giat.process.elasticsearch.GeoHashGrid implementation that will be used to convert each geohashgrid bucket into a raster value (number).
| Name | gridStrategy | gridStrategyArgs | Description |
| Basic | basic |
no | Raster value is geohashgrid bucket doc_count. |
| Metric | metric |
yes | Raster value is geohashgrid bucket metric value. |
| Nested | nested_agg |
yes | Extract raster value from nested aggregation results. |
gridStrategyArgs: (Optional) Parameter used to specify an optional argument list for the grid strategy.
emptyCellValue: (Optional) Parameter used to specify the value for empty grid cells. By default, empty grid cells are set to 0.
scaleMin, scaleMax: (Optional) Parameters used to specify a scale applied to all raster values. Each tile request is scaled according to the min and max values for that tile. It is best to use a non-tiled layer with this parameter to avoid confusing results.
useLog: (Optional) Flag indicating whether to apply logarithm to raster values (applied prior to scaling, if applicable)
Raster value is geohashgrid bucket doc_count.
Example Aggregation:
{
"agg": {
"geohash_grid": {
"field": "geo"
}
}
}
Example bucket:
{
"key" : "xv",
"doc_count" : 1
}
Extracted raster value: 1
Raster value is geohashgrid bucket metric value.
| Argument Index | Default Value | Description |
| 0 | metric |
Key used to pluck metric object from top level bucket. Empty string results in plucking doc_count. |
| 1 | value |
Key used to pluck the value from the metric object. |
Example Aggregation:
{
"agg": {
"geohash_grid": {
"field": "geo"
},
"aggs": {
"metric": {
"max": {
"field": "magnitude"
}
}
}
}
}
Example bucket:
{
"key" : "xv",
"doc_count" : 1,
"metric" : {
"value" : 4.9
}
}
Extracted raster value: 4.9
Extract raster value from nested aggregation results.
| Argument Index | Default Value | Description |
| 0 | nested |
Key used to pluck nested aggregation results from the geogrid bucket. |
| 1 | empty string | Key used to pluck metric object from each nested aggregation bucket. Empty string results in plucking doc_count. |
| 2 | value |
Key used to pluck the value from the metric object. |
| 3 | largest |
largest | smallest. Strategy used to select a bucket from the nested aggregation buckets. The grid cell raster value is extracted from the selected bucket. |
| 4 | value |
key | value. Strategy used to extract the raster value from the selected bucket. value: Raster value is the selected bucket's metric value. key: Raster value is the selected bucket's key. |
| 5 | null | (Optional) Map used to convert String keys into numeric values. Use the format key1:1;key2:2. Only utilized when raster strategy is key. |
Example Aggregation:
{
"agg": {
"geohash_grid": {
"field": "geo"
},
"aggs": {
"nested": {
"histogram": {
"field": "magnitude",
"interval": 1,
"min_doc_count": 1
}
}
}
}
}
Example Parameters:
<ogc:Function name="parameter"> <ogc:Literal>gridStrategyArgs</ogc:Literal> <ogc:Literal>nested</ogc:Literal> <ogc:Literal></ogc:Literal> <ogc:Literal></ogc:Literal> <ogc:Literal>largest</ogc:Literal> <ogc:Literal>key</ogc:Literal> </ogc:Function>
Example bucket:
{
"key" : "xv",
"doc_count" : 1729,
"nested" : {
"buckets" : [
{
"key" : 2.0,
"doc_count" : 5
},
{
"key" : 3.0,
"doc_count" : 107
},
{
"key" : 4.0,
"doc_count" : 1506
},
{
"key" : 5.0,
"doc_count" : 100
},
{
"key" : 6.0,
"doc_count" : 11
}
]
}
}
Extracted raster value: 4.0
By default the raster values computed in the geohash grid aggregation rendering transformation correspond to the top level doc_count. Adding an additional strategy for computing the raster values from bucket data currently requires source code updates to the gt-elasticsearch-process module as described below.
First create a custom implementation of mil.nga.giat.process.elasticsearch.GeoHashGrid and provide an implementation of the computeCellValue method, which takes the raw bucket data and returns the raster value. For example the default basic implementation simply returns the doc_count:
public class BasicGeoHashGrid extends GeoHashGrid {
@Override
public Number computeCellValue(Map<String,Object> bucket) {
return (Number) bucket.get("doc_count");
}
}
Then update mil.nga.giat.process.elasticsearch.GeoHashGridProcess and add a new entry to the Strategy enum to point to the custom implementation.
After deploying the customized plugin the new geohash grid computer can be used by updating the gridStrategy parameter in the GeoServer style:
<StyledLayerDescriptor version="1.0.0"
...
<Transformation>
<ogc:Function name="vec:GeoHashGrid">
...
<ogc:Function name="parameter">
<ogc:Literal>gridStrategy</ogc:Literal>
<ogc:Literal>NewName</ogc:Literal>
</ogc:Function>
- By default arrays are returned directly, which is suitable for many output formats including GeoJSON. When using CSV output format with layers containing arrays it's necessary to set the
array_encodingstore parameter toCSV. Note however when using theCSVarray encoding that only the first value will be returned. - When updating from pre-2.11.0 versions of the plugin it may be necessary to reload older layers to enable full aggregation and time support. Missing aggregation data or errors of the form
IllegalArgumentException: Illegal pattern componentindicate a layer reload is necessary. In this case the layer must be removed and re-added to GeoServer (e.g. a feature type reload will not be sufficient). - Commas in the native query and aggregation body must be escaped with a backslash. Additionally body may need to be URL encoded.
- Geometry property name in the aggregation SLD RasterSymbolizer must be a valid geometry property in the layer
PropertyIsEqualTomaps to an Elasticsearch term query, which will return documents that contain the supplied term. When searching on an analyzed string field, ensure that the search values are consistent with the analyzer used in the index. For example, values may need to be lowercase when querying fields analyzed with the default analyzer. See the Elasticsearch term query documentation for more information.PropertyIsLikemaps to either a query string query or a regexp query, depending on whether the field is analyzed or not. Reserved characters should be escaped as applicable. Note case sensitive and insensitive searches may not be supported for analyzed and not analyzed fields, respectively. See Elasticsearch query string and regexp query documentation for more information.- Date conversions are handled using the date format from the associated type mapping, or
date_optional_timeif not found. Note that UTC timezone is used for both parsing and printing of dates. - Filtering on Elasticsearch
objecttypes is supported. By default, field names will include the full path to the field (e.g. "parent.child.field_name"), but this can be changed in the GeoServer layer configuration.- When referencing fields with path elements using
cql_filter, it may be necessary to quote the name (e.g.cql_filter="parent.child.field_name"='value')
- When referencing fields with path elements using
- Filtering on Elasticsearch
nestedtypes is supported only for non-geospatial fields. - Circle geometries are not currently supported
- The
joda-shadedmodule may need to be excluded when importing the project into Eclipse. Otherwise modules may have build errors of the formDateTimeFormatter cannot be resolved to a type.