GeoMesa is an open source suite of tools that enables large-scale geospatial querying and analytics on distributed computing systems. GeoMesa provides spatio-temporal indexing on top of the Accumulo, HBase, Google Bigtable and Cassandra databases for massive storage of point, line, and polygon data. GeoMesa also provides near real time stream processing of spatio-temporal data by layering spatial semantics on top of Apache Kafka. Through GeoServer, GeoMesa facilitates integration with a wide range of existing mapping clients over standard OGC (Open Geospatial Consortium) APIs and protocols such as WFS and WMS. GeoMesa supports Apache Spark for custom distributed geospatial analytics.
GeoMesa is a member of the LocationTech working group of the Eclipse Foundation.
- Main documentation
- Upgrade Guide
- Quick Starts: HBase | Accumulo | Cassandra | Kafka | Redis | FileSystem
- Tutorials
Current release: 3.4.1
HBase | Accumulo | Cassandra | Kafka | Redis | FileSystem | Bigtable
Downloads hosted on GitHub include SHA-256 hashes and gpg signatures (.asc files). To verify a download using gpg, import the appropriate key:
$ gpg2 --keyserver hkp://pool.sks-keyservers.net --recv-keys CD24F317
Then verify the file:
$ gpg2 --verify geomesa-accumulo_2.12-3.4.1-bin.tar.gz.asc geomesa-accumulo_2.12-3.4.1-bin.tar.gz
The keys currently used for signing are:
Key ID | Name |
---|---|
CD24F317 |
Emilio Lahr-Vivaz <elahrvivaz(-at-)ccri.com> |
1E679A56 |
James Hughes <jnh5y(-at-)ccri.com> |
GeoMesa is hosted on Maven Central. To include it as a dependency, add the desired modules, for example:
<dependency>
<groupId>org.locationtech.geomesa</groupId>
<artifactId>geomesa-hbase-datastore_2.12</artifactId>
<version>3.4.1</version>
</dependency>
GeoMesa depends on several third-party libraries that are only available in separate repositories. To include GeoMesa in your project, add the following repositories to your pom:
<repositories>
<!-- geotools -->
<repository>
<id>osgeo</id>
<url>https://repo.osgeo.org/repository/release</url>
</repository>
<!-- confluent -->
<repository>
<id>confluent</id>
<url>https://packages.confluent.io/maven/</url>
</repository>
</repositories>
Snapshot versions are published nightly to the Eclipse repository:
<repository>
<id>geomesa-snapshots</id>
<url>https://repo.eclipse.org/content/repositories/geomesa-snapshots</url>
<releases>
<enabled>false</enabled>
</releases>
<snapshots>
<enabled>true</enabled>
</snapshots>
</repository>
GeoMesa publishes spark-runtime
JARs for integration with Spark environments like Databricks. These
shaded JARs include all the required dependencies in a single artifact. When importing through Maven, all
transitive dependencies can be excluded. There are Spark runtime JARs available for most of the different
DataStore implementations:
<dependency>
<groupId>org.locationtech.geomesa</groupId>
<artifactId>geomesa-gt-spark-runtime_2.12</artifactId>
<version>3.4.1</version>
<exclusions>
<exclusion>
<!-- if groupId wildcards are not supported, the two main ones are jline:* and org.geotools:* -->
<groupId>*</groupId>
<artifactId>*</artifactId>
</exclusion>
</exclusions>
</dependency>
These JARs are also included in the Downloads bundles, above.
Similarly, integration with sbt
is straightforward:
// Add necessary resolvers
resolvers ++= Seq(
"osgeo" at "https://repo.osgeo.org/repository/release",
"confluent" at "https://packages.confluent.io/maven"
)
// Select desired modules
libraryDependencies ++= Seq(
"org.locationtech.geomesa" %% "geomesa-utils" % "3.4.1"
)
Development version: 3.5.0-SNAPSHOT
Requirements:
- Git
- Java JDK 8
- Apache Maven 3.6.3 or later
Use Git to download the source code. Navigate to the destination directory, then run:
git clone [email protected]:locationtech/geomesa.git
cd geomesa
The project is built using Maven. To build, run:
mvn clean install
The full build takes quite a while. To speed it up, you may skip tests and use multiple threads. GeoMesa also
provides the script build/mvn
, which is a wrapper around Maven that downloads and runs
Zinc, a fast incremental compiler:
build/mvn clean install -T8 -DskipTests
If the Zinc build fails with an error finding "javac", try setting the JAVA_HOME environment variable to point to the root of your JDK. Example from a Mac:
JAVA_HOME="/Library/Java/JavaVirtualMachines/jdk1.8.0_51.jdk/Contents/Home" build/mvn clean install
To build for a different Scala version (e.g. 2.11), run the following script, then build as normal:
./build/change-scala-version.sh 2.11