4. Getting Started

This chapter highlights several features of GeoMesa, along with tutorials for getting started.

4.1. Quick Start

The GeoMesa quick start tutorials are the fastest and easiest way to get started with GeoMesa. They are a good stepping-stone on the path to the other tutorials that present increasingly involved examples of how to use GeoMesa. The tutorials show how to write custom Java code to ingest and query data with GeoMesa, and visualize the changes being made in GeoServer.

Quick starts are available for several back-end databases:

4.2. GeoDocker: Bootstrapping GeoMesa Accumulo and Spark on AWS

Getting started with spatio-temporal analysis with GeoMesa, Accumulo, and Spark on Amazon Web Services (AWS) is incredibly simple, thanks to the Geodocker project. The guide below describes how to bootstrap a GeoMesa Accumulo cluster using Amazon ElasticMapReduce (EMR) and Docker in order to ingest and query sample GDELT data.

See GeoDocker: Bootstrapping GeoMesa Accumulo and Spark on AWS.

4.3. GeoMesa Kafka

The GeoMesa Kakfa Quick Start tutorial shows how to write custom Java code to produce and consume messages in Apache Kafka using GeoMesa, query the data and visualize the changes being made in Kafka with GeoServer.

See GeoMesa Kafka Quick Start.

4.4. Storm Analysis

GeoMesa can leverage the Apache Storm distributed computation system to ingest and analyze geospatial data in near real time. The GeoMesa Storm Quick Start tutorial shows how to use Kafka, GeoMesa, and Storm to parse Open Street Map data files and ingest them into Accumulo.

See GeoMesa Storm Quick Start.

4.5. GeoJSON

GeoMesa provides built-in integration with GeoJSON. GeoMesa provides a GeoJSON API that allows for the indexing and querying of GeoJSON data without using the GeoTools API–all data and operations are pure JSON. The API also includes a REST endpoint for web integration.

See GeoMesa GeoJSON.