For the last several years, GeoWave has been an important tool for the US government, which leverages GeoWave to create a variety of solutions fueled by geospatial big data. But while our USG connection is stronger than ever and will continue to deepen, the drive for the GeoWave team now is diversity. We’re actively engaging with software developers from non-USG enterprises with new interests—with the goal of building the GeoWave ecosystem and significantly growing the set of contributors to the project.

To that end, DigitalGlobe’s Rich Fecher, Michael Whitby and Kent Miller recently gave a powerful demonstration of GeoWave and its applications at the CalGIS/LocationCon conference. Their objective was to demonstrate the scale that developers can achieve with GeoWave, as well as the spatial sub-sampling and distributed rendering that make it possible for GeoWave users to display incredibly large volumes of data.

First came an impressive GeoWave workshop, which demonstrated both the power of GeoWave and the ease of scaling GeoWave operations in Amazon Web Services (AWS). The team outlined how GeoWave integrates GIS with distributed computing pitch, and then wowed the audience by spinning up an AWS cluster on the spot! That cluster ran both HBase and Accumulo, pulled pre-ingested tables from S3 with significant amounts of vector and raster data on them, and used the GeoWave cli commands to setup layers for all of the data in GeoServer—all in a process that took less than 10 minutes!

Scalability and ease of use were also key themes of Rich Fecher’s Wednesday presentation, which guided the audience through a variety of examples showing how GeoWave can be used to efficiently visualize and analyze very large datasets. Perhaps the most impressive part of Rich’s presentation was his demonstration of GeoWave’s ability to manage and map the massive New York City Taxi and Limousine Commission’s (NYCTLC) public taxi trip data.

While the conference was going on, we learned that GeoWave had been accepted by the Eclipse Foundation as a LocationTech project. This has been one of the key goals of the LocationTech Working Group, and having GeoWave now officially in LocationTech incubation should bring the system wider awareness and exposure to many new big data users.

Among our key takeaways from the conference was the strong interest in new collaboration on HBase using S3 instead of HDFS, as well as in Spark SQL. Overall, the conference was successful in spreading the word about GeoWave, and in making it easier for new developers to understand and work with it. We eagerly anticipate welcoming new contributors to the ecosystem as a result of the team’s hard work at CalGIS/LocationCon.


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