:Author: Peter Baumann (p.baumann@jacobs-university.de) :Version: osgeo-live7.0 :License: Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) .. _rasdaman-quickstart: .. image:: ../../images/project_logos/logo-rasdaman.png :scale: 100 % :alt: project logo :align: right :target: http://www.rasdaman.org ******************** rasdaman Quickstart ******************** rasdaman is a Big Data Engine for flexible ad-hoc analytics on multi-dimensional spatio-temporal sensor, image, simulation, and statistics data of unlimited size. Exploring the 1-D to 4-D examples ================================= OSGeo Live contains a multitude of interactive 1D through 4D rasdaman demos. * Go to the `multi-dimensional demo `_ to explore these demos. * The small ones are part of OSGeo-Live, those utilizing larger sets (beyond this drive's capacity) forward to the `OGC standards showcase site `_ . Running queries on the OSGeo database ===================================== * Open a console, type in commands for sending queries and receive results. Here is an example combining red and blue bands from a sample RGB image:: $ rasql -q "select png( rgb.red + rgb.blue ) from rgb" --out file --filename osgeo.png * use your favorite image inspection tool to open the file generated. Things to Try ============= Here are some additional challenges for you to try: * Experiment with your own queries; the `rasql query language guide `_ is your friend. * To learn more about the OGC `Web Coverage Processing Service `_ (WCPS) Language standard (which was heavily inspired by rasdaman); a good starting point is the `documentation and tutorials page `_ . * Interested in coverage data and services in general? Visit OGC's `Coverages Domain Working Group wiki `_. Create your own database ======================== * Open a console, `Download and install rasdaman `_ and `its prerequisites `_, run the demo ingestion script:: $ install_demo.sh * use the rasql utility for querying, for example the one from above or this one:: $ rasql -q "select csv( marray bucket in [0:255] values count_cells( rgb.red = bucket ) ) from rgb --out string" * add your own datasets (see ``_ for details), publish them via OGC services.