Geospatial data has interesting properties that can be used when building applications that consume it. Some databases have special functions that use these properties to optimize for certain access patterns. Hadoop and HBase don’t have these functions but are required for scalable applications. In this talk, we’ll cover the challenges of working with geospatial data in Hadoop and HBase, some solutions ideas and how Monsanto implemented their backend for an application working with geospatial data to help increase crop yield.
Erich Hochmuth is lead of the Big Data and Analytics IT team that supports R&D at Monsanto. For the past three years Erich has been working on a cross functional team to build a heterogeneous computing stack to meet the compute and analytic needs of Monsanto’s scientific community.
Amandeep is a Solutions Architect at Cloudera where he’s involved in the entire lifecycle of Hadoop adoption for customers – from use case discovery to taking systems to production. Amandeep is also a co-author of HBase In Action, a book geared towards building applications using HBase. Prior to Cloudera, Amandeep was at Amazon Web Services, where he was a part of the Elastic MapReduce team and built the first version of EMR’s HBase offering.
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