K nearest neighbor is a proximity algorithm to find data in order of distance. Typically, this data cannot be indexed in advance, as both the centroid and the data can be in constant motion. PostgreSQL provides efficient searching algorithms for finding proximity data on the fly, including unique high-performance indexing options.

In this webinar, Kirk Roybal talked about the following topics:

• What is K-nearest neighbor?
• What can I do with it?
• What kinds of data can I search for?
• How expensive is it to the query planner?
• How do I minimize that cost?

Preview

Kirk Roybal is a Principal Consultant at 2ndQuadrant. He is a long time PostgreSQL DBA and published author for PostgreSQL. Kirk has used and overseen the implementation of PostgreSQL to manage financial systems, nuclear reactors, military ordinance, and hospital information systems.

Kirk is also the founder and frequent speaker at the Dallas/Fort Worth PostgreSQL Meetup Group. With over 300 members, the DFW PostgreSQL User Group is one of the largest in the USA.