Teradata US, Inc.

Teredata, US, Inc.

Daniel Wong

Congnan Luo

Heng Yuan

Guilian Wang

Relational data for a database table having multiple columns (dimensions) is represented as a histogram. The buckets of the histogram are clustered into clusters, the clusters are fewer in number than the buckets of the histogram. Each cluster is represented in hyper-space as a line segment (vector) with a thickness value. Average frequencies for the line segments (vectors) and their thickness values are computed. The average frequencies are processed by a query optimizer when processing a query predicate of a query to use as an estimation of selectivity or an estimation of a cardinality of a join operation.

Techniques for query processing using high dimension histograms

Statistics for a Relational Database Management System (RDBMS) set of tables are normalized and a grid computed. A particular grid cell having above threshold number of entries from the tables is determined and an R-Tree is dynamically constructed for that grid cell for use when performing a geospatial join operation against the tables.

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San Diego, CA, United States of America

Daniel Wong