Oracle Spatial Indexing: Faster Queries with Spatial-Temporal Data

How can you optimize spatial queries that filter by location, time, and other attributes? This Ask TOM Live session explains how Oracle Spatial indexes support spatial-temporal queries and demonstrates how composite indexes, execution-plan analysis, and spatial configuration can improve query performance. You will learn how to: Understand R-tree and composite B-tree spatial indexes Combine location and time filtering in one index Create and query spatial-temporal indexes Use execution plans to verify index selection Apply spatial operators such as SDO_WITHIN_DISTANCE Improve spatial query performance with spatial acceleration and function-based indexes Oracle Spatial Developer’s Guide: https://docs.oracle.com/en/database/o... Creating spatial indexes: https://docs.oracle.com/en/database/o... Spatial operators and functions: https://docs.oracle.com/en/database/o... Review the documentation and test these indexing patterns with your own spatial dataset. Chapters 00:00 Introduction and session context 06:00 Oracle Spatial indexing recap 12:45 Spatial-temporal query patterns 14:08 Enhanced spatial indexing in Oracle AI Database 19:14 Creating spatial indexes 24:15 Composite B-tree index configuration 29:56 Comparing query execution plans 38:28 Notebook discussion and questions 41:02 Spatial performance best practices 45:28 Composite B-tree index best practices 58:00 Spatial vector acceleration and final recommendations 01:01:02 Q&A and closing discussion #OracleAIDatabase #OracleSpatial #SpatialIndexing #DatabasePerformance #SQL