If you missed this event you can see the recording and presentation here. 

In the era of AI and massive feature stores, efficient data lifecycle management is a foundational requirement for analytical performance and operational stability. This session demystifies Range‑Partitioned Tables (RPTs) in Db2, demonstrating how to design, operate, and maintain large‑scale datasets organized by ranges.
The session begins with the core principles and design patterns of range partitioning, including roll‑in and roll‑out strategies for high‑velocity data ingestion and archival.

Attendees will learn how to use ATTACH, DETACH, and SET INTEGRITY, along with Asynchronous Index Cleanup (AIC), to make new data available quickly or retire historical data with minimal logging and near‑zero downtime.

 We will explore how Data Partition Elimination significantly reduces I/O by accessing only relevant data ranges - an essential optimization for model training, feature extraction, and time‑series analytics - while also addressing locking, concurrency, and backup/recovery considerations specific to partitioned environments.

 The session further examines indexes on range‑partitioned tables, including when to use partitioned versus non‑partitioned indexes and how index design impacts both query performance and maintenance costs.

 Finally, attendees will gain practical guidance on ongoing maintenance and optimization, covering REORG and REORG INDEXES for RPTs, effective use of REORGCHK, and a review of recent Db2 enhancements relevant to partitioned table management.

 By the end of this webinar, participants will have a clear, end‑to‑end blueprint for building and operating a Db2 range‑partitioning strategy that scales reliably to meet the demands of modern AI and analytics workloads.

Speaker:

Wei Cao

Wei Cao is a Senior Technical Manager at the IBM Canada Lab, leading core kernel development for Db2 on Linux, UNIX, and Windows (LUW). With over 15 years of experience in database engine development, she brings deep expertise in Tables, Indexes, Buffer Pools, Table Space Management, and more recently, LOBs and Data Movement Utilities.

Wei has played a key role in designing and delivering impactful features that enhance performance, availability, and resilience in Db2, including:

·       MDC Reclaim Extents for efficient space management

·       Online Index Create for pureScale to improve system uptime

·       Parallel Insert for BLU tables for high-performance analytics

·       Currently Committed for pureScale to boost concurrency

·       Control File Mirroring for enhanced fault tolerance

In 2023, she led the Availability Development Team, delivering Intra-Tablespace Parallelism (ITP) and advancing infrastructure for Transaction Log Management and HADR log replay.

Currently, Wei is focused on evolving the Db2 kernel into the industry’s leading AI-powered data platform, driving innovation at the intersection of data management and artificial intelligence.

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