Provided by: Harvard University
Topic: Big Data
Date Added: Sep 2010
Ideally, realizing the best physical design for the current and all subsequent workloads would impact neither performance nor storage usage. In reality, workloads and datasets can change dramatically over time and index creation impacts the performance of concurrent user and system activity. The authors propose a framework that evaluates the key premise of adaptive indexing - a new indexing paradigm where index creation and re-organization take place automatically and incrementally, as a side-effect of query execution. They focus on how the incremental costs and benefits of dynamic reorganization are distributed across the workload's lifetime.