Relevance Modeling with Multiple Query Variations

2019 ◽  
Author(s):  
Xiaolu Lu ◽  
Oren Kurland ◽  
J. Shane Culpepper ◽  
Nick Craswell ◽  
Ofri Rom
Keyword(s):  
Multiple Query

Workload scheduling for multiple query processing

1995 ◽  
Vol 55 (5) ◽  
pp. 251-257 ◽  
Author(s):  
Kian-Lee Tan ◽  
Hongjun Lu
Keyword(s):  
Query Processing ◽  
Workload Scheduling ◽  
Multiple Query

A Hybrid Approach for Data Warehouse View Selection

2008 ◽  
pp. 3085-3115
Author(s):  
Biren Shah ◽  
Karthik Ramachandran ◽  
Vijay Raghavan
Keyword(s):  
Data Warehouse ◽  
Hybrid Approach ◽  
Greedy Heuristic ◽  
Materialized Views ◽  
View Selection ◽  
Materialized View Selection ◽  
Optimal Efficiency ◽  
Access Patterns ◽  
Multiple Query ◽  
Selection Of

Materialized view selection is one of the crucial decisions in designing a data warehouse for optimal efficiency. Static selection of views may materialize certain views that are not beneficial as the data and usage trends change over time. On the contrary, dynamic selection of views works better only for queries demanding a high degree of aggregation. These facts point to the need for a technique that combines the improved response time of the static approach and the automated tuning capability of the dynamic approach. In this article, we propose a hybrid approach for the selection of materialized views. The idea is to partition the collection of all views into a static and dynamic set such that views selected for materialization from the static set are persistent over multiple query (and maintenance) windows, whereas views selected from the dynamic set can be queried and/or replaced on the fly. Highly aggregated views are selected on the fly based on the query access patterns of users, whereas the more detailed static set of views plays a significant role in the efficient maintenance of the dynamic set of views and in answering certain detailed view queries. We prove that our proposed strategy satisfies the monotonicity requirements, which is essential in order for the greedy heuristic to deliver competitive solutions. Experimental results show that our approach outperforms Dynamat, a well-known dynamic view management system that is known to outperform optimal static view selection.

Sign in / Sign up

Export Citation Format

Share Document