Bringing Together Physical Design and Fast Querying of Large Data Warehouses
| Autor: | Mohamed Kechar, Safia Nait-Bahloul |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Theoretical computer science
Computer science 05 social sciences 02 engineering and technology Fact table Partition (database) Data warehouse Oracle Set (abstract data type) Star schema 0502 economics and business Genetic algorithm 0202 electrical engineering electronic engineering information engineering Benchmark (computing) 020201 artificial intelligence & image processing 050203 business & management |
| Zdroj: | BDIoT |
| DOI: | 10.1145/3372938.3372947 |
| Popis: | Data partitioning is a well-known technique for decision-support query performance optimization. In this paper, we present a horizontal data partitioning approach tailored to a large data warehouse, interrogated through a high number of queries. The idea behind our approach is to partition horizontally only the large fact table based on partitioning predicates, elected from the set of the selection predicates used by the analytic queries. The partitioning predicates election depends on their numbers of occurrences, their access frequencies, and their selectivities. With the Star Scheme Benchmark under Oracle 12c, we demonstrate that our partitioning technique reduces both query response time and fact partitions number; which is the major drawback of existing partitioning techniques. We also show, that our partitioning algorithm is around 66% faster compared to the primary and derived partitioning techniques based on the genetic algorithm. |
| Databáze: | OpenAIRE |
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