Towards Dynamic Data Placement for Polystore Ingestion
| Autor: | Stan Zdonik, Nesime Tatbul, John Meehan, Jiang Du |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
060201 languages & linguistics
Database business.industry Computer science Dynamic data Workload Context (language use) 06 humanities and the arts 02 engineering and technology computer.software_genre Data warehouse 020204 information systems 0602 languages and literature Computer data storage Benchmark (computing) 0202 electrical engineering electronic engineering information engineering Data ingestion 020201 artificial intelligence & image processing business computer Data placement |
| Zdroj: | Real-Time Business Intelligence and Analytics ISBN: 9783030241230 BIRTE (Revised Selected Papers) |
| Popis: | Integrating low-latency data streaming into data warehouse architectures has become an important enhancement to support modern data warehousing applications. In these architectures, heterogeneous workloads with data ingestion and analytical queries must be executed with strict performance guarantees. Furthermore, the data warehouse may consists of multiple different types of storage engines (a.k.a., polystores or multi-stores). A paramount problem is data placement; different workload scenarios call for different data placement designs. Moreover, workload conditions change frequently. In this paper, we provide evidence that a dynamic, workload-driven approach is needed for data placement in polystores with low-latency data ingestion support. We study the problem based on the characteristics of the TPC-DI benchmark in the context of an abbreviated polystore that consists of S-Store and Postgres. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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