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2019 | OriginalPaper | Chapter

Towards Dynamic Data Placement for Polystore Ingestion

Authors : Jiang Du, John Meehan, Nesime Tatbul, Stan Zdonik

Published in: Real-Time Business Intelligence and Analytics

Publisher: Springer International Publishing

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Abstract

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.

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previous chapter DCS: A Policy Framework for the Detection of Correlated Data Streams
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Metadata
Title
Towards Dynamic Data Placement for Polystore Ingestion
Authors
Jiang Du
John Meehan
Nesime Tatbul
Stan Zdonik
Copyright Year
2019
Book
Real-Time Business Intelligence and Analytics

Print ISBN: 978-3-030-24123-0

Electronic ISBN: 978-3-030-24124-7

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-24124-7_13