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Data Replication in Hybrid Memory Database Systems

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Osoby i podmioty: Zarubin, Mikhail, Lehner, Wolfgang, Habich, Dirk
Tytuł: Data Replication in Hybrid Memory Database Systems
Hochschulschriftenvermerk: Dissertation, Technische Universität Dresden, 2022
Medientyp: E-book Praca dyplomowa
Język: Englisch
Online-Ausg.. 2022
Hasła przedmiotowe:
Źródło: Qucosa
Streszczenie: The recent advances in hardware technologies - i.e. highly scalable multi-core NUMA architectures and non-volatile random-access memory (NVRAM) - lead to significant changes in the architecture of in-memory database systems. The novel memory type allows persistent writes while featuring DRAM-like characteristics - byte addressability, high bandwidth, and low access latencies. It is likely to complement or replace the block-based secondary storage (e.g., HDDs or SSDs) for storing the primary data of the DBMS. Therefore, the next generation of highly-performant scalable database systems will rely on single-level hybrid memory (e.g., compound exclusively of DRAM and NVRAM) NUMA architectures and is expected to keep the primary data solely persistent in NVRAM, while query processing could be executed on both mediums. Unfortunately, NVRAM faces certain drawbacks such as a lower write endurance, lower bandwidth, higher latencies, and - most importantly - an increased error-proneness compared to DRAM. Thus, efficient minimal-overhead data protection mechanisms have to be deployed in the underlined architectures to avoid primary data losses. This thesis provides an analytical overview of such envisioned hybrid memory database systems, gives a survey of reliability techniques that are generally deployed in computing systems, identifies their strengths and weaknesses when used in hybrid memory databases. As a result, this work proposes effective adoption and optimization primitives for the software-managed data replication as the most applicable resilience approach. In particular, research focus is given to runtime and space (and, therefore, NVRAM wear-out) reduction of the replication overheads, while preserving strong resilience guaranties and instant recovery opportunities. Subsequently, this thesis proposes a rich set of techniques that leverage data replication for query processing needs to achieve high performance, allocation flexibility and effective hardware utilization in modern commodity scale-up systems.