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Rethinking System Design With Awareness for Cross-Layer Aspects of Datacenter Storage
Rethinking System Design With Awareness for Cross-Layer Aspects of Datacenter Storage
Rethinking System Design With Awareness for Cross-Layer Aspects of Datacenter Storage

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자료유형  
 학위논문 서양
최종처리일시  
20250211151451
ISBN  
9798382808048
DDC  
004
저자명  
Raina, Ashwini.
서명/저자  
Rethinking System Design With Awareness for Cross-Layer Aspects of Datacenter Storage
발행사항  
[Sl] : Princeton University, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
104 p
주기사항  
Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
주기사항  
Advisor: Freedman, Michael J.
학위논문주기  
Thesis (Ph.D.)--Princeton University, 2024.
초록/해제  
요약Storage is a critical piece of infrastructure in modern web applications. In recent years, storage technologies employed in building such systems have undergone significant evolution, bringing about novel cost-performance trade-offs. Concurrently, datacenter storage architectures have become increasingly layered. Software systems designed based on outdated assumptions of datacenter storage often result in poor cost-performance trade-offs or suffer from suboptimal performance. This dissertation proposes a new design approach for systems, one that incorporates the awareness of cross-layer aspects of datacenter storage, and validates the effectiveness of this approach through two systems.The first system is PrismDB, a novel key-value store that exploits two extreme ends of the spectrum of modern NVMe storage technologies (3D XPoint and QLC NAND) simultaneously. In recent years, emerging storage technologies have focused on divergent goals: better performance or lower cost. Correspondingly, data systems that employ these technologies are typically optimized either to be fast (but expensive) or cheap (but slow). PrismDB take a different approach: by architecting a storage engine to natively utilize two tiers of fast and low-cost storage technologies, it shows that a Pareto-efficient balance between performance and cost can be achieved.The second system is Fusion, an object store for analytics that is optimized for query pushdown on erasure-coded data. Computation pushdown is a widely adopted technique to reduce latency of highly selective queries in modern OLAP cloud database running on disaggregated storage. However, existing pushdown solutions are inefficient on erasure-coded storage since the analytics file objects get partitioned across storage nodes. Consequently, the storage system must reassemble the object across nodes before executing the query, leading to significant network latency. Fusion addresses this problem by co-designing its erasure coding and file placement topologies, taking into account popular analytics file formats (e.g., Parquet). It employs a novel stripe construction algorithm that prevents the fragmentation of computable units within an object, and minimizes storage overhead during erasure coding.Overall, this dissertation advocates for designing software systems with an awareness of cross-layer aspects in datacenter storage, and demonstrates the benefits of that approach via two systems: PrismDB and Fusion.
일반주제명  
Computer science
일반주제명  
Architectural engineering
키워드  
Datacenter storage
키워드  
Distributed systems
키워드  
Key-value store
키워드  
Object store
키워드  
Storage systems
키워드  
Tiered storage
기타저자  
Princeton University Computer Science
기본자료저록  
Dissertations Abstracts International. 85-12B.
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

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■035    ▼a(MiAaPQ)AAI31296766
■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a004
■1001  ▼aRaina,  Ashwini.▼0(orcid)0000-0002-3367-009X
■24510▼aRethinking  System  Design  With  Awareness  for  Cross-Layer  Aspects  of  Datacenter  Storage
■260    ▼a[Sl]▼bPrinceton  University▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a104  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  85-12,  Section:  B.
■500    ▼aAdvisor:  Freedman,  Michael  J.
■5021  ▼aThesis  (Ph.D.)--Princeton  University,  2024.
■520    ▼aStorage  is  a  critical  piece  of  infrastructure  in  modern  web  applications.  In  recent  years,  storage  technologies  employed  in  building  such  systems  have  undergone  significant  evolution,  bringing  about  novel  cost-performance  trade-offs.  Concurrently,  datacenter  storage  architectures  have  become  increasingly  layered.  Software  systems  designed  based  on  outdated  assumptions  of  datacenter  storage  often  result  in  poor  cost-performance  trade-offs  or  suffer  from  suboptimal  performance.  This  dissertation  proposes  a  new  design  approach  for  systems,  one  that  incorporates  the  awareness  of  cross-layer  aspects  of  datacenter  storage,  and  validates  the  effectiveness  of  this  approach  through  two  systems.The  first  system  is  PrismDB,  a  novel  key-value  store  that  exploits  two  extreme  ends  of  the  spectrum  of  modern  NVMe  storage  technologies  (3D  XPoint  and  QLC  NAND)  simultaneously.  In  recent  years,  emerging  storage  technologies  have  focused  on  divergent  goals:  better  performance  or  lower  cost.  Correspondingly,  data  systems  that  employ  these  technologies  are  typically  optimized  either  to  be  fast  (but  expensive)  or  cheap  (but  slow).  PrismDB  take  a  different  approach:  by  architecting  a  storage  engine  to  natively  utilize  two  tiers  of  fast  and  low-cost  storage  technologies,  it  shows  that  a  Pareto-efficient  balance  between  performance  and  cost  can  be  achieved.The  second  system  is  Fusion,  an  object  store  for  analytics  that  is  optimized  for  query  pushdown  on  erasure-coded  data.  Computation  pushdown  is  a  widely  adopted  technique  to  reduce  latency  of  highly  selective  queries  in  modern  OLAP  cloud  database  running  on  disaggregated  storage.  However,  existing  pushdown  solutions  are  inefficient  on  erasure-coded  storage  since  the  analytics  file  objects  get  partitioned  across  storage  nodes.  Consequently,  the  storage  system  must  reassemble  the  object  across  nodes  before  executing  the  query,  leading  to  significant  network  latency.  Fusion  addresses  this  problem  by  co-designing  its  erasure  coding  and  file  placement  topologies,  taking  into  account  popular  analytics  file  formats  (e.g.,  Parquet). It  employs  a  novel  stripe  construction  algorithm  that  prevents  the  fragmentation  of  computable  units  within  an  object,  and  minimizes  storage  overhead  during  erasure  coding.Overall,  this  dissertation  advocates  for  designing  software  systems  with  an  awareness  of  cross-layer  aspects  in  datacenter  storage,  and  demonstrates  the  benefits  of  that  approach  via  two  systems:  PrismDB  and  Fusion.
■590    ▼aSchool  code:  0181.
■650  4▼aComputer  science
■650  4▼aArchitectural  engineering
■653    ▼aDatacenter  storage
■653    ▼aDistributed  systems
■653    ▼aKey-value  store
■653    ▼aObject  store
■653    ▼aStorage  systems
■653    ▼aTiered  storage
■690    ▼a0984
■690    ▼a0543
■690    ▼a0462
■71020▼aPrinceton  University▼bComputer  Science.
■7730  ▼tDissertations  Abstracts  International▼g85-12B.
■790    ▼a0181
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161835▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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