Cherry Garcia: Transactions across Heterogeneous Data Stores

255 Pages·2016·2.68 MB·English

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CHERRY GARCIA:
TRANSACTIONS ACROSS
Linking Named Entities to Wikipedia
HETEROGENEOUS DATA STORES
Will Radford
Supervisor: Dr.JamesR.Curran
Athesissubmitted
infulfilmentoftherequirements
forthedegreeofDoctorofPhilosophy
A thesis submitteSdchoinoloffuIlnfifolrmmaetniotnToefchtnholeogrieesquirements for the
FacultyofEngineering&IT
degree of Doctor of Philosophy in the School of Information Technologies at
TheUniversityofSydney
The University of Sydney
2015
Akon Samir Dey
October 2015
© Copyright by Akon Samir Dey 2016
All Rights Reserved
ii
Abstract
In recent years, cloud or utility computing has revolutionised the way software,
hardware and network infrastructure is provisioned and deployed into production.
A key component of these vast, diverse and heterogeneous systems is the per-
sistence layer provided by a variety of data store and database services, broadly
categorised into what is referred to as NoSQL (Not only SQL) databases or data
stores. These come in many flavours from simple key-value stores and column
stores to database services with support for SQL-like interfaces.
These systems are primarily designed to operate at internet-scale with high
scalability and fault-tolerance in mind. As a result, they typically sacrifice consis-
tency guarantees and often support only single-item consistent operations or no
transactions at all. While these consistency limitations are fine for a wide class of
applications, there are a few or sometimes only parts of larger applications that
need ACID transactional guarantees in order to function correctly.
To address this, we define a data store client API, we call REST+T (REST
withTransactions), anextensionofHTTPthatsupportstransactionsononestore.
Then, we use this to define a client-coordinated transaction commitment protocol
and library, called Cherry Garcia, to enable easy applications development across
diverse, heterogeneous data stores that each support single-item transactions. We
extend the well-known YCSB benchmark, to present YCSB+T, to enable us to
group multiple data store operations into ACID transactions and evaluate proper-
ties such as throughput. YCSB+T also provides the ability to detect and quantify
data store anomalies that result from the execution of the workload. Finally, we
describe our prototype implementations of REST+T in a system called Tora, and
ourclient-coordinatedtransactionlibrary, alsocalledCherryGarcia, thatsupports
transactions across Windows Azure Storage (WAS), Google Cloud Storage (GCS)
and Tora. We evaluate these using both YCSB+T and micro-benchmarks.
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Acknowledgements
This thesis has enabled me to discover my strengths and overcome my weaknesses.
It has taught me to appreciate the friendship and support of family, friends and
colleagues who have enabled, empowered and encouraged me in this endeavour.
I would like to express my deepest gratitude to my supervisor, Prof. Alan
Fekete, forhissupportandguidance. Hiskindness, resourcefulnessandwillingness
to help in my research work and outside of it, made this dissertation possible.
My heartfelt thanks go to my co-supervisor, Assoc. Prof. Uwe R¨ohm, for
his guidance, support, encouragement and ideas on presenting my work. He has
complemented Alan as a guiding force behind this thesis.
IthankmembersoftheDatabaseResearchGroup,MichaelCahill,JackGalilee,
Hyungsoo Jung, Meena Rajani, Ying Zhou, Vincent Gramoli and Paul Greenfield
for their feedback and support. I also grateful to Arunmoezhi Ramachandran,
Raghunath Nambiar, Sherif Sakr, David Bermbach, J¨orn Kuhlemkamp for their
collaboration. Many thanks to Lynne Hutton-Williams and Robyn Kemmis for
their friendship, kindness and timely help.
I am eternally grateful to my parents, Bharati and Samir Dey, for their uncon-
ditional love, a wonderful childhood, and for instilling in me the curiosity to learn.
I thank my brother, Kautuk Dey, for his encouragement and support during this
work.
Mostofall, Iwouldliketothankmywife, Aditi, forherloveandunderstanding
during this very challenging time of our life. I could not have done this without
you.
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Contents
Abstract iii
Acknowledgements v
List of Figures xvi
List of Algorithms xvii
1 Introduction 1
1.1 Problem definition . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Relevant publications . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Organisation of the Thesis . . . . . . . . . . . . . . . . . . . . . . . 4
2 Background 5
2.1 Motivating example . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Database Management Systems . . . . . . . . . . . . . . . . . . . . 6
2.2.1 Transactions in Database Management Systems . . . . . . . 7
2.2.2 Properties of Transactions . . . . . . . . . . . . . . . . . . . 8
2.2.3 Transaction Programming Interface . . . . . . . . . . . . . . 9
2.2.4 Requirements of Transactional Systems . . . . . . . . . . . . 9
2.3 Distributed Concurrency Control . . . . . . . . . . . . . . . . . . . 10
2.4 Serializability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.4.1 Serializability in Distributed Databases . . . . . . . . . . . . 12
2.4.2 Serializability in Heterogeneous Federation . . . . . . . . . . 13
2.4.3 Weak Isolation . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.5 Distributed Transaction Recovery . . . . . . . . . . . . . . . . . . . 15
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2.5.1 The Basic Two-Phase Commit Algorithm . . . . . . . . . . 16
2.5.2 The Transaction Tree Two-Phase Commit Algorithm . . . . 26
2.5.3 Optimised Algorithms for Distributed Commit . . . . . . . . 28
2.6 Distributed systems . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.7 NoSQL and NewSQL database systems . . . . . . . . . . . . . . . . 35
2.8 Transactions in NoSQL database systems . . . . . . . . . . . . . . . 38
2.9 Evaluating database systems . . . . . . . . . . . . . . . . . . . . . . 39
2.9.1 TPC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.9.2 Benchmarks . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
2.9.3 Evaluation metrics . . . . . . . . . . . . . . . . . . . . . . . 42
2.9.4 Properties of a good benchmark . . . . . . . . . . . . . . . . 43
2.10 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3 Related Work 47
3.1 Cloud and web services . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.2 Distributed Concurrency Control . . . . . . . . . . . . . . . . . . . 48
3.3 Distributed Transaction Recovery . . . . . . . . . . . . . . . . . . . 49
3.4 Transaction Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.5 Transactions over HTTP . . . . . . . . . . . . . . . . . . . . . . . . 51
3.6 Transaction support in NoSQL and Cloud Storage Systems . . . . . 52
3.7 Middleware coordinated transactions . . . . . . . . . . . . . . . . . 54
3.8 Client coordinated transactions . . . . . . . . . . . . . . . . . . . . 54
3.8.1 Comparison to our approach . . . . . . . . . . . . . . . . . . 56
3.9 Time in Distributed Systems . . . . . . . . . . . . . . . . . . . . . . 56
3.10 Database benchmarks . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.10.1 Cloud services benchmarks . . . . . . . . . . . . . . . . . . . 58
3.10.2 YCSB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.11 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4 REST+T: Scalable transactions over HTTP 63
4.1 State and state change . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.2 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.3 REST with Transaction support . . . . . . . . . . . . . . . . . . . . 69
4.4 The REST+T Proposal . . . . . . . . . . . . . . . . . . . . . . . . 69
viii
4.4.1 REST+T data header metadata . . . . . . . . . . . . . . . . 72
4.4.2 REST+T methods . . . . . . . . . . . . . . . . . . . . . . . 75
4.5 Limiting REST+T to HTTP verbs . . . . . . . . . . . . . . . . . . 77
4.6 A Case Study - Tora: a transaction-aware NoSQL data store . . . . 78
4.6.1 REST+T interface . . . . . . . . . . . . . . . . . . . . . . . 79
4.6.2 Storage layer . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.7 Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5 Cherry Garcia - The Protocol 81
5.1 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.2 Intuition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.2.1 Overview of Two-Phase Commit . . . . . . . . . . . . . . . . 84
5.2.2 Distributed Two-Phase Commit . . . . . . . . . . . . . . . . 86
5.2.3 Write-Ahead Log (WAL) Protocol . . . . . . . . . . . . . . . 87
5.3 An example application . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.4 Assumptions on the platforms . . . . . . . . . . . . . . . . . . . . . 90
5.5 Protocol overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
5.5.1 Phase 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
5.5.2 Phase 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.6 Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
5.7 Data item records . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.8 Data store abstraction . . . . . . . . . . . . . . . . . . . . . . . . . 95
5.9 Transaction abstraction . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.10 Cherry Garcia Protocol . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.10.1 Start transaction . . . . . . . . . . . . . . . . . . . . . . . . 97
5.10.2 Transactional read . . . . . . . . . . . . . . . . . . . . . . . 97
5.10.3 Transactional write . . . . . . . . . . . . . . . . . . . . . . . 98
5.10.4 Transaction commit . . . . . . . . . . . . . . . . . . . . . . . 100
5.10.5 Transaction abort . . . . . . . . . . . . . . . . . . . . . . . . 102
5.10.6 Transaction recovery . . . . . . . . . . . . . . . . . . . . . . 103
5.10.7 Performance Analysis of the Protocol . . . . . . . . . . . . . 103
5.11 Deadlock detection and avoidance . . . . . . . . . . . . . . . . . . . 104
5.11.1 First preparer wins . . . . . . . . . . . . . . . . . . . . . . . 104
5.11.2 Ensuring at least one winner . . . . . . . . . . . . . . . . . . 105
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