Scalable parallel graph algorithms with matrix–vector multiplication evaluated with queries

Graph problems are significantly harder to solve with large graphs residing on disk compared to main memory only. In this work, we study how to solve four important graph problems: reachability from a source vertex, single source shortest path, weakly connected components, and PageRank. It is well k...

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Published in:Distributed and parallel databases : an international journal Vol. 35; no. 3-4; pp. 335 - 362
Main Authors: Cabrera, Wellington, Ordonez, Carlos
Format: Journal Article
Language:English
Published: New York Springer US 01.12.2017
Springer Nature B.V
Subjects:
Algorithms
Computer Science
Data base management systems
Data management
Data Structures
Database Management
Graph algorithms
Information Systems Applications (incl.Internet)
Iterative methods
Mathematical analysis
Matrix algebra
Matrix methods
Memory Structures
Multiplication
Operating Systems
Performance assessment
Queries
Query languages
Rings (mathematics)
Search engines
Shortest-path problems
Special Issue on In-Database Analytics
Data distribution
Parallel computation
Graph
Columnar DBMS
Array DBMS
ISSN:0926-8782, 1573-7578
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Abstract Graph problems are significantly harder to solve with large graphs residing on disk compared to main memory only. In this work, we study how to solve four important graph problems: reachability from a source vertex, single source shortest path, weakly connected components, and PageRank. It is well known that the aforementioned algorithms can be expressed as an iteration of matrix–vector multiplications under different semi-rings. Based on this mathematical foundation, we show how to express the computation with standard relational queries and then we study how to efficiently evaluate them in parallel in a shared-nothing architecture. We identify a common algorithmic pattern that unifies the four graph algorithms, considering a common mathematical foundation based on sparse matrix–vector multiplication. The net gain is that our SQL-based approach enables solving “big data” graph problems on parallel database systems, debunking common wisdom that they are cumbersome and slow. Using large social networks and hyper-link real data sets, we present performance comparisons between a columnar DBMS, an open-source array DBMS, and Spark’s GraphX.
AbstractList Graph problems are significantly harder to solve with large graphs residing on disk compared to main memory only. In this work, we study how to solve four important graph problems: reachability from a source vertex, single source shortest path, weakly connected components, and PageRank. It is well known that the aforementioned algorithms can be expressed as an iteration of matrix–vector multiplications under different semi-rings. Based on this mathematical foundation, we show how to express the computation with standard relational queries and then we study how to efficiently evaluate them in parallel in a shared-nothing architecture. We identify a common algorithmic pattern that unifies the four graph algorithms, considering a common mathematical foundation based on sparse matrix–vector multiplication. The net gain is that our SQL-based approach enables solving “big data” graph problems on parallel database systems, debunking common wisdom that they are cumbersome and slow. Using large social networks and hyper-link real data sets, we present performance comparisons between a columnar DBMS, an open-source array DBMS, and Spark’s GraphX.
Author Cabrera, Wellington
Ordonez, Carlos
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Cites_doi 10.1145/129888.129894
10.1109/TKDE.2009.83
10.14778/2733004.2733057
10.14778/2735471.2735477
10.1561/1900000024
10.1137/1.9780898719581
10.1016/0010-4655(96)00017-3
10.1016/j.is.2016.04.006
10.1109/MNET.2013.6423193
10.1145/2484425.2484441
10.1145/316188.316229
10.1145/775152.775190
10.1109/ICDM.2009.14
10.1145/1559845.1559865
10.1137/1.9780898719918.ch5
10.1145/2484425.2484432
10.1007/978-3-642-22351-8_1
10.1109/BigData.2015.7363873
10.1145/1989323.1989351
10.1145/2615569.2615674
10.1137/1.9780898719918
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Issue 3-4
Keywords Data distribution
Parallel computation
Graph
Columnar DBMS
Array DBMS
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References Idreos, Groffen, Nes, Manegold, Mullender, Kersten (CR12) 2012; 35
Bai, Demmel, Dongarra, Ruhe, van der Vorst (CR2) 2000
Cormen, Leiserson, Rivest, Stein (CR6) 2009
CR19
CR18
CR17
CR16
CR15
CR13
CR11
Ordonez (CR21) 2010; 22
CR10
CR31
CR30
Jindal, Rawlani, Wu, Madden, Deshpande, Stonebraker (CR14) 2014; 7
Mahanti, Carlsson, Mahanti, Arlitt, Williamson (CR20) 2013; 27
Choi, Demmel, Dhillon, Dongarra, Ostrouchov, Petitet, Stanley, Walker, Whaley (CR5) 1996; 97
Bu, Borkar, Jia, Carey, Condie (CR3) 2014; 8
CR4
Zaharia, Chowdhury, Franklin, Shenker, Stoica (CR32) 2010; 10
Abadi, Boncz, Harizopoulos, Idreos, Madden (CR1) 2013; 5
CR8
CR29
CR28
CR9
CR27
CR26
CR25
CR24
CR23
Ordonez, Cabrera, Gurram (CR22) 2016; 63
DeWitt, Gray (CR7) 1992; 35
A Jindal (7200_CR14) 2014; 7
A Mahanti (7200_CR20) 2013; 27
7200_CR27
7200_CR28
7200_CR29
7200_CR23
Y Bu (7200_CR3) 2014; 8
7200_CR24
7200_CR25
7200_CR26
C Ordonez (7200_CR21) 2010; 22
C Ordonez (7200_CR22) 2016; 63
7200_CR4
TH Cormen (7200_CR6) 2009
7200_CR8
S Idreos (7200_CR12) 2012; 35
7200_CR9
D Abadi (7200_CR1) 2013; 5
M Zaharia (7200_CR32) 2010; 10
J Choi (7200_CR5) 1996; 97
7200_CR16
7200_CR17
Z Bai (7200_CR2) 2000
7200_CR18
7200_CR19
7200_CR13
7200_CR15
7200_CR30
7200_CR31
7200_CR10
7200_CR11
D DeWitt (7200_CR7) 1992; 35
References_xml – ident: CR18
– volume: 35
  start-page: 85
  issue: 6
  year: 1992
  end-page: 98
  ident: CR7
  article-title: Parallel database systems: the future of high performance database systems
  publication-title: Commun. ACM
  doi: 10.1145/129888.129894
– ident: CR4
– ident: CR16
– ident: CR30
– ident: CR10
– ident: CR29
– ident: CR8
– volume: 35
  start-page: 40
  issue: 1
  year: 2012
  end-page: 45
  ident: CR12
  article-title: MonetDB: two decades of research in column-oriented database architectures
  publication-title: IEEE Data Eng. Bull.
– volume: 22
  start-page: 264
  issue: 2
  year: 2010
  end-page: 277
  ident: CR21
  article-title: Optimization of linear recursive queries in SQL
  publication-title: IEEE Trans. Knowl. Data Eng. (TKDE)
  doi: 10.1109/TKDE.2009.83
– volume: 7
  start-page: 1669
  issue: 13
  year: 2014
  end-page: 1672
  ident: CR14
  article-title: Vertexica: your relational friend for graph analytics!
  publication-title: Proc. VLDB Endow.
  doi: 10.14778/2733004.2733057
– ident: CR25
– ident: CR27
– ident: CR23
– ident: CR19
– volume: 8
  start-page: 161
  issue: 2
  year: 2014
  end-page: 172
  ident: CR3
  article-title: Pregelix: big(ger) graph analytics on a dataflow engine
  publication-title: Proc. VLDB Endow.
  doi: 10.14778/2735471.2735477
– volume: 5
  start-page: 197
  issue: 3
  year: 2013
  end-page: 280
  ident: CR1
  article-title: The design and implementation of modern column-oriented database systems
  publication-title: Found. Trends® Databases
  doi: 10.1561/1900000024
– year: 2000
  ident: CR2
  publication-title: Templates for the Solution of Algebraic Eigenvalue Problems: A Practical Guide
  doi: 10.1137/1.9780898719581
– year: 2009
  ident: CR6
  publication-title: Introduction to Algorithms
– ident: CR15
– volume: 97
  start-page: 1
  issue: 1–2
  year: 1996
  end-page: 15
  ident: CR5
  article-title: Scalapack: a portable linear algebra library for distributed memory computers-design issues and performance
  publication-title: Comput. Phys. Commun.
  doi: 10.1016/0010-4655(96)00017-3
– ident: CR17
– ident: CR31
– ident: CR13
– ident: CR11
– volume: 10
  start-page: 95
  issue: 10–10
  year: 2010
  ident: CR32
  article-title: Spark: cluster computing with working sets
  publication-title: HotCloud
– ident: CR9
– volume: 63
  start-page: 66
  year: 2016
  end-page: 79
  ident: CR22
  article-title: Comparing columnar, row and array DBMSs to process recursive queries on graphs
  publication-title: Inf. Syst.
  doi: 10.1016/j.is.2016.04.006
– volume: 27
  start-page: 59
  issue: 1
  year: 2013
  end-page: 64
  ident: CR20
  article-title: A tale of the tails: power-laws in internet measurements
  publication-title: IEEE Netw.
  doi: 10.1109/MNET.2013.6423193
– ident: CR28
– ident: CR26
– ident: CR24
– volume-title: Introduction to Algorithms
  year: 2009
  ident: 7200_CR6
– ident: 7200_CR26
  doi: 10.1145/2484425.2484441
– ident: 7200_CR8
  doi: 10.1145/316188.316229
– volume: 35
  start-page: 85
  issue: 6
  year: 1992
  ident: 7200_CR7
  publication-title: Commun. ACM
  doi: 10.1145/129888.129894
– volume: 10
  start-page: 95
  issue: 10–10
  year: 2010
  ident: 7200_CR32
  publication-title: HotCloud
– volume-title: Templates for the Solution of Algebraic Eigenvalue Problems: A Practical Guide
  year: 2000
  ident: 7200_CR2
  doi: 10.1137/1.9780898719581
– ident: 7200_CR27
– ident: 7200_CR15
  doi: 10.1145/775152.775190
– ident: 7200_CR25
– ident: 7200_CR29
– ident: 7200_CR19
– volume: 5
  start-page: 197
  issue: 3
  year: 2013
  ident: 7200_CR1
  publication-title: Found. Trends® Databases
  doi: 10.1561/1900000024
– ident: 7200_CR16
  doi: 10.1109/ICDM.2009.14
– volume: 27
  start-page: 59
  issue: 1
  year: 2013
  ident: 7200_CR20
  publication-title: IEEE Netw.
  doi: 10.1109/MNET.2013.6423193
– ident: 7200_CR11
– ident: 7200_CR24
  doi: 10.1145/1559845.1559865
– volume: 97
  start-page: 1
  issue: 1–2
  year: 1996
  ident: 7200_CR5
  publication-title: Comput. Phys. Commun.
  doi: 10.1016/0010-4655(96)00017-3
– volume: 63
  start-page: 66
  year: 2016
  ident: 7200_CR22
  publication-title: Inf. Syst.
  doi: 10.1016/j.is.2016.04.006
– ident: 7200_CR9
  doi: 10.1137/1.9780898719918.ch5
– ident: 7200_CR31
  doi: 10.1145/2484425.2484432
– ident: 7200_CR23
– volume: 22
  start-page: 264
  issue: 2
  year: 2010
  ident: 7200_CR21
  publication-title: IEEE Trans. Knowl. Data Eng. (TKDE)
  doi: 10.1109/TKDE.2009.83
– volume: 8
  start-page: 161
  issue: 2
  year: 2014
  ident: 7200_CR3
  publication-title: Proc. VLDB Endow.
  doi: 10.14778/2735471.2735477
– ident: 7200_CR30
  doi: 10.1007/978-3-642-22351-8_1
– ident: 7200_CR13
  doi: 10.1109/BigData.2015.7363873
– volume: 7
  start-page: 1669
  issue: 13
  year: 2014
  ident: 7200_CR14
  publication-title: Proc. VLDB Endow.
  doi: 10.14778/2733004.2733057
– ident: 7200_CR28
  doi: 10.1145/1989323.1989351
– ident: 7200_CR18
  doi: 10.1145/2615569.2615674
– ident: 7200_CR10
– ident: 7200_CR17
  doi: 10.1137/1.9780898719918
– ident: 7200_CR4
– volume: 35
  start-page: 40
  issue: 1
  year: 2012
  ident: 7200_CR12
  publication-title: IEEE Data Eng. Bull.
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Snippet Graph problems are significantly harder to solve with large graphs residing on disk compared to main memory only. In this work, we study how to solve four...
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SubjectTerms Algorithms
Computer Science
Data base management systems
Data management
Data Structures
Database Management
Graph algorithms
Information Systems Applications (incl.Internet)
Iterative methods
Mathematical analysis
Matrix algebra
Matrix methods
Memory Structures
Multiplication
Operating Systems
Performance assessment
Queries
Query languages
Rings (mathematics)
Search engines
Shortest-path problems
Special Issue on In-Database Analytics
Title Scalable parallel graph algorithms with matrix–vector multiplication evaluated with queries
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