Linguagens de consulta para bases de dados em grafos: um mapeamento sistemático

A popularizacao das redes sociais, associado a necessidade de analisar e sumarizar grandes volumes de dados oriundos das mesmas tem favorecido o uso de bases de dados em grafos. As linguagens de consulta a este tipo de base de dados devem, ao mesmo tempo, ter expressividade suficiente para a realizacao de consultas complexas e possibilitarem o processamento eficiente de grandes volumes de dados. Este artigo apresenta um mapeamento sistematico sobre as linguagens de consulta para bases de dados em grafos, com foco nas suas caracteristicas principais como paradigma ou capacidade de agregacao de dados. O foco deste mapeamento e investigar e quantificar as publicacoes referentes as linguagens de consulta, caracterizando-as, identificando possiveis areas de pesquisa, tendencias e desafios.

[1]  C. Fourrier.  Constraint-based Queries in a Geographical Database for Network Facilities , 2007 .

[2]  Timos K. Sellis,et al.  Efficient compilation of large rule bases using logical access paths , 1990, Inf. Syst..

[3]  Jessie B. Kennedy,et al.  The Prometheus taxonomic database , 2000, Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering.

[4]  David Dominguez-Sal,et al.  Using semijoin programs to solve traversal queries in graph databases , 2014, GRADES.

[5]  Jianzhong Li,et al.  Efficient Subgraph Matching on Billion Node Graphs , 2012, Proc. VLDB Endow..

[6]  Yinghui Wu,et al.  SLQ: a user-friendly graph querying system , 2014, SIGMOD Conference.

[7]  Lise Getoor,et al.  Subgraph pattern matching over uncertain graphs with identity linkage uncertainty , 2014, 2014 IEEE 30th International Conference on Data Engineering.

[8]  Peter Milligan,et al.  Range queries over skip tree graphs , 2008, Comput. Commun..

[9]  Salim Jouili,et al.  An Empirical Comparison of Graph Databases , 2013, 2013 International Conference on Social Computing.

[10]  Alan G. Labouseur,et al.  A demonstration of the G∗ graph database system , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[11]  Monica S. Lam,et al.  SociaLite: Datalog extensions for efficient social network analysis , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).

[12]  Chang-Sup Park,et al.  Efficient processing of keyword queries over graph databases for finding effective answers , 2015, Inf. Process. Manag..

[13]  Yinghui Wu,et al.  Emerging Graph Queries in Linked Data , 2012, 2012 IEEE 28th International Conference on Data Engineering.

[14]  Marios D. Dikaiakos,et al.  Querying the Data Web: The MashQL Approach , 2010, IEEE Internet Computing.

[15]  Vasant Honavar,et al.  Clustering remote RDF data using SPARQL update queries , 2013, 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW).

[16]  Federica Mandreoli,et al.  Flexible query answering on graph-modeled data , 2009, EDBT '09.

[17]  Mohammed J. Zaki,et al.  GRAIL: a scalable index for reachability queries in very large graphs , 2011, The VLDB Journal.

[18]  Amol Deshpande,et al.  EAGr: supporting continuous ego-centric aggregate queries over large dynamic graphs , 2014, SIGMOD Conference.

[19]  Jürgen Umbrich,et al.  Searching and browsing Linked Data with SWSE: The Semantic Web Search Engine , 2011, J. Web Semant..

[20]  Rui Wang,et al.  A stream partitioning approach to processing large scale distributed graph datasets , 2013, 2013 IEEE International Conference on Big Data.

[21]  Alberto O. Mendelzon,et al.  Expressing structural hypertext queries in graphlog , 1989, Hypertext.

[22]  Alfredo Cuzzocrea,et al.  A reachability-based theoretical framework for modeling and querying complex probabilistic graph data , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[23]  Rakesh Agrawal,et al.  Extending SQL with Generalized Transitive Closure Functionality , 1993, IEEE Trans. Knowl. Data Eng..

[24]  Dan Suciu,et al.  Distributed query evaluation on semistructured data , 2002, TODS.

[25]  Tim Furche,et al.  pest: Fast approximate keyword search in semantic data using eigenvector-based term propagation , 2012, Inf. Syst..

[26]  Rolf Stadler,et al.  Graph search for cloud network management , 2014, 2014 IEEE Network Operations and Management Symposium (NOMS).

[27]  Roberto De Virgilio,et al.  Converting relational to graph databases , 2013, GRADES.

[28]  Nicolas Bruno,et al.  SCOPE: parallel databases meet MapReduce , 2012, The VLDB Journal.

[29]  Yunkai Liu,et al.  Graph Data Warehouse: Steps to Integrating Graph Databases Into the Traditional Conceptual Structure of a Data Warehouse , 2013, 2013 IEEE International Congress on Big Data.

[30]  Philip S. Yu,et al.  On Pattern Preserving Graph Generation , 2013, 2013 IEEE 13th International Conference on Data Mining.

[31]  Ciro Cattuto,et al.  Time-varying social networks in a graph database: a Neo4j use case , 2013, GRADES.

[32]  Leonidas Fegaras,et al.  Supporting Bulk Synchronous Parallelism in Map-Reduce Queries , 2012, 2012 SC Companion: High Performance Computing, Networking Storage and Analysis.

[33]  Yehoshua Sagiv,et al.  Language models for keyword search over data graphs , 2012, WSDM '12.

[34]  Hasan M. Jamil.  Design of Declarative Graph Query Languages: On the Choice between Value, Pattern and Object Based Representations for Graphs , 2012, 2012 IEEE 28th International Conference on Data Engineering Workshops.

[35]  Yang Xiang,et al.  3-HOP: a high-compression indexing scheme for reachability query , 2009, SIGMOD Conference.

[36]  Vito Giovanni Castellana,et al.  Accelerating semantic graph databases on commodity clusters , 2013, 2013 IEEE International Conference on Big Data.

[37]  Yerach Doytsher,et al.  Querying geo-social data by bridging spatial networks and social networks , 2010, LBSN '10.

[38]  Chang Zhou,et al.  GLog: A high level graph analysis system using MapReduce , 2014, 2014 IEEE 30th International Conference on Data Engineering.

[39]  Josep-Lluís Larriba-Pey,et al.  Benchmarking database systems for social network applications , 2013, GRADES.

[40]  Zhen Lin,et al.  HBase System-Based Distributed Framework for Searching Large Graph Databases , 2013, 2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing.

[41]  Yannis Kotidis,et al.  Business intelligence on complex graph data , 2012, EDBT-ICDT '12.

[42]  Loredana Laera,et al.  Enterprise BigGraph , 2013, 2013 46th Hawaii International Conference on System Sciences.

[43]  Philip S. Yu,et al.  BLINKS: ranked keyword searches on graphs , 2007, SIGMOD '07.

[44]  Jeremy J. Carroll,et al.  Resource description framework (rdf) concepts and abstract syntax , 2003 .

[45]  Nan Li,et al.  Neighborhood based fast graph search in large networks , 2011, SIGMOD '11.

[46]  Claudio Gutiérrez,et al.  Querying RDF Data from a Graph Database Perspective , 2005, ESWC.

[47]  Anton Dries,et al.  Analyzing graph databases by aggregate queries , 2010, MLG '10.

[48]  Haixun Wang,et al.  A Distributed Graph Engine for Web Scale RDF Data , 2013, Proc. VLDB Endow..

[49]  Antonino Tumeo,et al.  Toward a data scalable solution for facilitating discovery of scientific data resources , 2013, DISCS-2013.

[50]  Fan Wang,et al.  Answering complex structured queries over the deep web , 2011, IDEAS '11.

[51]  HyeongSik Kim,et al.  To nest or not to nest, when and how much: representing intermediate results of graph pattern queries in MapReduce based processing , 2012, SWIM '12.

[52]  Ying Ding,et al.  Community detection: Topological vs. topical , 2011, J. Informetrics.

[53]  Claudia Roncancio,et al.  Graph Data Transformations and Querying , 2014, C3S2E.

[54]  Han-Wei Shen,et al.  GraphCharter: Combining browsing with query to explore large semantic graphs , 2013, 2013 IEEE Pacific Visualization Symposium (PacificVis).

[55]  Simone Santini,et al.  On Querying OBO Ontologies Using a DAG Pattern Query Language , 2006, DILS.

[56]  Jennifer Widom,et al.  GPS: a graph processing system , 2013, SSDBM.

[57]  Bernhard Mitschang,et al.  Query processing for complex objects , 1992, Data Knowl. Eng..

[58]  Vito Giovanni Castellana,et al.  Toward a data scalable solution for facilitating discovery of science resources , 2014, Parallel Comput..

[59]  Carole A. Goble,et al.  API-centric Linked Data integration: The Open PHACTS Discovery Platform case study , 2014, J. Web Semant..

[60]  Kai Petersen,et al.  Systematic Mapping Studies in Software Engineering , 2008, EASE.

[61]  Oded Shmueli,et al.  SoQL: A Language for Querying and Creating Data in Social Networks , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[62]  V. S. Subrahmanian,et al.  COSI: Cloud Oriented Subgraph Identification in Massive Social Networks , 2010, 2010 International Conference on Advances in Social Networks Analysis and Mining.

[63]  Luc De Raedt,et al.  A query language for analyzing networks , 2009, CIKM.

[64]  René Peinl,et al.  Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j , 2013, EDBT '13.

[65]  Renzo Angles,et al.  A Comparison of Current Graph Database Models , 2012, 2012 IEEE 28th International Conference on Data Engineering Workshops.

[66]  Schahram Dustdar,et al.  Expressive languages for selecting groups from graph-structured data , 2013, WWW.

[67]  Gerhard Weikum,et al.  STAR: Steiner-Tree Approximation in Relationship Graphs , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[68]  Wei Wang,et al.  Keyword-based search and exploration on databases , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[69]  Svetha Venkatesh,et al.  Semantic data modelling and visualisation using Noetica , 2000, Data Knowl. Eng..

[70]  Xiang Lian,et al.  k-nearest keyword search in RDF graphs , 2013, J. Web Semant..

[71]  K. Selçuk Candan,et al.  R2DF framework for ranked path queries over weighted RDF graphs , 2011, WIMS '11.

[72]  Jignesh M. Patel,et al.  Periscope/GQ: a graph querying toolkit , 2008, Proc. VLDB Endow..

[73]  Rinkle Rani,et al.  Modeling and querying data in NoSQL databases , 2013, 2013 IEEE International Conference on Big Data.

[74]  Louiqa Raschid,et al.  Flexible and efficient querying and ranking on hyperlinked data sources , 2009, EDBT '09.

[75]  James Bailey,et al.  A Query Based Approach for Mining Evolving Graphs , 2009, AusDM.

[76]  Gultekin Özsoyoglu,et al.  Querying Multimedia Presentations Based on Content , 1999, IEEE Trans. Knowl. Data Eng..

[77]  Pranjul Yadav,et al.  Benchmarking over a Semantic Repository , 2010, ICoAC 2010.

[78]  Panos Constantopoulos,et al.  Shortcut selection in RDF databases , 2011, 2011 IEEE 27th International Conference on Data Engineering Workshops.

[79]  Giovanni Tummarello,et al.  Searching web data: An entity retrieval and high-performance indexing model , 2012, J. Web Semant..

[80]  Vito Giovanni Castellana,et al.  Composing Data Parallel Code for a SPARQL Graph Engine , 2013, 2013 International Conference on Social Computing.

[81]  Haofen Wang,et al.  Hermes: Data Web search on a pay-as-you-go integration infrastructure , 2009, J. Web Semant..

[82]  James Cheng,et al.  Structure and attribute index for approximate graph matching in large graphs , 2011, Inf. Syst..

[83]  Sherif Sakr,et al.  Hybrid query execution engine for large attributed graphs , 2014, Inf. Syst..

[84]  Claudio Gutierrez,et al.  Survey of graph database models , 2008, CSUR.

[85]  Andrej Chu,et al.  Distributed SPARQL Query Answering over RDF Data Streams , 2013, 2013 IEEE International Congress on Big Data.

[86]  Chao Yang,et al.  Unicorn: A System for Searching the Social Graph , 2013, Proc. VLDB Endow..

[87]  Carlo Zaniolo,et al.  Extending the power of datalog recursion , 2012, The VLDB Journal.

[88]  Johannes Gehrke,et al.  Fast Iterative Graph Computation with Block Updates , 2013, Proc. VLDB Endow..

[89]  Jeffrey Heer,et al.  Orion: A system for modeling, transformation and visualization of multidimensional heterogeneous networks , 2011, IEEE VAST.

[90]  Sameh Elnikety,et al.  Horton+: A Distributed System for Processing Declarative Reachability Queries over Partitioned Graphs , 2013, Proc. VLDB Endow..

[91]  Gianluca Demartini,et al.  Combining inverted indices and structured search for ad-hoc object retrieval , 2012, SIGIR '12.

[92]  Peter T. Wood,et al.  Query languages for graph databases , 2012, SGMD.

[93]  Yehoshua Sagiv,et al.  Efficiently enumerating results of keyword search over data graphs , 2008, Inf. Syst..

[94]  Bertram Ludäscher,et al.  On implementing provenance-aware regular path queries with relational query engines , 2013, EDBT '13.

[95]  Bo Zong,et al.  Towards effective partition management for large graphs , 2012, SIGMOD Conference.

[96]  Pablo Barceló,et al.  Querying graph databases , 2013, PODS '13.

[97]  Olivier Curé,et al.  On The Potential Integration of an Ontology-Based Data Access Approach in NoSQL Stores , 2013, Int. J. Distributed Syst. Technol..

[98]  Tim Furche,et al.  Web and Semantic Web Query Languages: A Survey , 2005, Reasoning Web.

[99]  Alan Mycroft,et al.  Source-code queries with graph databases - with application to programming language usage and evolution , 2015, Sci. Comput. Program..

[100]  Jürgen Umbrich,et al.  An empirical survey of Linked Data conformance , 2012, J. Web Semant..

[101]  Vassilis Christophides,et al.  Querying the Semantic Web with RQL , 2003, Comput. Networks.

[102]  Erhard Rahm,et al.  BIIIG: Enabling business intelligence with integrated instance graphs , 2014, 2014 IEEE 30th International Conference on Data Engineering Workshops.

[103]  Mike Buerli.  The Current State of Graph Databases , 2012 .