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CliqueSquare: Flat plans for massively parallel RDF queries

Francois Goasdoue, Zoi Kaoudi, Ioana Manolescu, Jorge-Arnulfo Quiane-Ruiz, Stamatis Zampetakis
2015 2015 IEEE 31st International Conference on Data Engineering  
We present CliqueSquare, a novel optimization approach for evaluating conjunctive RDF queries in a massively parallel environment.  ...  As increasing volumes of RDF data are being produced and analyzed, many massively distributed architectures have been proposed for storing and querying this data.  ...  Contributions We present CliqueSquare, a novel approach for the logical optimization of BGP queries over large RDF graphs distributed in a massively parallel environment, such as MapReduce.  ... 
doi:10.1109/icde.2015.7113332 dblp:conf/icde/GoasdoueKMQZ15 fatcat:vvikryub6ja4tpkndyjlwhebbu

CliqueSquare in action: Flat plans for massively parallel RDF queries

Benjamin Djahandideh, Francois Goasdoue, Zoi Kaoudi, Ioana Manolescu, Jorge-Arnulfo Quiane-Ruiz, Stamatis Zampetakis
2015 2015 IEEE 31st International Conference on Data Engineering  
The main technical novelty of CliqueSquare resides in its logical query optimization algorithm, guaranteed to find a logical plan as flat as possible for a given query, meaning: a plan having the smallest  ...  CliqueSquare's ability to build flat plans allows it to take advantage of a parallel processing framework in order to shorten response times.  ...  To increase inter-operator parallelism one should aim at building massively-parallel (flat) plans, having as few (join) operators as possible on any root-to-leaf path in the plan; this is because the processing  ... 
doi:10.1109/icde.2015.7113394 dblp:conf/icde/DjahandidehGKMQ15 fatcat:y44cqk6ipzddbccmcf62hrmmbq

ICDE conference 2015 detailed author index

2015 2015 IEEE 31st International Conference on Data Engineering  
: Flat Plans for Massively Parallel RDF Queries 1432 CliqueSquare in Action: Flat Plans for Massively Parallel RDF Queries 1541 Reasoning on Web Data: Algorithms and Performance G continues on  ...  : Flat Plans for Massively Parallel RDF Queries 1432 CliqueSquare in Action: Flat Plans for Massively Parallel RDF Queries [Search] A B C D E F G H I J K L M N O P Q R S T U V W X Y Z R Rabl,  ... 
doi:10.1109/icde.2015.7113260 fatcat:ep7pomkm55f45j33tkpoc5asim

Storage, Indexing, Query Processing, and Benchmarking in Centralized and Distributed RDF Engines: A Survey [article]

Waqas Ali, Muhammad Saleem, Bin Yao, Aidan Hogan, Axel-Cyrille Ngonga Ngomo
2020 arXiv   pre-print
This massive adoption has paved the way for the development of various centralized and distributed RDF processing engines.  ...  The type of the underlying querying language (e.g., SPARQL or SQL) used for query execution is a crucial optimization component of the RDF storage solutions.  ...  The massive adoption of the RDF format requires effective solutions for storing and querying this massive amount of data.  ... 
arXiv:2009.10331v2 fatcat:ou4nctjyj5c6jbh4osclewj62e

ICDE conference 2015 table of contents

2015 2015 IEEE 31st International Conference on Data Engineering  
: Flat Plans for Massively Parallel RDF Queries (François Goasdoué, Zoi Kaoudi, Ioana Manolescu, Jorge-Arnulfo Quiané-Ruiz, Stamatis Zampetakis) 783 INSURE: An Integrated Load Reduction Framework  ...  Research Session 24: Query Processing 3 1083 Scalable Parallelization of Skyline Computation for Multi-Core Processors (Sean Chester, Darius Šidlauskas, Ira Assent, Kenneth S.  ...  Industry Session 3: Big Data 1304 Accelerating Big Data Analytics with Collaborative Planning in Teradata Aster 6 (Aditi Pandit, Derrick Kondo, David Simmen, Anjali Norwood, Tongxin Bai) [Search]  ... 
doi:10.1109/icde.2015.7113258 fatcat:yvim4gc5rfhevoehwfvl35nqji

SPARQL query processing with Apache Spark [article]

Hubert Naacke and Olivier Curé and Bernd Amann
2016 arXiv   pre-print
A detailed experimentation, on real-world and synthetic data sets, emphasizes that two approaches tailored for the RDF data model outperform the other ones on all major query shapes, i.e., star, snowflake  ...  As a consequence, semantic RDF services are more and more confronted to various "big data" problems.  ...  Impala [15] is a Massively Parallel Processing (MPP) database on Hadoop that plans the parallelization and fragmentation of SQL queries using a dedicated query processor.  ... 
arXiv:1604.08903v2 fatcat:476zynifujglffe5qmonprbjlu

A Survey of RDF Stores SPARQL Engines for Querying Knowledge Graphs [article]

Waqas Ali, Muhammad Saleem, Bin Yao, Aidan Hogan, Axel-Cyrille Ngonga Ngomo
2021 arXiv   pre-print
RDF has seen increased adoption in recent years, prompting the standardization of the SPARQL query language for RDF, and the development of local and distributed engines for processing SPARQL queries.  ...  This survey paper provides a comprehensive review of techniques and systems for querying RDF knowledge graphs.  ...  CliqueSquare [75] (2015) is a Hadoop-based RDF engine used to store and process massive RDF graphs.  ... 
arXiv:2102.13027v4 fatcat:phontczhbfcvdjt5y75n3hfcge

Scalable Discovery and Analytics on Web Linked Data

Ibrahim Abdelaziz
2018
To address the scalability limitation of federated RDF engines, we propose Lusail; a scalable system for querying geo-distributed RDF graphs.  ...  Several distributed and federated RDF systems have emerged to handle the massive amounts of RDF data available nowadays.  ...  The flat plans do not improve the performance CliqueSquare compared to H2RDF+.  ... 
doi:10.25781/kaust-pg966 fatcat:r6mjiift6fgj5msmuntzfmcnnq

Accelerating SPARQL Queries and Analytics on RDF Data Dissertation by EXAMINATION COMMITTEE

Razen Al-Harbi, Razen Al-Harbi
2016 unpublished
The locality-aware query optimizer of AdPart takes full advantage of the partitioning to (i) support the fully parallel processing of join patterns on subjects and (ii) minimize data communication for  ...  Being primarily designed and optimized to execute SPARQL queries, which lack procedural capabilities, existing systems are not suitable for rich RDF analytics.  ...  The flat plans of CliqueSquare significantly reduce the joins overhead for complex queries.  ... 
fatcat:6dfkuah4wzdo3hq7zc3lxdjqea