Processing of OLAP and SOLAP Queries on Parallel and Distributed Environments

• Grant number: 18/22277-8
• Support Opportunities: Regular Research Grants
• Start date: February 01, 2019
• End date: April 30, 2021
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Cristina Dutra de Aguiar
• Grantee: Cristina Dutra de Aguiar
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• City of the host institution: São Carlos

Abstract

Processing OLAP (on-line analytical processing) queries is very expensive because of the huge volume of data stored in the data warehouse and the fact that they perform star-join. Processing SOLAP queries is even more expensive, since spatial data warehouses are more voluminous and perform the star-join extended with costly topological predicates. The processing of OLAP and SOLAP queries can be benefited by the use of computational environments with large storage and processing capacities. In these environments, it is common the use of parallel and distributed programming paradigms, such as the Apache Hadoop MapReduce and the Apache Spark frameworks. Recently, these frameworks have been extended by DSDMSs (distributed spatial data management systems), which aim to store, index, and process huge volumes of spatial data (e.g.: SpatialHadoop e SpatialSpark). This research project is aimed to propose solutions for the efficient processing of OLAP and SOLAP queries on parallel and distributed environments. Its specific objectives are: (i) the star-join processing considering slice and dice queries with low selectivity; (ii) the star-join processing considering drill-down, roll-up, and drill-across queries with high and low selectivity; (iii) a comparative analyses of DSDMSs available in the literature; and (iv) the star-join processing extended with topological predicates, using as a basis functionalities provided by DSDMSs. (AU)

Scientific publications

(11)

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

ROCHA, GUILHERME M.; CAPELO, PIERO L.; CIFERRI, CRISTINA D. A.. Healthcare Decision-Making Over a Geographic, Socioeconomic, and Image Data Warehouse. ADBIS, TPDL AND EDA 2020 COMMON WORKSHOPS AND DOCTORAL CONSORTIUM, v. 1260, p. 13-pg., 2020-01-01. (18/10607-3, 18/22277-8)

BRITO, JAQUELINE J.; MOSQUEIRO, THIAGO; CIFERRI, RICARDO R.; CIFERRI, CRISTINA D. A.. Random access with a distributed Bitmap Join Index for Star Joins. HELIYON, v. 6, n. 2, FEB 2020. (12/13158-9, 18/22277-8)

CARNIEL, ANDERSON CHAVES; AGUIAR, CRISTINA DUTRA. Spatial Index Structures for Modern Storage Devices: A Survey. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, v. 35, n. 9, p. 20-pg., 2023-09-01. (18/22277-8)

CARNIEL, ANDERSON CHAVES; ROUMELIS, GEORGE; CIFERRI, RICARDO R.; VASSILAKOPOULOS, MICHAEL; CORRAL, ANTONIO; AGUIAR, CRISTINA D.. Porting disk-based spatial index structures to flash-based solid state drives. GEOINFORMATICA, v. 26, n. 1, DEC 2021. (18/22277-8)

DE CARVALHO CASTRO, JOAO PEDRO; CHAVES CARNIEL, ANDERSON; DUTRA DE AGUIAR CIFERRI, CRISTINA. Analyzing spatial analytics systems based on Hadoop and Spark: A user perspective. SOFTWARE-PRACTICE & EXPERIENCE, v. 50, n. 12, p. 2121-2144, DEC 2020. (18/22277-8)

CARNIEL, ANDERSON C.; CIFERRI, RICARDO R.; CIFERRI, CRISTINA D. A.. A generic and efficient framework for flash-aware spatial indexing. INFORMATION SYSTEMS, v. 82, p. 102-120, MAY 2019. (15/26687-8, 18/22277-8)

MORAES, LEONARDO MAURO PEREIRA; JARDIM, PEDRO CALCIOLARI; AGUIAR, CRISTINA DUTRA. BigQA: A Software Reference Architecture for Big Data Question Answering Systems. ENTERPRISE INFORMATION SYSTEMS, ICEIS 2023, PT I, v. 518, p. 24-pg., 2024-01-01. (18/22277-8, 23/08293-9)

TRAINA, CAETANO, JR.; MORIYAMA, ANDRE; ROCHA, GUILHERME; CORDEIRO, ROBSON; CIFERRI, CRISTINA D. A.; TRAINA, AGMA; ASSOC COMP MACHINERY. The SIMILARQL framework: similarity queries in plain SQL. SAC '19: PROCEEDINGS OF THE 34TH ACM/SIGAPP SYMPOSIUM ON APPLIED COMPUTING, v. N/A, p. 4-pg., 2019-01-01. (18/05714-5, 16/17078-0, 18/22277-8)

ROCHA, GUILHERME MUZZI; CAPELO, PIERO LIMA; CARNIEL, ANDERSON CHAVES; AGUIAR, CRISTINA DUTRA; CHIUSANO, S; CERQUITELLI, T; WREMBEL, R; NORVAG, K; CATANIA, B; VARGAS-SOLAR, G; et al. Storing Feature Vectors in Relational Image Data Warehouses. NEW TRENDS IN DATABASE AND INFORMATION SYSTEMS, ADBIS 2022, v. 1652, p. 9-pg., 2022-01-01. (18/10607-3, 18/22277-8)

CASTRO, JOAO PEDRO C.; ROMERO, LUCAS M. F.; CARNIEL, ANDERSON CHAVES; AGUIAR, CRISTINA D.; CHIUSANO, S; CERQUITELLI, T; WREMBEL, R; NORVAG, K; CATANIA, B; VARGAS-SOLAR, G; et al. Open Science in the Cloud: The CloudFAIR Architecture for FAIR-compliant Repositories. NEW TRENDS IN DATABASE AND INFORMATION SYSTEMS, ADBIS 2022, v. 1652, p. 11-pg., 2022-01-01. (18/22277-8)

CARNIEL, ANDERSON C.; CIFERRI, RICARDO R.; CIFERRI, CRISTINA D. A.. FESTIval: A versatile framework for conducting experimental evaluations of spatial indices. METHODSX, v. 7, 2020. (18/22277-8, 15/26687-8)