Fábio Coelho

Bessa R, Coelho F, Rodrigues X, Alonso A, Soares T, Pires G, Matos P, Prates I, Shahrokni H, Mäkivierikko A.  2018.  GRID AND MARKET HUB: EMPOWERING LOCAL ENERGY COMMUNITIES IN INTEGRID.
Maia F, Paulo J, Coelho F, Neves F, Pereira JO, Oliveira R.  2017.  DDFlasks: Deduplicated Very Large Scale Data Store. Distributed Applications and Interoperable Systems - 17th IFIP WG 6.1 International Conference, DAIS 2017, Held as Part of the 12th International Federated Conference on Distributed Computing Techniques, DisCoTec 2017, Neuchâtel, Switzerland, June 1. :51–66. Abstract

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Coelho F, Matos M, Pereira JO, Oliveira R.  2017.  Similarity Aware Shuffling for the Distributed Execution of SQL Window Functions : BPA. Distributed Applications and Interoperable Systems - 17th IFIP WG 6.1 International Conference, DAIS 2017, Held as Part of the 12th International Federated Conference on Distributed Computing Techniques, DisCoTec 2017, Neuchâtel, Switzerland, June 1. :3–18. Abstract

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Coelho F, Paulo J, Vilaça R, Pereira JO, Oliveira R.  2017.  HTAPBench: Hybrid Transactional and Analytical Processing Benchmark. Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering. :293–304. Abstract
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HTAPBench

Gartner claims the ever increasing demand for real-time analytics requires the fusion of Transactional (OLTP) and Analytical (OLAP) databases, eschewing ETL processes and giving birth to the so-called Hybrid Analytical and Trans- actional Processing (HTAP) databases.

Coelho F, Pereira JO, Vilaça R, Oliveira R.  2016.  Reducing Data Transfer in Parallel Processing of SQL Window Functions. Proceedings of the 6th International Conference on Cloud Computing and Services Science. :343-347. Abstractdatadiversityconvergence_2016_1_copy.pdf

Window functions are a sub-class of analytical operators that allow data to be handled in a derived view of a given relation, while taking into account their neighboring tuples. We propose a technique that can be used in the parallel execution of this operator when data is naturally partitioned. The proposed method benefits the cases where the required partitioning is not the natural partitioning employed. Preliminary evaluation shows that we are able to limit data transfer among parallel workers to 14\% of the registered transfer when using a naive approach.

Coelho F, Pereira JO, Vilaça R, Oliveira R.  2016.  Holistic Shuffler for the Parallel Processing of SQL Window Functions. Distributed Applications and Interoperable Systems - 16th {IFIP} {WG} 6.1 International Conference, {DAIS} 2016, Held as Part of the 11th International Federated Conference on Distributed Computing Techniques, DisCoTec 2016, Heraklion, Crete, Greece, June. :75–81. Abstractholistic-proceedings.pdf

Window functions are a sub-class of analytical operators that allow data to be handled in a derived view of a given relation, while taking into account their neighboring tuples. Currently, systems bypass parallelization opportunities which become especially relevant when considering Big Data as data is naturally partitioned.
We present a shuffling technique to improve the parallel execution of window functions when data is naturally partitioned when the query holds a partitioning clause that does not match the natural partitioning of the relation. We evaluated this technique with a non-cumulative ranking function and we were able to reduce data transfer among parallel workers in 85% when compared to a naive approach.

Coelho F.  2013.  Implementation and test of transactional primitives over Cassandra. Abstractthesis.pdf

NoSQL databases opt not to o er important abstractions traditionally found in relational databases in order to achieve high levels of scalability and availability: transactional guarantees and strong data consistency. These limitations bring considerable complexity to the development of client applications and are therefore an obstacle to the broader adoption of the technology. In this work we propose a middleware layer over NoSQL databases that o ers transactional guarantees with Snapshot Isolation. The proposed solution is achieved in a non-intrusive manner, providing to the clients the same interface as a NoSQL database, simply adding the transactional context. The transactional context is the focus of our contribution and is modularly based on a Non Persistent Version Store that holds several versions of elements and interacts with an external transaction certi er. In this work, we present an implementation of our system over Apache Cassandra and by using two representative benchmarks, YCSB and TPC-C, we measure the cost of adding transactional support with ACID guarantees.

Coelho F, Cruz F, Vilaça R, Pereira JO, Oliveira R.  2014.  pH1: A Transactional Middleware for NoSQL. 33rd IEEE International Symposium on Reliable Distributed Systems - SRDS. Abstractph1.pdf

NoSQL databases opt not to offer important abstractions traditionally found in relational databases in order to achieve high levels of scalability and availability: transactional guarantees and strong data consistency.
In this work we propose pH1, a generic middleware layer over NoSQL databases that offers transactional guarantees with Snapshot Isolation. This is achieved in a non-intrusive manner,
requiring no modifications to servers and no native support for multiple versions. Instead, the transactional context is achieved by means of a multiversion distributed cache and an external
transaction certifier, exposed by extending the client’s interface with transaction bracketing primitives.
We validate and evaluate pH1 with Apache Cassandra and Hyperdex. First, using the YCSB benchmark, we show that the cost of providing ACID guarantees to these NoSQL databases
amounts to 11% decrease in throughput.
Moreover, using the transaction intensive TPC-C workload, pH1 presented an impact of 22% decrease in throughput. This contrasts with OMID, a previous proposal that takes advantage of
HBase’s support for multiple versions, with a throughput penalty of 76% in the same conditions.

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Biography

Currently I am PostDoc Researcher at HASLab, a sub-unit of INESC TEC.

pH1: Middleware transacional para NoSQL, at HASLab, 1/27/2014
As bases de dados NoSQL optam por não oferecer importantes abstracções tipicamente encontradas em sistemas relacionais, por forma a atingir elevada escalabilidade e disponibilidade: garantias transacionais e critérios de coerência de dados fortes.
Apresentamos o pH1, um middleware transacional com Snapshot Isolation como nível de isolamento, que se posiciona sobre uma base de dados NoSQL, mitigando o acréscimo de dificuldade que se verifica no desenvolvimento de aplicações sobre bases de dados NoSQL.
Position: 
Assistant Researcher