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About

Francisco Cruz was born in Portugal (1986), has a B.Sc. (2007), an M.Sc. (2009), and PhD (2016) by the University of Minho and is currently postdoctoral researcher at INESC TEC.

During his M.Sc. he started working at HASLab/ INESC TEC, at the University of Minho, on the HPLabs Innovation Research Award funded project DC2MS - Dependable Cloud Computing Management Services (DC2MS - IRA/CW118736). During this time, his research focused on Cloud Computing environments, more specifically on the new NoSQL data stores. At the same time, he worked on his master thesis, entitled SocialSeer, revolved around metadata sharing and suggestion of data in dropbox like systems.

In his Ph.D work his research shifted towards providing a SQL interface to NoSQL data stores as well as how to improve their elasticity and performance.

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Details

Details

  • Name

    Francisco Miguel Cruz
  • Cluster

    Computer Science
  • Role

    Researcher
  • Since

    01st January 2012
002
Publications

2016

Resource Usage Prediction in Distributed Key-Value Datastores

Authors
Cruz, F; Maia, F; Matos, M; Oliveira, R; Paulo, J; Pereira, J; Vilaca, R;

Publication
DISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS, DAIS 2016

Abstract
In order to attain the promises of the Cloud Computing paradigm, systems need to be able to transparently adapt to environment changes. Such behavior benefits from the ability to predict those changes in order to handle them seamlessly. In this paper, we present a mechanism to accurately predict the resource usage of distributed key-value datastores. Our mechanism requires offline training but, in contrast with other approaches, it is sufficient to run it only once per hardware configuration and subsequently use it for online prediction of database performance under any circumstance. The mechanism accurately estimates the database resource usage for any request distribution with an average accuracy of 94 %, only by knowing two parameters: (i) cache hit ratio; and (ii) incoming throughput. Both input values can be observed in real time or synthesized for request allocation decisions. This novel approach is sufficiently simple and generic, while simultaneously being suitable for other practical applications.

2014

PH1: A transactional middleware for NoSQL

Authors
Coelho, F; Cruz, F; Vilaca, R; Pereira, J; Oliveira, R;

Publication
Proceedings of the IEEE Symposium on Reliable Distributed Systems

Abstract
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 © 2014 IEEE.

2013

MeT

Authors
Cruz, F; Maia, F; Matos, M; Oliveira, R; Paulo, J; Pereira, J; Vilaça, R;

Publication
Proceedings of the 8th ACM European Conference on Computer Systems - EuroSys '13

Abstract

2013

MeT: Workload aware elasticity for NoSQL

Authors
Cruz, F; Maia, F; Matos, M; Oliveira, R; Paulo, J; Pereira, J; Vilaca, R;

Publication
Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys 2013

Abstract
NoSQL databases manage the bulk of data produced by modern Web applications such as social networks. This stems from their ability to partition and spread data to all available nodes, allowing NoSQL systems to scale. Unfortunately, current solutions' scale out is oblivious to the underlying data access patterns, resulting in both highly skewed load across nodes and suboptimal node configurations. In this paper, we first show that judicious placement of HBase partitions taking into account data access patterns can improve overall throughput by 35%. Next, we go beyond current state of the art elastic systems limited to uninformed replica addition and removal by: i) reconfiguring existing replicas according to access patterns and ii) adding replicas specifically configured to the expected access pattern. MeT is a prototype for a Cloud-enabled framework that can be used alone or in conjunction with OpenStack for the automatic and heterogeneous reconfiguration of a HBase deployment. Our evaluation, conducted using the YCSB workload generator and a TPC-C workload, shows that MeT is able to i) autonomously achieve the performance of a manual configured cluster and ii) quickly reconfigure the cluster according to unpredicted workload changes. © 2013 ACM.