Abstract-This article presents the ALOJA project, an initiative to produce mechanisms for an automated characterization of cost-effectiveness of Hadoop deployments and reports its initial results. ALOJA is the latest phase of a long-term collaborative engagement between BSC and Microsoft which, over the past 6 years has explored a range of different aspects of computing systems, software technologies and performance profiling. While during the last 5 years, Hadoop has become the de-facto platform for Big Data deployments, still little is understood of how the different layers of the software and hardware deployment options affects its performance. Early ALOJA results show that Hadoop's runtime performance, and therefore its price, are critically affected by relatively simple software and hardware configuration choices e.g., number of mappers, compression, or volume configuration. Project ALOJA presents a vendor-neutral repository featuring over 5000 Hadoop runs, a test bed, and tools to evaluate the cost-effectiveness of different hardware, parameter tuning, and Cloud services for Hadoop. As few organizations have the time or performance profiling expertise, we expect our growing repository will benefit Hadoop customers to meet their Big Data application needs. ALOJA seeks to provide both knowledge and an online service to with which users make better informed configuration choices for their Hadoop compute infrastructure whether this be on-premise or cloud-based.The initial version of ALOJA's Web application and sources are available at http://hadoop.bsc.es

BackgroundCerebral palsy (CP) is one of the causes of physical disability in children. Sitting abilities can be described using the Level of Sitting Scale (LSS) and the Gross Motor Function Classification System (GMFCS). There is growing interest in the sitting posture of children with CP owing to a stable sitting position allows for the development of eye-hand coordination, functions of the upper extremities and functional skills. Besides, in recent years researchers have tried to develop a new terminology to classify the CP as performed by the Surveillance of Cerebral Palsy in Europe (SCPE), in order to improve the monitoring of the frequency of the PC, providing a framework for research and service planning. The aim of this study was to analyse the relationship between GMFCS and LSS. The second purpose was to describe how the SCPE relates to sitting abilities with the GMFCS and LSS.MethodsThe study involved 139 children with CP (range 3–18 years) from 24 educational centres. Age, gender, CP classification according to SCPE, GMFCS and LSS levels were recorded by an experienced physiotherapist.ResultsA significant inverse relationship between GMFCS and LSS score levels was found (rs = −0.86, p = 0.00). 45.3 % of the children capable of leaning in any direction and of re-erecting the trunk (level VIII on the LSS) could walk without limitation (level I on the GMFCS). There were differences in the distribution of the GMFCS (χ2(4):50.78) and LSS (χ2(7): 37.15) levels and CP according to the distribution of the spasticity (p <0.01).ConclusionsThere was a negative correlation between both scales and a relation between sitting ability and the capacity to walk with or without technical devices. GMFCS and the LSS are useful tools for describing the functional abilities and limitations of children with CP, specially sitting and mobility. Classification based on the distribution of spasticity and the gross motor function provides clinical information on the prognosis and development of children with CP.

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