LeanBigData
Ultra-Scalable and Ultra-Efficient Integrated and Visual Big Data Analytics
| Coordinatore | UNIVERSIDAD POLITECNICA DE MADRID
Organization address
address: CALLE RAMIRO DE MAEZTU 7 EDIFICIO RECTORADO contact info |
| Nazionalità Coordinatore | Spain [ES] |
| Totale costo | 6˙148˙197 € |
| EC contributo | 3˙905˙000 € |
| Programma | FP7-ICT
Specific Programme "Cooperation": Information and communication technologies |
| Code Call | FP7-ICT-2013-11 |
| Funding Scheme | CP |
| Anno di inizio | 2014 |
| Periodo (anno-mese-giorno) | 2014-02-01 - 2017-01-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
UNIVERSIDAD POLITECNICA DE MADRID
Organization address
address: CALLE RAMIRO DE MAEZTU 7 EDIFICIO RECTORADO contact info |
ES (MADRID) | coordinator | 0.00 |
| 2 |
ATOS SPAIN SA
Organization address
address: Calle de Albarracin 25 contact info |
ES (Madrid) | participant | 0.00 |
| 3 |
CA TECHNOLOGIES DEVELOPMENT SPAIN SA
Organization address
address: PLAZA DE LA PAU SN WTC ALAMEDA PARK 2 contact info |
ES (CORNELLA DE LLOBREGAT BARCELONA) | participant | 0.00 |
| 4 |
FOUNDATION FOR RESEARCH AND TECHNOLOGY HELLAS
Organization address
address: N PLASTIRA STR 100 contact info |
EL (HERAKLION) | participant | 0.00 |
| 5 |
INESC PORTO - INSTITUTO DE ENGENHARIA DE SISTEMAS E COMPUTADORES DO PORTO
Organization address
address: Campus da FEUP, Rua Dr. Roberto Frias 378 contact info |
PT (PORTO) | participant | 0.00 |
| 6 |
INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS
Organization address
address: Patission Str. 42 contact info |
EL (ATHINA) | participant | 0.00 |
| 7 |
INTEL RESEARCH AND INNOVATION IRELAND LIMITED
Organization address
address: Collinstown Industrial Park contact info |
IE (LEIXLIP, CO KILDARE) | participant | 0.00 |
| 8 |
PT COMUNICACOES SA
Organization address
address: RUA ANDRADE CORVO 6 contact info |
PT (LISBOA) | participant | 0.00 |
| 9 |
SYNC LAB SRL
Organization address
address: VIA G PORZIO 4, CDN ISOLA B8 contact info |
IT (NAPOLI) | participant | 0.00 |
Mappa
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Obiettivo del progetto (Objective)
LeanBigData aims at addressing three open challenges in big data analytics: 1) The cost, in terms of resources, of scaling big data analytics for streaming and static data sources; 2) The lack of integration of existing big data management technologies and their high response time; 3) The insufficient end-user support leading to extremely lengthy big data analysis cycles. LeanBigData will address these challenges by:•Architecting and developing three resource-efficient Big Data management systems typically involved in Big Data processing: a novel transactional NoSQL key-value data store, a distributed complex event processing (CEP) system, and a distributed SQL query engine. We will achieve at least one order of magnitude in efficiency by removing overheads at all levels of the big-data analytics stack and we will take into account technology trends in multicore technologies and non-volatile memories. •Providing an integrated big data platform with these three main technologies used for big data, NoSQL, SQL, and Streaming/CEP that will improve response time for unified analytics over multiple sources and large amounts of data avoiding the inefficiencies and delays introduced by existing extract-transfer-load approaches. To achieve this we will use fine-grain intra-query and intra-operator parallelism that will lead to sub-second response times.•Supporting an end-to-end big data analytics solution removing the four main sources of delays in data analysis cycles by using: 1) automated discovery of anomalies and root cause analysis; 2) incremental visualization of long analytical queries; 3) drag-and-drop declarative composition of visualizations; and 4) efficient manipulation of visualizations through hand gestures over 3D/holographic views.Finally, LeanBigData will demonstrate these results in a cluster with 1,000 cores in four real industrial use cases with real data, paving the way for deployment in the context of realistic business processes.