Increasing the accessibility to Big Data systems via a common services API

Malcolm, Rohan; Morrison, Cherrelle; Grandison, Tyrone; Thorpe, Sean; Christie, Kimron; Wallace, Akim; Green, Damian; Jarrett, Julian; Campbell, Arnett

doi:10.1109/bigdata.2014.7004319

Cited by 6 publications

(4 citation statements)

References 2 publications

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“…The Architecture ( Figure.2) of this model implements Data achieve, Transaction system, Operational Data Store (ODS), Big Data Engine [14] and Data Analytics. They are interrelated and both are used to provide the efficient mining process to find the associations existing in Big Data.…”

Section: Proposed Systemmentioning

confidence: 99%

Performance evaluation of association mining in Hadoop single node cluster with Big Data

Asbern

Asha

2015

2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]

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Data Mining means extracting unique information from pre-existing large data sets. Data Mining techniques have been applied to almost all areas such as Education, health care, Stock market, etc. Since the data size is getting increased exponentially, maintaining high performance plays a major challenge in the field of data mining. The data may be in structured format or unstructured format and hence the research on extracting the frequent pattern which is repeated in an iterative fashion seems to be really difficult. The paper aims at evaluating the performance of a Hadoop single node cluster with respect to Big Data. Apriori based Association rule mining algorithm was used to find the frequent patterns and then their rules. Finally the time taken to perform the entire data mining task was found and the performance is evaluated.

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Section: Proposed Systemmentioning

confidence: 99%

Performance evaluation of association mining in Hadoop single node cluster with Big Data

Asbern

Asha

2015

2015 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015]

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“…Giannakis et al present a series of articles that describe how sensor signal processing algorithms may be adapted to operate over big and social data sets [38]. Malcom et al even developed a uniform programming interface so that non-experts can utilize state-of-the-art big data technologies [63] for social role analysis.…”

Section: Comparative Analysismentioning

confidence: 99%

On the discovery of social roles in large scale social systems

Doran

2015

Soc. Netw. Anal. Min.

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The social role of a participant in a social system is a label conceptualizing the circumstances under which she interacts within it. They may be used as a theoretical tool that explains why and how users participate in an online social system. Social role analysis also serves practical purposes, such as reducing the structure of complex systems to relationships among roles rather than alters, and enabling a comparison of social systems that emerge in similar contexts. This article presents a data-driven approach for the discovery of social roles in large scale social systems. Motivated by an analysis of the present art, the method discovers roles by the conditional triad censuses of user ego-networks, which is a promising tool because they capture the degree to which basic social forces push upon a user to interact with others. Clusters of censuses, inferred from samples of large scale network carefully chosen to preserve local structural properties, define the social roles. The promise of the method is demonstrated by discussing and discovering the roles that emerge in both Facebook and Wikipedia. The article concludes with a discussion of the challenges and future opportunities in the discovery of social roles in large social systems.

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“…The McKinsey Global Institute estimates that data volume is growing 40% per year, and will grow 44 times larger between 2009 and 2020 [1], similar statements can be applied to the other V-dimensions of the Big Data paradigm (Velocity and Variety). Many IT companies propose to their customers to manage Big Data challenges using a complex stack of technologies [2] including (i) data preparation utilities like Paxata 1 ; (ii) a data storage layer, such as Hadoop Distributed File System (HDFS) 2 ; (iii) a distributed computing framework such as Hadoop 3 or Spark 4 ; (iv) a data flow layer that applies map-reduce operations to the data partitions of the data storage layer; typically implemented with Big Data specific languages like HiveQL 5 , PigLatin 6 or Jaql 7 ; and (v) a data query layer implemented with scaling "Not only SQL" databases like Cassandra 8 or HBase 9 .…”

Section: Introductionmentioning

confidence: 99%

“…Despite the benefits of investing in Big Data systems are largely recognised, their adoption have been slow due to a variety of reasons [3]. One of the main reason is that organisations are strongly committed to their systems mainly due to the costs and implications of renewing a technological infrastructure from scratch, therefore their main concern is integrating legacy systems to new technologies, making the best of both worlds.…”

Section: Introductionmentioning

confidence: 99%

Facing big data variety in a model driven approach

Leida¹,

Ruiz²,

Ceravolo

2016

2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI)

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Despite the benefits of investing in Big Data systems are largely recognised, their adoption have been slower than expected. Actually, organisations and companies cannot migrate their systems to new a technological infrastructure without a safe integration to their legacy systems and data. For these reasons, it is required to evolve Big Data technologies with mature functions for supporting portability, interoperability and reusability. This paper illustrates a practical use case exploiting the Model-driven capabilities of the TOREADOR platform as a way to fast track the uptake of business-driven Big Data models.

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Increasing the accessibility to Big Data systems via a common services API

Cited by 6 publications

References 2 publications

Performance evaluation of association mining in Hadoop single node cluster with Big Data

Performance evaluation of association mining in Hadoop single node cluster with Big Data

On the discovery of social roles in large scale social systems

Facing big data variety in a model driven approach

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