Distributed scaling out solutions for data management
نویسندگان
چکیده
منابع مشابه
Scaling out Column Stores: Data, Queries, and Transactions Scaling out Column Stores: Data, Queries, and Transactions
The amount of data available today is huge and keeps increasing steadily. Databases help to cope with huge amounts of data. Yet, traditional databases are not fast enough to answer the complex analytical queries that decision makers in big enterprises ask over large datasets. This is where column stores have their field of application. Tailored to this type of on-line analytical processing (OLA...
متن کاملEntropy-based Consensus for Distributed Data Clustering
The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...
متن کاملScaling out data preprocessing with Hive
We introduce a user-friendly graphical data preprocessing application based on Hive, one of the well known opensource distributed warehouse systems. It is comfortable, and easy to use for preprocessing purposes, but to prove usability of this application, we created measurement a framework to ensure precise results. These results show that our application has outstanding scaling capability in t...
متن کاملScaling Out Federated Queries for Life Sciences Data in Production
There exists an abundance of Linked Data storage solutions, but only few meet the requirements of a production environment with interlinked life sciences data. In such environments, a triple store has to support complex SPARQL queries and handle large datasets with hundreds of millions of triples. The Ontoforce platform DISQOVER offers federated search for life sciences, relying on complex fede...
متن کاملDistributed Data Mining: Scaling up and beyond
In this chapter I begin by discussing Distributed Data Mining (DDM) for scaling up, beginning by asking what scaling up means, questioning whether it is necessary, and then presenting a brief survey of what has been done to date. I then provide motivation beyond scaling up, arguing that DDM is a more natural way to view data mining generally. DDM eliminates many difficulties encountered when co...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the Institute for System Programming of RAS
سال: 2013
ISSN: 2079-8156,2220-6426
DOI: 10.15514/ispras-2013-24-15