Performing MapReduce on Data Centers with Hierarchical Structures
نویسندگان
چکیده
منابع مشابه
Software Design and Implementation for MapReduce across Distributed Data Centers
Recently, the computational requirements for large-scale data-intensive analysis of scientific data have grown significantly. In High Energy Physics (HEP) for example, the Large Hadron Collider (LHC) produced 13 petabytes of data in 2010. This huge amount of data are processed on more than 140 computing centers distributed across 34 countries. The MapReduce paradigm has emerged as a highly succ...
متن کاملHierarchical Spatial Data Structures
An overview is presented of the use of hierarchical spatial data structures such as the quadtree. They are based on the principle of recursive decomposition. The focus is on the representation of data used in image databases. The emphasis is on twodimensional regions, points, rectangles, and lines.
متن کاملA MapReduce-supported network structure for data centers
Several novel data center network structures have been proposed to improve the topological properties of data centers. A common characteristic of these structures is that they are designed for supporting general applications and services. Consequently, these structures do not match well with the specific requirements of some dedicated applications. In this paper, we propose a hyper-fat-tree net...
متن کاملDatabase Outsourcing with Hierarchical Authenticated Data Structures
In an outsourced database scheme, the data owner delegates the data management tasks to a remote service provider. At a later time, the remote service is supposed to answer any query on the database. The essential requirements are ensuring the data integrity and authenticity with efficient mechanisms. Current approaches employ authenticated data structures to store security information, generat...
متن کاملExperiences on Processing Spatial Data with MapReduce
The amount of information in spatial databases is growing as more data is made available. Spatial databases mainly store two types of data: raster data (satellite/aerial digital images), and vector data (points, lines, polygons). The complexity and nature of spatial databases makes them ideal for applying parallel processing. MapReduce is an emerging massively parallel computing model, proposed...
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: International Journal of Computers Communications & Control
سال: 2014
ISSN: 1841-9844,1841-9836
DOI: 10.15837/ijccc.2012.3.1385