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One of the main reasons why cloud computing has gained so much popularity is due to its ease of use and its ability to scale computing resources on demand. As a result, users can now rent computing nodes on large commercial clusters through several vendors, such as Amazon and rackspace. However, despite the attention paid by Cloud providers, performance(More)
MapReduce is a computing paradigm that has gained a lot of attention in recent years from industry and research. Unlike parallel DBMSs, MapReduce allows non-expert users to run complex analytical tasks over very large data sets on very large clusters and clouds. However, this comes at a price: MapReduce processes tasks in a scan-oriented fashion. Hence, the(More)
With the exponential growth of moving objects data to the Gigabyte range, it has become critical to develop effective techniques for indexing, updating , and querying these massive data sets. To meet the high update rate as well as low query response time requirements of moving object applications, this paper takes a novel approach in moving object(More)
Yellow elephants are slow. A major reason is that they consume their inputs entirely before responding to an elephant rider's orders. Some clever riders have trained their yellow elephants to only consume parts of the inputs before responding. However, the teaching time to make an elephant do that is high. So high that the teaching lessons often do not pay(More)
Personal Information Management Systems require a powerful and versatile data model that is able to represent a highly heterogeneous mix of data such as relational data, XML, file content, folder hierarchies, emails and email attachments, data streams, RSS feeds and dynamically computed documents, e.g. ActiveXML [3]. Interestingly, until now no approach was(More)
Dataspace management has been recently identified as a new agenda for information management [17, 22] and information integration [23]. In sharp contrast to standard information integration ar-chitectures, a dataspace management system is a data-coexistence approach: it does not require any investments in semantic integration before querying services on the(More)
MapReduce is becoming ubiquitous in large-scale data analysis. Several recent works have shown that the performance of Hadoop MapReduce could be improved, for instance, by creating indexes in a non-invasive manner. However, they ignore the impact of the data layout used inside data blocks of Hadoop Distributed File System (HDFS). In this paper, we analyze(More)
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (<i>x, y</i>) that are within a distance <i>&#949;</i>.One of the most efficient algorithms for processing similarity-joins is the Multidimensional-Spatial Join (MSJ) by Koudas and Sevcik. In our previous(More)