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2013 IEEE 29th International Conference on Data Engineering (ICDE)

8-12 April 2013

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Displaying Results 1 - 25 of 158
  • [USB label]

    Publication Year: 2013, Page(s): 1
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  • ICDE 2013 Conference [cover]

    Publication Year: 2013, Page(s): 1
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  • Hub page

    Publication Year: 2013, Page(s): 1
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  • Session list

    Publication Year: 2013, Page(s): 1
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  • Table of contents

    Publication Year: 2013, Page(s):1 - 16
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  • Author index

    Publication Year: 2013, Page(s):1 - 12
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  • Detailed author index

    Publication Year: 2013, Page(s):1 - 63
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  • The end of indexes

    Publication Year: 2013, Page(s): 1
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  • ICDE 2012 [Abstracts book]

    Publication Year: 2013, Page(s):1 - 128
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2117 KB)

    Presents abstracts for the articles comprising the conference proceedings. View full abstract»

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  • [PDF Reader FAQ and support]

    Publication Year: 2013, Page(s): 1
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  • Frequently asked questions

    Publication Year: 2013, Page(s):1 - 6
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  • Message from the ICDE 2013 program committee and general chairs

    Publication Year: 2013, Page(s):i - ii
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  • Panel: Big data for the public

    Publication Year: 2013, Page(s): iii
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (73 KB)

    Summary form only given. While data are now being produced and collected on unprecedented scales, most of the "big data" remain inaccessible or difficult to use by the public. View full abstract»

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  • Proceedings [editors]

    Publication Year: 2013, Page(s): 1
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  • Committees

    Publication Year: 2013, Page(s):iv - xi
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  • Patrons and supporters

    Publication Year: 2013, Page(s): xii
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  • Hardware killed the software star

    Publication Year: 2013, Page(s):1 - 4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (76 KB) | HTML iconHTML

    Until relatively recently, the development of data processing applications took place largely ignoring the underlying hardware. Only in niche applications (supercomputing, embedded systems) or in special software (operating systems, database internals, language runtimes) did (some) programmers had to pay attention to the actual hardware where the software would run. In most cases, working atop the... View full abstract»

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  • Recent progress towards an ecosystem of structured data on the Web

    Publication Year: 2013, Page(s):5 - 8
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (511 KB) | HTML iconHTML

    Google Fusion Tables aims to support an ecosystem of structured data on the Web by providing a tool for managing and visualizing data on the one hand, and for searching and exploring for data on the other. This paper describes a few recent developments in our efforts to further the ecosystem. View full abstract»

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  • Re-thinking the performance of information processing systems

    Publication Year: 2013, Page(s):9 - 13
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (191 KB) | HTML iconHTML

    Recent advances in hardware and software technologies have enabled us to re-think how we architect databases to meet the demands of today's information systems. However, this makes existing performance evaluation metrics obsolete. In this paper, I describe SAP HANA a novel, powerful database platform that leverages the availability of large main memory and massively parallel processors. Based on t... View full abstract»

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  • CPU and cache efficient management of memory-resident databases

    Publication Year: 2013, Page(s):14 - 25
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (947 KB) | HTML iconHTML

    Memory-Resident Database Management Systems (MRDBMS) have to be optimized for two resources: CPU cycles and memory bandwidth. To optimize for bandwidth in mixed OLTP/OLAP scenarios, the hybrid or Partially Decomposed Storage Model (PDSM) has been proposed. However, in current implementations, bandwidth savings achieved by partial decomposition come at increased CPU costs. To achieve the aspired ba... View full abstract»

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  • Identifying hot and cold data in main-memory databases

    Publication Year: 2013, Page(s):26 - 37
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (507 KB) | HTML iconHTML

    Main memories are becoming sufficiently large that most OLTP databases can be stored entirely in main memory, but this may not be the best solution. OLTP workloads typically exhibit skewed access patterns where some records are hot (frequently accessed) but many records are cold (infrequently or never accessed). It is more economical to store the coldest records on secondary storage such as flash.... View full abstract»

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  • The adaptive radix tree: ARTful indexing for main-memory databases

    Publication Year: 2013, Page(s):38 - 49
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (289 KB) | HTML iconHTML

    Main memory capacities have grown up to a point where most databases fit into RAM. For main-memory database systems, index structure performance is a critical bottleneck. Traditional in-memory data structures like balanced binary search trees are not efficient on modern hardware, because they do not optimally utilize on-CPU caches. Hash tables, also often used for main-memory indexes, are fast but... View full abstract»

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  • Finding connected components in map-reduce in logarithmic rounds

    Publication Year: 2013, Page(s):50 - 61
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1290 KB) | HTML iconHTML

    Given a large graph G = (V, E) with millions of nodes and edges, how do we compute its connected components efficiently? Recent work addresses this problem in map-reduce, where a fundamental trade-off exists between the number of map-reduce rounds and the communication of each round. Denoting d the diameter of the graph, and n the number of nodes in the largest component, all prior techniques for ... View full abstract»

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  • Enumerating subgraph instances using map-reduce

    Publication Year: 2013, Page(s):62 - 73
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (438 KB) | HTML iconHTML

    The theme of this paper is how to find all instances of a given “sample” graph in a larger “data graph,” using a single round of map-reduce. For the simplest sample graph, the triangle, we improve upon the best known such algorithm. We then examine the general case, considering both the communication cost between mappers and reducers and the total computation cost at th... View full abstract»

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  • Scalable maximum clique computation using MapReduce

    Publication Year: 2013, Page(s):74 - 85
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (295 KB) | HTML iconHTML

    We present a scalable and fault-tolerant solution for the maximum clique problem based on the MapReduce framework. The key contribution that enables us to effectively use MapReduce is a recursive partitioning method that partitions the graph into several subgraphs of similar size. After partitioning, the maximum cliques of the different partitions can be computed independently, and the computation... View full abstract»

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