An architecture for fast and general data processing on large clusters /
| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
[New York] : [San Rafael, California] :
Association for Computing Machinery ; Morgan & Claypool,
2016.
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| Edition: | First edition. |
| Series: | ACM books ;
#11. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Abstract: | The past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too. |
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| Physical Description: | 1 online resource PDF (xii, 128 pages) : illustrations. Also available in print. |
| Format: | Mode of access: World Wide Web. System requirements: Adobe Acrobat Reader. |
| Bibliography: | Includes bibliographical references (pages 119-128). |
| ISBN: | 9781970001570 |
| ISSN: | 2374-6777 ; |
| DOI: | 10.1145/2886107 |
| Access: | Abstract freely available; full-text restricted to subscribers or individual document purchasers. |