STEP : A Distributed Multi-threading Framework Towards Efficient Data Analytics Article Swipe
YOU?
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· 2018
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.1812.04971
Various general-purpose distributed systems have been proposed to cope with high-diversity applications in the pipeline of Big Data analytics. Most of them provide simple yet effective primitives to simplify distributed programming. While the rigid primitives offer great ease of use to savvy programmers, they probably compromise efficiency in performance and flexibility in data representation and programming specifications, which are critical properties in real systems. In this paper, we discuss the limitations of coarse-grained primitives and aim to provide an alternative for users to have flexible control over distributed programs and operate globally shared data more efficiently. We develop STEP, a novel distributed framework based on in-memory key-value store. The key idea of STEP is to adapt multi-threading in a single machine to a distributed environment. STEP enables users to take fine-grained control over distributed threads and apply task-specific optimizations in a flexible manner. The underlying key-value store serves as distributed shared memory to keep globally shared data. To ensure ease-of-use, STEP offers plentiful effective interfaces in terms of distributed shared data manipulation, cluster management, distributed thread management and synchronization. We conduct extensive experimental studies to evaluate the performance of STEP using real data sets. The results show that STEP outperforms the state-of-the-art general-purpose distributed systems as well as a specialized ML platform in many real applications.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1812.04971
- https://arxiv.org/pdf/1812.04971
- OA Status
- green
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2905481056
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2905481056Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1812.04971Digital Object Identifier
- Title
-
STEP : A Distributed Multi-threading Framework Towards Efficient Data AnalyticsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-12-12Full publication date if available
- Authors
-
Yijie Mei, Yanyan Shen, Yanmin Zhu, Linpeng HuangList of authors in order
- Landing page
-
https://arxiv.org/abs/1812.04971Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1812.04971Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1812.04971Direct OA link when available
- Concepts
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Computer science, Distributed computing, Thread (computing), Distributed memory, Data structure, Distributed shared memory, Data management, Key (lock), Synchronization (alternating current), Scalability, Shared memory, Parallel computing, Memory management, Operating system, Database, Uniform memory access, Computer network, Overlay, Channel (broadcasting)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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30Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.with | 9 |
| abstract_inverted_index.STEP, | 98 |
| abstract_inverted_index.While | 31 |
| abstract_inverted_index.adapt | 115 |
| abstract_inverted_index.apply | 136 |
| abstract_inverted_index.based | 103 |
| abstract_inverted_index.data. | 156 |
| abstract_inverted_index.great | 36 |
| abstract_inverted_index.novel | 100 |
| abstract_inverted_index.offer | 35 |
| abstract_inverted_index.rigid | 33 |
| abstract_inverted_index.savvy | 41 |
| abstract_inverted_index.sets. | 193 |
| abstract_inverted_index.store | 146 |
| abstract_inverted_index.terms | 166 |
| abstract_inverted_index.users | 81, 127 |
| abstract_inverted_index.using | 190 |
| abstract_inverted_index.which | 57 |
| abstract_inverted_index.ensure | 158 |
| abstract_inverted_index.memory | 151 |
| abstract_inverted_index.offers | 161 |
| abstract_inverted_index.paper, | 66 |
| abstract_inverted_index.serves | 147 |
| abstract_inverted_index.shared | 92, 150, 155, 169 |
| abstract_inverted_index.simple | 23 |
| abstract_inverted_index.single | 119 |
| abstract_inverted_index.store. | 107 |
| abstract_inverted_index.thread | 175 |
| abstract_inverted_index.Various | 0 |
| abstract_inverted_index.cluster | 172 |
| abstract_inverted_index.conduct | 180 |
| abstract_inverted_index.control | 85, 131 |
| abstract_inverted_index.develop | 97 |
| abstract_inverted_index.discuss | 68 |
| abstract_inverted_index.enables | 126 |
| abstract_inverted_index.machine | 120 |
| abstract_inverted_index.manner. | 142 |
| abstract_inverted_index.operate | 90 |
| abstract_inverted_index.provide | 22, 77 |
| abstract_inverted_index.results | 195 |
| abstract_inverted_index.studies | 183 |
| abstract_inverted_index.systems | 3, 204 |
| abstract_inverted_index.threads | 134 |
| abstract_inverted_index.critical | 59 |
| abstract_inverted_index.evaluate | 185 |
| abstract_inverted_index.flexible | 84, 141 |
| abstract_inverted_index.globally | 91, 154 |
| abstract_inverted_index.pipeline | 14 |
| abstract_inverted_index.platform | 211 |
| abstract_inverted_index.probably | 44 |
| abstract_inverted_index.programs | 88 |
| abstract_inverted_index.proposed | 6 |
| abstract_inverted_index.simplify | 28 |
| abstract_inverted_index.systems. | 63 |
| abstract_inverted_index.effective | 25, 163 |
| abstract_inverted_index.extensive | 181 |
| abstract_inverted_index.framework | 102 |
| abstract_inverted_index.in-memory | 105 |
| abstract_inverted_index.key-value | 106, 145 |
| abstract_inverted_index.plentiful | 162 |
| abstract_inverted_index.analytics. | 18 |
| abstract_inverted_index.compromise | 45 |
| abstract_inverted_index.efficiency | 46 |
| abstract_inverted_index.interfaces | 164 |
| abstract_inverted_index.management | 176 |
| abstract_inverted_index.primitives | 26, 34, 73 |
| abstract_inverted_index.properties | 60 |
| abstract_inverted_index.underlying | 144 |
| abstract_inverted_index.alternative | 79 |
| abstract_inverted_index.distributed | 2, 29, 87, 101, 123, 133, 149, 168, 174, 203 |
| abstract_inverted_index.flexibility | 50 |
| abstract_inverted_index.limitations | 70 |
| abstract_inverted_index.management, | 173 |
| abstract_inverted_index.outperforms | 199 |
| abstract_inverted_index.performance | 48, 187 |
| abstract_inverted_index.programming | 55 |
| abstract_inverted_index.specialized | 209 |
| abstract_inverted_index.applications | 11 |
| abstract_inverted_index.ease-of-use, | 159 |
| abstract_inverted_index.efficiently. | 95 |
| abstract_inverted_index.environment. | 124 |
| abstract_inverted_index.experimental | 182 |
| abstract_inverted_index.fine-grained | 130 |
| abstract_inverted_index.programmers, | 42 |
| abstract_inverted_index.programming. | 30 |
| abstract_inverted_index.applications. | 215 |
| abstract_inverted_index.manipulation, | 171 |
| abstract_inverted_index.optimizations | 138 |
| abstract_inverted_index.task-specific | 137 |
| abstract_inverted_index.coarse-grained | 72 |
| abstract_inverted_index.high-diversity | 10 |
| abstract_inverted_index.representation | 53 |
| abstract_inverted_index.general-purpose | 1, 202 |
| abstract_inverted_index.multi-threading | 116 |
| abstract_inverted_index.specifications, | 56 |
| abstract_inverted_index.state-of-the-art | 201 |
| abstract_inverted_index.synchronization. | 178 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile |