A gray-box modeling methodology for runtime prediction of Apache Spark jobs

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Distributed and Parallel Databases Pub Date : 2020-03-10 DOI:10.1007/s10619-020-07286-y
Hani Al-Sayeh, Stefan Hagedorn, K. Sattler
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引用次数: 12
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用于Apache Spark作业运行时预测的灰盒建模方法
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来源期刊
Distributed and Parallel Databases
Distributed and Parallel Databases 工程技术-计算机:理论方法
CiteScore
3.50
自引率
0.00%
发文量
17
审稿时长
>12 weeks
期刊介绍: Distributed and Parallel Databases publishes papers in all the traditional as well as most emerging areas of database research, including: Availability and reliability; Benchmarking and performance evaluation, and tuning; Big Data Storage and Processing; Cloud Computing and Database-as-a-Service; Crowdsourcing; Data curation, annotation and provenance; Data integration, metadata Management, and interoperability; Data models, semantics, query languages; Data mining and knowledge discovery; Data privacy, security, trust; Data provenance, workflows, Scientific Data Management; Data visualization and interactive data exploration; Data warehousing, OLAP, Analytics; Graph data management, RDF, social networks; Information Extraction and Data Cleaning; Middleware and Workflow Management; Modern Hardware and In-Memory Database Systems; Query Processing and Optimization; Semantic Web and open data; Social Networks; Storage, indexing, and physical database design; Streams, sensor networks, and complex event processing; Strings, Texts, and Keyword Search; Spatial, temporal, and spatio-temporal databases; Transaction processing; Uncertain, probabilistic, and approximate databases.
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