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020 ▼a 9780438324428
035 ▼a (MiAaPQ)AAI10814346
035 ▼a (MiAaPQ)berkeley:17784
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 004
1001 ▼a Xin, Reynold Shi.
24510 ▼a Go with the Flow: Graphs, Streaming and Relational Computations over Distributed Dataflow.
260 ▼a [S.l.] : ▼b University of California, Berkeley., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 126 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Advisers: Michael Franklin
5021 ▼a Thesis (Ph.D.)--University of California, Berkeley, 2018.
520 ▼a Modern data analysis is undergoing a "Big Data" transformation: organizations are generating and gathering more data than ever before, in a variety of formats covering both structured and unstructured data, and employing increasingly sophisticat
520 ▼a This dissertation builds on Apache Spark, a distributed dataflow engine, and creates three related systems: Spark SQL, Structured Streaming, and GraphX. Spark SQL combines relational and procedural processing through a new API called DataFrame.
520 ▼a The three systems have enjoyed wide adoption in industry and academia, and together they laid the foundation for Spark's 2.0 release. They demonstrate the feasibility and advantages of unifying disparate, specialized data systems on top of distr
590 ▼a School code: 0028.
650 4 ▼a Computer science.
690 ▼a 0984
71020 ▼a University of California, Berkeley. ▼b Electrical Engineering & Computer Sciences.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0028
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998116 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자