Time Allowed Rubric 2 hours ANSWER ALL FOUR QUESTIONS. Calculators Notes Calculators are not permitted Books, notes or other written material may not be brought into this examination 7CCSMBDT BIG DATA TECHNOLOGIES King¡¯s College London This paper is part of an examination of the College counting towards the award of a degree. Examinations are governed […]
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7CCSMBDT – Big Data Technologies Week 7 Grigorios Loukides, PhD (grigorios.loukides@kcl.ac.uk) Spring 2017/2018 1 Objectives Hive Chapter 9.2 Bagha Thusoo et al. Hive – a petabyte scale data warehouse using Hadoop. ICDE ‘10. https://doi.org/10.1109/ICDE.2010.5447738 http://blog.cloudera.com/wp-content/uploads/2010/01/6-IntroToHive.pdf SparkSQL Chapter 9.1 Bagha M. Armbrust et al. Spark SQL: Relational Data Processing
7CCSMBDT – Big Data Technologies Week 11 Grigorios Loukides, PhD (grigorios.loukides@kcl.ac.uk) 1 Objectives Introduce the format of the exam Go through the main concepts quickly Answer questions 2 Exam The exam will have a weight 80% (the rest 20% from the two courseworks) Format We are waiting for formal
7CCSMBDT – Big Data Technologies Week 2 Grigorios Loukides, PhD (grigorios.loukides@kcl.ac.uk) Sections 1.5, 1.6 , 5.3.1, 5.3.2 from Bagha’s book https://flume.apache.org/FlumeUserGuide.html Spring 2017/2018 1 Analytics flow for big data TODAY’s FOCUS Data The data is collected and ingested into a big data stack collection Data Preparation Issues required for meaningful processing are resolved Analysis types
Graduate Diploma in Systems Analysis Page 1 of 6 SAMPLE PAPER Institute of Systems Science National University of Singapore GRADUATE DIPLOMA IN SYSTEMS ANALYSIS SA Term 2 Examination Sample Paper 4 (Module Code – 4105): Web Application Development Instructions for Paper Date: Time: Duration: Place: N.A 9.00am 3 hours (9.30 a.m. to 12.30 p.m.) excluding
and Review RDBMS review Memory hierarchy John Edgar 2 1.1 A table consists of rows and columns ▪ Rows represent records ▪ Records must be unique ▪ One or more attributes forms a primary key ▪ Records are also referred to as tuples ▪ Each column represents an attribute ▪ Columns must
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有哪些常见的统计软件 它们的特点是什么 有哪些统计软件 出处: https://en.wikipedia.org/wiki /Comparison_of_statistical_pa ckages 非统计软件:Excel+VBA • Excel不需要多介绍了吧? • 绝大多数同学毕业后最常用的软件 • 市场占有率最大的桌面级数据制表/分 析软件 • 绝大多数统计软件都提供了Excel数据 接口 • 复旦师生可以免费下载使用 • Why VBA? • 数据操作比较复杂 • 重复性的数据操作 • 数据的量变大 • 不是专门的统计分析软件 • 专业的事情留给专业的软件去做 统计软件:SAS • http://www.sas.com • 企业级产品，体积庞大，价格贵， 成熟方法几乎无所不包 • 语言比较陈旧，少量菜单操作， 但功能强，计算效率高 • 最近这些年针对新方法新应用提 供了很多更新的产品 • 业界标准，少数几家FDA认可的分 析软件 • 要充分利用其功能，一定要学会 宏语言。 统计软件:SPSS • https://www.ibm.com/analyti cs/spss-statistics-software
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School of Information Technology & Computer Science Session: Autumn 2020 University of Wollongong Scope Lecturer: Janusz R. Getta CSCI317 Database Performance Tuning Assignment 4 Published on 25 May 2020 This assignment includes the tasks in improving performance of database applications through transformations of SQL statements, replacing SQL statements with more efficient SQL statements, transformation of
School of Science COSC1295 Advanced Programming, S1, 2020 Assignment Part 2: UniLink system – Java FX UI Implementation and Data Persistence Assessment Type: Individual assignment; no group work. Submit online via Canvas → Assignments → Assignment 2. Marks are awarded for meeting requirements as closely as possible according to assignment specifications and the supplied rubric.
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41025 ISD Assignment 2 Autumn 2020 Due Date: UNIVERSITY OF TECHNOLOGY, SYDNEY 41025 Introduction to Software Development Project – Implementation & Testing Assignment 2 Softcopy Due by Friday 05/06/2020 11:55 PM AEST Showcases in Week Commencing from 08/06/2020 – During Related Workshop: See workshop schedule on UTS Online for exact dates/ time slots) Submission: Each
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