大数据分析:Hive、Spark SQL、DataFrames和GraphFrames

Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames

893 次查看
Yandex
Coursera
  • 完成时间大约为 68 个小时
  • 高级
  • 英语, 韩语
注:本课程由Coursera和Linkshare共同提供,因开课平台的各种因素变化,以上开课日期仅供参考

课程概况

No doubt working with huge data volumes is hard, but to move a mountain, you have to deal with a lot of small stones. But why strain yourself? Using Mapreduce and Spark you tackle the issue partially, thus leaving some space for high-level tools. Stop struggling to make your big data workflow productive and efficient, make use of the tools we are offering you.

This course will teach you how to:
– Warehouse your data efficiently using Hive, Spark SQL and Spark DataFframes.
– Work with large graphs, such as social graphs or networks.
– Optimize your Spark applications for maximum performance.

Precisely, you will master your knowledge in:
– Writing and executing Hive & Spark SQL queries;
– Reasoning how the queries are translated into actual execution primitives (be it MapReduce jobs or Spark transformations);
– Organizing your data in Hive to optimize disk space usage and execution times;
– Constructing Spark DataFrames and using them to write ad-hoc analytical jobs easily;
– Processing large graphs with Spark GraphFrames;
– Debugging, profiling and optimizing Spark application performance.

Still in doubt? Check this out. Become a data ninja by taking this course!

Special thanks to:
– Prof. Mikhail Roytberg, APT dept., MIPT, who was the initial reviewer of the project, the supervisor and mentor of half of the BigData team. He was the one, who helped to get this show on the road.
– Oleg Sukhoroslov (PhD, Senior Researcher at IITP RAS), who has been teaching MapReduce, Hadoop and friends since 2008. Now he is leading the infrastructure team.
– Oleg Ivchenko (PhD student APT dept., MIPT), Pavel Akhtyamov (MSc. student at APT dept., MIPT) and Vladimir Kuznetsov (Assistant at P.G. Demidov Yaroslavl State University), superbrains who have developed and now maintain the infrastructure used for practical assignments in this course.
– Asya Roitberg, Eugene Baulin, Marina Sudarikova. These people never sleep to babysit this course day and night, to make your learning experience productive, smooth and exciting.

课程大纲

Welcome to the Second Course: Big Data Analysis

Big Data SQL: Hive

Big Data SQL: Hive (practice week)

Spark SQL and Spark Dataframe

Graph Analysis from Big Data Perspective

PageRank and Recent Advances

Spark Internals and Optimization

千万首歌曲。全无广告干扰。
此外,您还能在所有设备上欣赏您的整个音乐资料库。免费畅听 3 个月,之后每月只需 ¥10.00。
Apple 广告
声明:MOOC中国十分重视知识产权问题,我们发布之课程均源自下列机构,版权均归其所有,本站仅作报道收录并尊重其著作权益。感谢他们对MOOC事业做出的贡献!
  • Coursera
  • edX
  • OpenLearning
  • FutureLearn
  • iversity
  • Udacity
  • NovoEd
  • Canvas
  • Open2Study
  • Google
  • ewant
  • FUN
  • IOC-Athlete-MOOC
  • World-Science-U
  • Codecademy
  • CourseSites
  • opencourseworld
  • ShareCourse
  • gacco
  • MiriadaX
  • JANUX
  • openhpi
  • Stanford-Open-Edx
  • 网易云课堂
  • 中国大学MOOC
  • 学堂在线
  • 顶你学堂
  • 华文慕课
  • 好大学在线CnMooc
  • (部分课程由Coursera、Udemy、Linkshare共同提供)

© 2008-2020 MOOC.CN 慕课改变你,你改变世界