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Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames(으)로 돌아가기

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

4.0
108개의 평가
21개의 리뷰

About this Course

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....

최상위 리뷰

대학: SM

Nov 13, 2018

content of the course is remarkable and the way they explained concepts is very lucid. I just want to give suggestions please give link to the data set they are using for illustrating the concepts.

대학: SS

Feb 03, 2018

I wish I could give more rating than 5 :). Excellent course. Thanks so much for such an excellent course. All the instructors are great.

필터링 기준:

21개의 리뷰

대학: Kiselyov Alexander

May 23, 2019

Nice course, but the impression about practical tasks is really awful. The tasks are ok, but grading system is too buggy

대학: Dilip Nair

Apr 01, 2019

Good informative Course

대학: Luis Manuel Arcia Pérez

Mar 27, 2019

Good. Please fix assignments explanations. i.e In week 5.

대학: Симкин Иван Михайлович

Feb 01, 2019

Excellent teachers, but material from lessons on graphs required a lot of time.

대학: Павел Сорокин

Jan 20, 2019

minuses: GraphFrames seems useless. No tasks on them. And a lot of time were spent on algorithms, not spark functions and internals.

Other were good!

대학: Pismarev Vitaly

Jan 06, 2019

I think lessons about GraphFrames were too hard. I cannot understood a lot about algorithmes and didn't do honor tasks ( More examples and more explanatons could help a lot

대학: Phi Hong Thai

Dec 18, 2018

Very useful

대학: Marco Gorelli

Dec 05, 2018

Unfortunately, I often spent more time trying to get my assignments to pass the automatic grader than on solving them. This made the course a bit frustrating at times.

대학: shatabdi mandal

Nov 13, 2018

content of the course is remarkable and the way they explained concepts is very lucid. I just want to give suggestions please give link to the data set they are using for illustrating the concepts.

대학: Shubhajit Saha

Sep 07, 2018

Only good content can not suffice for a good tutorial. I tried hard to pursue this course, but now giving up for the poor speakers, poor communication and lack of helpful visual aids.

Thank you.