Chevron Left
返回到 Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames

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

4.0
101 個評分
20 個審閱

課程信息

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....

熱門審閱

創建者 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.

創建者 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.

篩選依據:

20 個審閱

創建者 Dilip Nair

Apr 01, 2019

Good informative Course

創建者 Luis Manuel Arcia Pérez

Mar 27, 2019

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

創建者 Симкин Иван Михайлович

Feb 01, 2019

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

創建者 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!

創建者 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

創建者 Phi Hong Thai

Dec 18, 2018

Very useful

創建者 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.

創建者 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.

創建者 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.

創建者 Jingting Lu

Sep 05, 2018

A decent course with lots of room for improvement to be great.

I absolutely loved the sections taught by the two Pavels. Their presentation is top notch in depth, structure and clarify.

I could not stand Natasha's lectures. Please read to the feedback on the forum and rework those weeks. It is a shame that there is such inconsistency of quality from week to week.

The issues with the grading machine are unacceptable. It gets tripped by simple, common variations in code. (Ie putting the name of the database in the from statement as opposed to using a standalone "use" statement in the hive assignment - executes perfectly in the sandbox). Would have been nice to call out explicitly or better yet, provide a template notebook with the line written. Hours wasted on such problems makes me hesitate to recommend this course to colleagues and friends despite that this is probably the best one on Coursera for now.