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

Отзывы учащихся о курсе Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames от партнера Яндекс

3.9
звезд
Оценки: 196
Рецензии: 45

О курсе

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....

Лучшие рецензии

SM
12 нояб. 2018 г.

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.

SS
2 февр. 2018 г.

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

Фильтр по:

26–45 из 45 отзывов о курсе Big Data Analysis: Hive, Spark SQL, DataFrames and GraphFrames

автор: Phi H T

18 дек. 2018 г.

Very useful

автор: Minh T

29 сент. 2019 г.

Great!!!!

автор: Alok K

22 июля 2019 г.

vey nice

автор: Alex Q G

7 июня 2020 г.

El tema de GraphFrames ha sido bastante complejo, sin embargo no te brinda las herramientas suficientes para poder comprender y resolver la última tarea práctica (honor task) . Por lo demás ha sido un muy buen curso, sobre todo las tres primeras semanas.

автор: Viacheslav I

9 дек. 2017 г.

Quite a good course, but weeks about graphs I found somewhat poor. Apart from that you learn basics of Hive, details of DataFrame API of Spark and how it internally works.

автор: Alexander K

23 мая 2019 г.

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

автор: Aldrin

30 июля 2019 г.

Good course...Deep dive into optimization of spark for production environment.Also interesting graph implementations

автор: Luis M A P

27 мар. 2019 г.

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

автор: Adarsh G

29 дек. 2019 г.

Wonderful course for new learners. Thanks !!!

автор: Emile P R

3 янв. 2021 г.

This one was not for playing.

автор: Дюкарев В В

16 сент. 2019 г.

This is 2nd course of specialization and its better than 1st, but big big problems with outer grader system is still there :(

Another minus is that there is too much theory (graph algorithms especially) and too less practice, i think 1/10. You know theory is forgotten very fast.

Nevertheless its good, valuable course for review of technologies

автор: Evgenii K

15 мая 2018 г.

Grading system it terrible, it hadn't work for a week summary, no help from staff on Coursera forum, only Slack channel could help. Theoretical material is quite good.

автор: ANNAMALAI A

26 авг. 2019 г.

Few Environment not supporting frequently.

автор: Pavlo R

30 окт. 2020 г.

Speakers are poor, except of last one

Grader is poor

Technical support will help you within a ... week, in best case

автор: Evgenii M

6 окт. 2021 г.

Bugged grader and complete lack of support from the course admins

автор: Enrique A M

10 окт. 2020 г.

gracias, no e podido completarlo.

автор: Andrey N

7 янв. 2022 г.

Today on the 7th of January, there are grader problems that are not fixed since at least the 24th of November of the previous year.. While the whole course has deadline within 6 weeks, they do not fix the bugs in the PAID course within this 6 weeks. That is just unacceptable!

автор: Haithem H

13 мая 2020 г.

There is many issues in LTI grader. At the begining, I have been attracted by the content, and as far as I moved on the grader has pushed every thing down

автор: karimulla k

29 дек. 2020 г.

Worst course very difficult to pass

автор: Cedric L s

30 апр. 2020 г.

Le cours n'est pas bien structuré