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Big Data Analysis with Scala and Spark(으)로 돌아가기

로잔연방공과대학교의 Big Data Analysis with Scala and Spark 학습자 리뷰 및 피드백

2,548개의 평가

강좌 소개

Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections. Through hands-on examples in Spark and Scala, we'll learn when important issues related to distribution like latency and network communication should be considered and how they can be addressed effectively for improved performance. Learning Outcomes. By the end of this course you will be able to: - read data from persistent storage and load it into Apache Spark, - manipulate data with Spark and Scala, - express algorithms for data analysis in a functional style, - recognize how to avoid shuffles and recomputation in Spark, Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Parallel Programming:

최상위 리뷰


2019년 11월 28일

Excellent overview of Spark, including exercises that solidify what you learn during the lectures. The development environment setup tutorials were also very helpful, as I had not yet worked with sbt.


2017년 6월 7일

The sessions where clearly explained and focused. Some of the exercises contained slightly confusing hints and information, but I'm sure those mistakes will be ironed out in future iterations. Thanks!

필터링 기준:

Big Data Analysis with Scala and Spark의 506개 리뷰 중 426~450

교육 기관: Francis T

2017년 4월 16일

I really liked the content regarding Dataframes and Datasets.

교육 기관: Emmanouil G

2017년 4월 1일

Assignment Instructions need improvement in terms of clarity.

교육 기관: Gongqi L

2017년 4월 9일

Very good course, but it needs more details and examples.

교육 기관: kaushik

2017년 4월 9일

Good course ! But does need more programming assignments

교육 기관: Mohammad T

2019년 8월 24일

such a beautiful course design for a bigData devlopers

교육 기관: Kota M

2018년 4월 5일

It is a good course, but the lecturer speaks too fast.

교육 기관: Anuj A

2020년 10월 22일

Needs more detailing for datasets and dataframe apis

교육 기관: Wolfgang G

2017년 8월 30일

Very well-lead introductory, a bit lengthy at times.

교육 기관: Manuel W

2017년 4월 18일

Would be better to have more and shorter exercises.

교육 기관: Ruslan A

2017년 8월 23일

lectures don't correlate to practical assigment :(

교육 기관: David G

2017년 8월 25일

Great course, but can be great idea have the ppts

교육 기관: Yuan R

2018년 1월 20일

Great course that is very practical for the job.

교육 기관: Guillermo G H

2017년 6월 30일

Great approach to learn about Spark in practice

교육 기관: Michaël M P

2019년 2월 5일

Talk about how to set Scala version in Eclipse

교육 기관: 林鼎棋

2017년 5월 29일

Great! But I want to know more about dataset!

교육 기관: VeeraVenkataSatyanarayana M

2017년 6월 4일

Basics are covered in an effective way.

교육 기관: Pavel O

2017년 8월 12일

Good final course for Scala learners.

교육 기관: Lucas F

2017년 5월 15일

Great lectures and great content!

교육 기관: Роман В

2018년 6월 24일

I would like to learn some more.

교육 기관: Park H

2017년 4월 18일

Learned Spark APIs, internals.

교육 기관: Alberto P d P

2017년 5월 12일

Very good and concise course.

교육 기관: Dibash B

2022년 7월 1일

nice spark indepth knowledge

교육 기관: Javier L B

2021년 12월 7일

Good course.

교육 기관: Stéphane L

2017년 10월 13일

Very useful