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

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

4.7
별점
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: https://www.coursera.org/learn/parprog1....

최상위 리뷰

BP

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.

CC

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 376~400

교육 기관: Jose F O

2019년 12월 25일

It is a great course however the exercises make you waste time trying to figure out how the grader works. You really need to read the instructions word by word then go to the discussions to figure out from others questions the pitfalls.

교육 기관: Tony H

2017년 11월 18일

It felt short at 4 weeks! I wish it was longer and presented an assignment with each new concept-cluster.

Great information and I appreciated Dr. Miller's efforts to simplify the newly taught concepts and present with concrete examples.

교육 기관: Greg J

2019년 1월 24일

Assignments are challenging but reasonable and can be completed in the estimated time. The assignments seem a little out of sync with the course, though. Material taught in week 2 was recommended to be used on the week 1 assignment.

교육 기관: Tri N

2018년 4월 29일

Excellent course, RDD, DataFrame, Dataset are better discussed in this course than most of Spark books. SparkSQL is light however. The missing star is because some code suggested by the course is more imperative than functional.

교육 기관: Mark M

2017년 11월 20일

Dr. Miller's lectures are clear and concise. An excellent intro to Spark! This would have gotten a 5 star rating from me, if not for the unfortunate inclusion of the awful kmeans problem from the Parallel Programming class.

교육 기관: Adam R

2021년 8월 25일

Enjoyed learning about apache spark and optimizations in distributed data processing. I still feel like I've only been introduced to spark. Maybe if there was a Spark 2 course? I would like more familiarity with this tool.

교육 기관: Prateek G

2017년 4월 15일

Informative. Although, it a week course on architecture of Spark (especially YARN mode), explaining Spark Jobs, Stages & Tasks would be nice addition. Thank you for sharing knowledge and a wonderful learning experience!

교육 기관: Miguel D

2017년 4월 3일

I learned a lot and I really enjoyed the course. What I would improve - reference material from upcoming weeks should be organized (or at least added as recommended reading) if it helps the current week assignment.

교육 기관: Srinivas S

2018년 10월 24일

The exercises were below the standard of previous courses. Also the instructions on exercises could have been better. Lost a lot of time figuring out as a new bee in Spark.

교육 기관: Benj L

2020년 4월 3일

some of the questions are unnecessarily specific (i.e. needs to be rounded to 1 decimal and sorted exactly for it to work)

but otherwise, great lecturer and great content

교육 기관: Changli H

2017년 11월 17일

although spark part is taught nicely, it also takes a lot of time to understand the sql part and remember a lot of sql operations as a zero background man in sql

교육 기관: Alisdair W

2017년 4월 20일

Great course, I learned a lot through the course. However, some of the lectures are quite long and could do with being broken down in to more smaller segments.

교육 기관: antonin p

2018년 2월 25일

Great Sparks introduction. Still sometime unsure about the distributed vs local : should I compute this or that locally ? Or in a distributed manner ...

교육 기관: Eduardo

2017년 7월 16일

Quite insightful as a first or second approach to Spark. After being introduced to Spark dataframes, what's the value of Scala API over the Python one?

교육 기관: Du L

2018년 6월 2일

Very good introduction to spark. The assignment would be better if they were more targeted at spark, the underlying working of spark, efficiency etc.

교육 기관: Yilong W

2018년 5월 11일

Very practical course. You can quite freely apply the course material to the programming assignments. I feel like I really learnt Spark in details.

교육 기관: Vikash S

2020년 6월 22일

The spark internal details was quite descriptive for few topics. Need to add more topics mostly related to transformation and spark submit flow

교육 기관: MAHESH S

2017년 7월 18일

Introduction to kmeans or asking to read about kmeans would have helped. I found programming exercises more difficult then some other courses.

교육 기관: Tyler F

2018년 10월 6일

Somewhat specific, hard to reuse knowledge but do recommend if you're someone who works with Spark or even just work with someone who does.

교육 기관: Pravina

2018년 9월 8일

It would be great if there are 2 assignments covering dataframes and datasets spanning week3 & week4 instead of week 3 with no assignment

교육 기관: P.K

2017년 7월 15일

Way Much Better Presentation than the previous 2 courses in this Specialization!!!

Dr Heather and M. Odersky are really good professors!!!

교육 기관: Frédéric D

2017년 6월 18일

With this course, I surely improved my knowledge about Spark... But I am still thinking that Spark is an overly intricate framework.

교육 기관: Valter F

2019년 5월 29일

I love the indepth aproach at the RDDs. I'd say DataFrames and DataSets required a bit more examples and testing material though.

교육 기관: Björn W

2017년 4월 10일

Quizzes in the lecture videos would be nice. Also more, but shorter videos would be enjoyable. Programming assignments very nice!

교육 기관: Evgheni E

2017년 3월 24일

The video speed is way to fast, this woman is speaking really fast, first as i slowed the video down at 75% was its ok.