课程信息
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第 4 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

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完成时间大约为15 小时

建议:6 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

Scala ProgrammingBig DataApache SparkSQL

第 4 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

完成时间大约为15 小时

建议:6 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 12 小时

Getting Started + Spark Basics

7 个视频 (总计 105 分钟), 5 个阅读材料, 3 个测验
7 个视频
Data-Parallel to Distributed Data-Parallel10分钟
Latency24分钟
RDDs, Spark's Distributed Collection9分钟
RDDs: Transformation and Actions16分钟
Evaluation in Spark: Unlike Scala Collections!20分钟
Cluster Topology Matters!8分钟
5 个阅读材料
Tools setup10分钟
Sbt tutorial10分钟
Intellij IDEA Tutorial10分钟
Eclipse tutorial10分钟
Submitting solutions10分钟
2
完成时间为 7 小时

Reduction Operations & Distributed Key-Value Pairs

4 个视频 (总计 59 分钟), 2 个测验
4 个视频
Pair RDDs6分钟
Transformations and Actions on Pair RDDs20分钟
Joins17分钟
3
完成时间为 1 小时

Partitioning and Shuffling

4 个视频 (总计 57 分钟)
4 个视频
Partitioning14分钟
Optimizing with Partitioners11分钟
Wide vs Narrow Dependencies16分钟
4
完成时间为 8 小时

Structured data: SQL, Dataframes, and Datasets

5 个视频 (总计 133 分钟), 2 个测验
5 个视频
Spark SQL17分钟
DataFrames (1)26分钟
DataFrames (2)30分钟
Datasets43分钟
4.7
421 条评论Chevron Right

11%

完成这些课程后已开始新的职业生涯

15%

通过此课程获得实实在在的工作福利

12%

加薪或升职

来自Big Data Analysis with Scala and Spark的热门评论

创建者 BPNov 29th 2019

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.

创建者 CCJun 8th 2017

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!

讲师

Avatar

Prof. Heather Miller

Assistant Professor
Carnegie Mellon University

关于 洛桑联邦理工学院

关于 Functional Programming in Scala 专项课程

Discover how to write elegant code that works the first time it is run. This Specialization provides a hands-on introduction to functional programming using the widespread programming language, Scala. It begins from the basic building blocks of the functional paradigm, first showing how to use these blocks to solve small problems, before building up to combining these concepts to architect larger functional programs. You'll see how the functional paradigm facilitates parallel and distributed programming, and through a series of hands on examples and programming assignments, you'll learn how to analyze data sets small to large; from parallel programming on multicore architectures, to distributed programming on a cluster using Apache Spark. A final capstone project will allow you to apply the skills you learned by building a large data-intensive application using real-world data....
Functional Programming in Scala

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