This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process.
от партнера
Hadoop Platform and Application Framework
Калифорнийский университет в Сан-ДиегоОб этом курсе
Приобретаемые навыки
- Python Programming
- Apache Hadoop
- Mapreduce
- Apache Spark
от партнера

Калифорнийский университет в Сан-Диего
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Программа курса: что вы изучите
Hadoop Basics
Welcome to the first module of the Big Data Platform course. This first module will provide insight into Big Data Hype, its technologies opportunities and challenges. We will take a deeper look into the Hadoop stack and tool and technologies associated with Big Data solutions.
Introduction to the Hadoop Stack
In this module we will take a detailed look at the Hadoop stack ranging from the basic HDFS components, to application execution frameworks, and languages, services.
Introduction to Hadoop Distributed File System (HDFS)
In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance and robustness, and get an overview of the different ways you can access data on HDFS.
Introduction to Map/Reduce
This module will introduce Map/Reduce concepts and practice. You will learn about the big idea of Map/Reduce and you will learn how to design, implement, and execute tasks in the map/reduce framework. You will also learn the trade-offs in map/reduce and how that motivates other tools.
Рецензии
- 5 stars45,42 %
- 4 stars28,06 %
- 3 stars12,37 %
- 2 stars6,71 %
- 1 star7,41 %
Лучшие отзывы о курсе HADOOP PLATFORM AND APPLICATION FRAMEWORK
Covers the basics well, but lacks depth and integration between the weeks. E.g. it would be nice to see how to use Spark + HDFS together and what the efficiency considerations are.
I'm forced to give 5 stars. I don't want to have a certification on a poor quality course (another coursera mistake). This material needs tremendous amount of work to get finished and revised.
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I don't think the answers of quiz are accurate. Some answers may be true in some cases, but not in others. Difficult to choose, even review the videos and do some google.
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