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.
提供方
Hadoop 平台和应用程序框架
加州大学圣地亚哥分校
課程信息
50,294 次近期查看
Learner Career Outcomes
30%
完成這些課程後已開始新的職業生涯
27%
通過此課程獲得實實在在的工作福利
您將獲得的技能
Python ProgrammingApache HadoopMapreduceApache Spark
Learner Career Outcomes
30%
完成這些課程後已開始新的職業生涯
27%
通過此課程獲得實實在在的工作福利
100% 在線
立即開始，按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
完成時間大約為19 小時
建議：5 weeks of study, 1-2 hours/week
英語（English）
字幕：英語（English）
教學大綱 - 您將從這門課程中學到什麼
完成時間為 2 小時
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.
完成時間為 2 小時
7 個視頻 （總計 53 分鐘）, 4 個閱讀材料, 1 個測驗
7 個視頻
The Apache Framework: Basic Modules3分鐘
Hadoop Distributed File System (HDFS)5分鐘
The Hadoop "Zoo"5分鐘
Hadoop Ecosystem Major Components11分鐘
Exploring the Cloudera VM: Hands-On Part 116分鐘
Exploring the Cloudera VM: Hands-On Part 26分鐘
4 個閱讀材料
Apache Hadoop Ecosystem10分鐘
Lesson 1 Slides (PDF)10分鐘
Hardware & Software Requirements10分鐘
Lesson 2 Slides - Cloudera VM Tour10分鐘
1 個練習
Basic Hadoop Stack20分鐘
完成時間為 3 小時
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.
完成時間為 3 小時
10 個視頻 （總計 70 分鐘）, 6 個閱讀材料, 3 個測驗
10 個視頻
The Hadoop Distributed File System (HDFS) and HDFS28分鐘
MapReduce Framework and YARN8分鐘
The Hadoop Execution Environment4分鐘
YARN, Tez, and Spark11分鐘
Hadoop Resource Scheduling6分鐘
Hadoop-Based Applications3分鐘
Introduction to Apache Pig7分鐘
Introduction to Apache HIVE7分鐘
Introduction to Apache HBASE7分鐘
6 個閱讀材料
Hadoop Basics - Lesson 1 Slides10分鐘
Lesson 2: Hadoop Execution Environment - Slides10分鐘
Lesson 3: Hadoop-Based Applications Overview - All Slides10分鐘
Command list for Applications Slides10分鐘
Tips to handle service connection errors10分鐘
References for Applications10分鐘
3 個練習
Overview of Hadoop Stack10分鐘
Hadoop Execution Environment14分鐘
Hadoop Applications12分鐘
完成時間為 2 小時
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.
完成時間為 2 小時
9 個視頻 （總計 58 分鐘）, 5 個閱讀材料, 3 個測驗
9 個視頻
The HDFS Performance Envelope5分鐘
Read/Write Processes in HDFS4分鐘
HDFS Tuning Parameters6分鐘
HDFS Performance and Robustness9分鐘
Overview of HDFS Access, APIs, and Applications5分鐘
HDFS Commands8分鐘
Native Java API for HDFS4分鐘
REST API for HDFS8分鐘
5 個閱讀材料
Lesson 1: Introduction to HDFS - Slides10分鐘
HDFS references10分鐘
Lesson 2: HDFS Performance and Tuning - Slides10分鐘
HDFS Access, APIs10分鐘
Lesson 3: HDFS Access, APIs, Applications - Slides10分鐘
3 個練習
HDFS Architecture12分鐘
HDFS performance,tuning, and robustness10分鐘
Accessing HDFS12分鐘
完成時間為 7 小時
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.
完成時間為 7 小時
9 個視頻 （總計 27 分鐘）, 3 個閱讀材料, 3 個測驗
9 個視頻
The Map/Reduce Framework2分鐘
A MapReduce Example: Wordcount in detail4分鐘
MapReduce: Intro to Examples and Principles2分鐘
MapReduce Example: Trending Wordcount1分鐘
MapReduce Example: Joining Data4分鐘
MapReduce Example: Vector Multiplication2分鐘
Computational Costs of Vector Multiplication3分鐘
MapReduce Summary2分鐘
3 個閱讀材料
Lesson 1: Introduction to MapReduce - Slides10分鐘
A note on debugging map/reduce programs.10分鐘
Lesson 2: MapReduce Examples and Principles - Slides10分鐘
1 個練習
Lesson 1 Review14分鐘
3.9
713 條評論
來自Hadoop 平台和应用程序框架的熱門評論
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.
Super hands on introduction to key Hadoop components, such as Spark, Map Reduce, Hive, Pig, HBase, HDFS, YARN, Squoop and Flume.\n\nI can't wait to the next course on the specialization.
講師
Natasha Balac, Ph.D.
Interdisciplinary Center for Data ScienceQualcomm Institute/CalIT2
Paul Rodriguez
Research ProgrammerSan Diego Supercomputer Center (SDSC)
Andrea Zonca
HPC Applications SpecialistSan Diego Supercomputer Center (SDSC)
關於 加州大学圣地亚哥分校
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.
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