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.
제공자:
캘리포니아 샌디에고 대학교
About this Course
최근 조회 51,772회
귀하가 습득할 기술
Python ProgrammingApache HadoopMapreduceApache Spark
Course을(를) 수강하는 학습자
- Data Engineers
- Data Scientists
- Data Analysts
- Machine Learning Engineers
- Software Engineers
강의 계획 - 이 강좌에서 배울 내용
주
1완료하는 데 2시간 필요
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.
7개 동영상 (총 53분), 4 readings, 1 quiz
7개의 동영상
The Apache Framework: Basic Modules3m
Hadoop Distributed File System (HDFS)5m
The Hadoop "Zoo"5m
Hadoop Ecosystem Major Components11m
Exploring the Cloudera VM: Hands-On Part 116m
Exploring the Cloudera VM: Hands-On Part 26m
4개의 읽기 자료
Apache Hadoop Ecosystem10m
Lesson 1 Slides (PDF)10m
Hardware & Software Requirements10m
Lesson 2 Slides - Cloudera VM Tour10m
1개 연습문제
Basic Hadoop Stack20m
주
2완료하는 데 3시간 필요
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.
10개 동영상 (총 70분), 6 readings, 3 quizzes
10개의 동영상
The Hadoop Distributed File System (HDFS) and HDFS28m
MapReduce Framework and YARN8m
The Hadoop Execution Environment4m
YARN, Tez, and Spark11m
Hadoop Resource Scheduling6m
Hadoop-Based Applications3m
Introduction to Apache Pig7m
Introduction to Apache HIVE7m
Introduction to Apache HBASE7m
6개의 읽기 자료
Hadoop Basics - Lesson 1 Slides10m
Lesson 2: Hadoop Execution Environment - Slides10m
Lesson 3: Hadoop-Based Applications Overview - All Slides10m
Command list for Applications Slides10m
Tips to handle service connection errors10m
References for Applications10m
3개 연습문제
Overview of Hadoop Stack10m
Hadoop Execution Environment14m
Hadoop Applications12m
주
3완료하는 데 2시간 필요
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.
9개 동영상 (총 58분), 5 readings, 3 quizzes
9개의 동영상
The HDFS Performance Envelope5m
Read/Write Processes in HDFS4m
HDFS Tuning Parameters6m
HDFS Performance and Robustness9m
Overview of HDFS Access, APIs, and Applications5m
HDFS Commands8m
Native Java API for HDFS4m
REST API for HDFS8m
5개의 읽기 자료
Lesson 1: Introduction to HDFS - Slides10m
HDFS references10m
Lesson 2: HDFS Performance and Tuning - Slides10m
HDFS Access, APIs10m
Lesson 3: HDFS Access, APIs, Applications - Slides10m
3개 연습문제
HDFS Architecture12m
HDFS performance,tuning, and robustness10m
Accessing HDFS12m
주
4완료하는 데 7시간 필요
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.
9개 동영상 (총 27분), 3 readings, 3 quizzes
9개의 동영상
The Map/Reduce Framework2m
A MapReduce Example: Wordcount in detail4m
MapReduce: Intro to Examples and Principles2m
MapReduce Example: Trending Wordcount1m
MapReduce Example: Joining Data4m
MapReduce Example: Vector Multiplication2m
Computational Costs of Vector Multiplication3m
MapReduce Summary2m
3개의 읽기 자료
Lesson 1: Introduction to MapReduce - Slides10m
A note on debugging map/reduce programs.10m
Lesson 2: MapReduce Examples and Principles - Slides10m
1개 연습문제
Lesson 1 Review14m
3.9
696개의 리뷰31%
이 강좌를 수료한 후 새로운 경력 시작하기
26%
이 강좌를 통해 확실한 경력상 이점 얻기
Hadoop Platform and Application Framework의 최상위 리뷰
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.
강사
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)
캘리포니아 샌디에고 대학교 정보
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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