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.
Hadoop Platform and Application Framework
ofrecido por
Universidad de California en San Diego
Acerca de este Curso
40,775 vistas recientes
Habilidades que obtendrás
Python ProgrammingApache HadoopMapreduceApache Spark
Programa - Qué aprenderás en este curso
Semana
12 horas para completar
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.
7 videos (Total 53 minutos), 4 readings, 1 quiz
7 videos
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
4 lecturas
Apache Hadoop Ecosystem10m
Lesson 1 Slides (PDF)10m
Hardware & Software Requirements10m
Lesson 2 Slides - Cloudera VM Tour10m
1 ejercicio de práctica
Basic Hadoop Stack20m
Semana
23 horas para completar
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.
10 videos (Total 70 minutos), 6 readings, 3 quizzes
10 videos
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
6 lecturas
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
3 ejercicios de práctica
Overview of Hadoop Stack10m
Hadoop Execution Environment14m
Hadoop Applications12m
Semana
32 horas para completar
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.
9 videos (Total 58 minutos), 5 readings, 3 quizzes
9 videos
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
5 lecturas
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
3 ejercicios de práctica
HDFS Architecture12m
HDFS performance,tuning, and robustness10m
Accessing HDFS12m
Semana
47 horas para completar
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.
9 videos (Total 27 minutos), 3 readings, 3 quizzes
9 videos
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
3 lecturas
Lesson 1: Introduction to MapReduce - Slides10m
A note on debugging map/reduce programs.10m
Lesson 2: MapReduce Examples and Principles - Slides10m
1 ejercicio de práctica
Lesson 1 Review14m
29%
comenzó una nueva carrera después de completar estos cursos
24%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Principales revisiones sobre Hadoop Platform and Application Framework
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.
Instructores
Natasha Balac
Director, Predictive Analytics Center of Excellence (PACE)San Diego Supercomputer Center
Paul Rodriguez
Research ProgrammerSan Diego Supercomputer Center (SDSC)
Andrea Zonca
HPC Applications SpecialistSan Diego Supercomputer Center (SDSC)
Acerca de Universidad de California en San Diego
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Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si compro el Certificado?
Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.
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¿Hay ayuda económica disponible?
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