Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Hadoop and Spark Fundamentals 专项课程

Hadoop and Spark Fundamentals 专项课程

Get Started With Hadoop and Spark. Core components, tools, installation, and data processing for the Apache Hadoop Big Data ecosystem.

位教师：Pearson

包含在 Coursera Plus 中

了解更多

3 门课程系列

深入学习学科知识

中级等级

推荐体验

4 周完成

在 5 小时一周

灵活的计划

自行安排学习进度

3 门课程系列

深入学习学科知识

中级等级

推荐体验

4 周完成

在 5 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Install, configure, and operate Hadoop and Spark environments on both single machines and clusters, utilizing tools like Ambari and Zeppelin for effective management and development.
Understand and apply core big data concepts, including HDFS, MapReduce, PySpark, HiveQL, and advanced data ingestion techniques using Flume and Sqoop.
Develop, run, and debug data analytics applications, leveraging higher-level tools and scripting languages to efficiently process and analyze large datasets.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

向大学和行业专家学习热门技能
借助实践项目精通一门科目或一个工具
培养对关键概念的深入理解
通过 Pearson 获得职业证书

专业化 - 3门课程系列

Gain practical, hands-on experience installing and running Hadoop and Spark on your own desktop or laptop, and progress to managing real-world cluster deployments. Through engaging lessons and interactive examples, you’ll master essential concepts such as HDFS, MapReduce, PySpark, HiveQL, and data ingestion tools, while also learning to leverage user-friendly interfaces like Ambari and Zeppelin to streamline analytics workflows and cluster administration. By the end of this course, you’ll possess the foundational skills and confidence to begin your journey in big data analytics and explore the vast Hadoop ecosystem.

应用的学习项目

Run Apache Pig, Hive, Flume, Sqoop, Oozie, Spark applications and write basic MapReduce/Spark programs. The steps for easily installing a working Hadoop/Spark system on a desktop/laptop and on a local stand-alone cluster using the powerful Ambari GUI are also included. All software used is open source and freely available.

Hadoop and Spark Fundamentals: Unit 1

第 1 门课程6小时

您将学到什么

Understand the core concepts of Hadoop, including its architecture, data lake metaphor, and the role of MapReduce and Spark in big data analytics.
Install and configure a full-featured Hadoop and Spark environment on your desktop or laptop using the Hortonworks HDP sandbox.
Navigate and utilize the Hadoop Distributed File System (HDFS), including advanced features like high availability and federation.
Gain hands-on experience running Hadoop and Spark applications, preparing you for real-world data analytics challenges.

您将获得的技能

类别：Apache Hadoop

类别：Linux Commands

类别：File Systems

类别：Apache Spark

类别：Software Installation

类别：Command-Line Interface

类别：Data Lakes

类别：Big Data

类别：Distributed Computing

类别：Data Processing

类别：Data Management

类别：System Configuration

类别：Linux

Hadoop and Spark Fundamentals: Unit 2

第 2 门课程6小时

您将学到什么

Understand and implement Hadoop MapReduce for distributed data processing, including compiling, running, and debugging applications.
Apply advanced MapReduce techniques to real-world scenarios such as log analysis and large-scale text processing.
Utilize higher-level tools like Apache Pig and Hive QL to streamline data workflows and perform complex queries.
Gain hands-on experience with Apache Spark and PySpark for modern, scalable data analytics.

您将获得的技能

类别：Apache Hadoop

类别：Apache Spark

类别：PySpark

类别：Apache Hive

类别：Data Processing

类别：Debugging

类别：Java Programming

类别：Analytics

类别：Distributed Computing

类别：Big Data

类别：Data Mapping

类别：Text Mining

类别：Java

Hadoop and Spark Fundamentals: Unit 3

第 3 门课程7小时

您将学到什么

Master advanced data ingestion techniques into Hadoop HDFS, including Hive, Spark, Flume, and Sqoop.
Develop and run interactive Spark applications using the Apache Zeppelin web interface.
Install, monitor, and administer Hadoop clusters with Ambari and essential command-line tools.
Utilize advanced HDFS features such as snapshots and NFS mounts for enhanced data management.

您将获得的技能

类别：Apache Spark

类别：Apache Hive

类别：Data Import/Export

类别：Software Installation

类别：Data Pipelines

类别：Big Data

类别：Apache Hadoop

类别：Data Integration

类别：Data Processing

类别：Relational Databases

类别：Command-Line Interface

类别：Configuration Management

类别：File Systems

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Pearson

268 门课程9,454 名学生

提供方

Pearson

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生

''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'

Jennifer J.

自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生

''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'

Chaitanya A.

''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'

通过 Coursera Plus 开启新生涯

无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

了解更多

通过在线学位推动您的职业生涯

获取世界一流大学的学位 - 100% 在线

探索学位

加入超过 3400 家选择 Coursera for Business 的全球公司

提升员工的技能，使其在数字经济中脱颖而出

了解更多

常见问题

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.