本课程是 Modern Big Data Analysis with SQL 专项课程专项课程的一部分

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Ian Cook 另外 +1 位授课教师
顶尖授课教师

9,140 人已注册

提供方

Modern Big Data Analysis with SQL 专项课程Cloudera

课程信息

15,321 次近期查看

In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.
By the end of the course, you will be able to
• use different tools to browse existing databases and tables in big data systems;
• use different tools to explore files in distributed big data filesystems and cloud storage;
• create and manage big data databases and tables using Apache Hive and Apache Impala; and
• describe and choose among different data types and file formats for big data systems.

To use the hands-on environment for this course, you need to download and install a virtual machine and the software on which to run it. Before continuing, be sure that you have access to a computer that meets the following hardware and software requirements:
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work)
• 64-bit operating system (32-bit operating systems will not work)
• 8 GB RAM or more
• 25GB free disk space or more
• Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled;
on Windows and Linux computers, you might need to enable it in the BIOS)
• For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

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第 3 门课程（共 3 门）

Modern Big Data Analysis with SQL 专项课程

初级

完成时间大约为21 小时

英语（English）

字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）

您将学到的内容有

Use different tools to browse existing databases and tables in big data systems

Use different tools to explore files in distributed big data filesystems and cloud storage

Create and manage big data databases and tables using Apache Hive and Apache Impala

Describe and choose among different data types and file formats for big data systems

您将获得的技能

Data Management
Distributed File Systems
Cloud Storage
Big Data
SQL

可灵活调整截止日期

根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 3 门课程（共 3 门）

Modern Big Data Analysis with SQL 专项课程

初级

完成时间大约为21 小时

英语（English）

授课教师

授课教师评分

4.88/5 （44 个评分）

Ian Cook
顶尖授课教师

Staff Curriculum Developer

Cloudera

22,248 个学生

2 门课程

Glynn Durham

提供方

Cloudera

At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights. Cloudera delivers an enterprise data cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

授课大纲 - 您将从这门课程中学到什么

周

周 1

完成时间为 3 小时

Orientation to Data in Clusters and Cloud Storage

完成时间为 3 小时

7 个视频（总计 56 分钟）, 3 个阅读材料, 1 个测验

7 个视频

Welcome to the Course4分钟

Browsing Tables with Hue7分钟

Browsing Tables with SQL Utility Statements6分钟

Browsing HDFS with the Hue File Browser13分钟

Browsing HDFS from the Command Line9分钟

Understanding S3 and Other Cloud Storage Platforms6分钟

Browsing S3 Buckets from the Command Line8分钟

3 个阅读材料

Review and Preparation30分钟

Instructions for Downloading and Installing the Exercise Environment30分钟

Troubleshooting the VM5分钟

1 个练习

Week 1 Graded Quiz30分钟

周

周 2

完成时间为 5 小时

Defining Databases, Tables, and Columns

完成时间为 5 小时

7 个视频（总计 33 分钟）, 12 个阅读材料, 2 个测验

7 个视频

Week 2 Introduction3分钟

Introduction to the CREATE TABLE Statement5分钟

Using Different Schemas on the Same Data12分钟

Specifying TBLPROPERTIES2分钟

Examining, Modifying, and Removing Tables1分钟

Hive and Impala Interoperability2分钟

Impala Metadata Refresh3分钟

12 个阅读材料

Creating Databases and Tables with Hue30分钟

Creating Databases and Tables with SQL15分钟

Permissions to Create Databases and Tables5分钟

The ROW FORMAT Clause25分钟

The STORED AS Clause15分钟

The LOCATION Clause20分钟

CREATE TABLE Shortcuts10分钟

Using Hive SerDes15分钟

Working with Unstructured and Semi-Structured Data15分钟

Examining Table Structure10分钟

Dropping Databases and Tables5分钟

Modifying Existing Tables35分钟

2 个练习

Week 2 Practice Quiz30分钟

Week 2 Graded Quiz30分钟

周

周 3

完成时间为 3 小时

Data Types and File Types

完成时间为 3 小时

5 个视频（总计 14 分钟）, 12 个阅读材料, 2 个测验

5 个视频

Week 3 Introduction1分钟

Overview of Data Types1分钟

Choosing the Right Data Types4分钟

Overview of File Types3分钟

Choosing the Right File Types3分钟

12 个阅读材料

Integer Data Types5分钟

Decimal Data Types10分钟

Character String Data Types10分钟

Other Data Types5分钟

Examining Data Types10分钟

Out-of-Range Values5分钟

Text Files5分钟

Avro Files5分钟

Parquet Files5分钟

ORC Files5分钟

Other File Types5分钟

Creating Tables with Avro and Parquet Files20分钟

2 个练习

Week 3 Practice Quiz20分钟

Week 3 Graded Quiz30分钟

周

周 4

完成时间为 5 小时

Managing Datasets in Clusters and Cloud Storage

完成时间为 5 小时

8 个视频（总计 48 分钟）, 13 个阅读材料, 3 个测验

8 个视频

Week 4 Introduction3分钟

Refresh Impala's Metadata Cache after Loading Data2分钟

Loading Files into HDFS with Hue's Table Browser10分钟

Loading Files into HDFS with Hue's File Browser6分钟

Loading Files into HDFS from the Command Line8分钟

Loading Files into S3 from the Command Line10分钟

Using Hive and Impala to Load Data into Tables3分钟

Conclusion2分钟

13 个阅读材料

More about HDFS Shell Commands10分钟

Chaining and Scripting with HDFS Commands5分钟

HDFS Permissions5分钟

Other Ways to Load Files into S35分钟

S3 Permissions10分钟

Missing Values15分钟

Character Sets5分钟

Using Sqoop to Import Data15分钟

More Sqoop Import Options5分钟

Using Sqoop to Export Data5分钟

SQL LOAD DATA Statements10分钟

SQL INSERT Statements10分钟

SQL INSERT ... SELECT and CTAS Statements15分钟

2 个练习

Week 4 Practice Quiz30分钟

Week 4 Graded Quiz30分钟

审阅

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来自MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE的热门评论

由 PZ 提供Sep 3, 2020

This was definitely the most challenging course I have done so far, but I am loving it! Glynn and Ian do a fantastic job of guiding you through the content in an engaging and practical manner.

由 SY 提供Feb 29, 2020

This is Very good course for a beginners, it gives you lots of exercises to practice in vm and course material is Really really good but only thing is you have to read a lot ,

由 AM 提供Dec 15, 2019

It would have been nice if videos would have been present instead of reading. Also a more deep diving would have been done in concepts like bucketing and indexing.

由 MA 提供Apr 13, 2020

This is one of the systematic specializations which makes the harder and otherwise overwhelming subject so easy to navigate, follow and learn.

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关于 Modern Big Data Analysis with SQL 专项课程

This Specialization teaches the essential skills for working with large-scale data using SQL.

Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you. Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable. To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines. This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches—Hive and Impala.

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课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
有助学金吗？
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
What are the hardware and software requirements for the exercise environment?
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)

还有其他问题吗？请访问学生帮助中心。

Managing Big Data in Clusters and Cloud Storage