In this course, you'll get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL.
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课程信息
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第 2 门课程（共 3 门）
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初级
完成时间大约为17 小时
英语（English）
字幕：法语（French）, 巴西葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
您将获得的技能
Apache HiveApache ImpalaData AnalysisBig DataSQL
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 2 门课程（共 3 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为17 小时
英语（English）
字幕：法语（French）, 巴西葡萄牙语, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）
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.
教学大纲 - 您将从这门课程中学到什么
完成时间为 3 小时
Orientation to SQL on Big Data
完成时间为 3 小时
9 个视频 （总计 47 分钟）, 5 个阅读材料, 2 个测验
9 个视频
Review and Preparation4分钟
Using the Hue Query Editors7分钟
Running SQL Utility Statements6分钟
Running SQL SELECT Statements5分钟
Understanding Different SQL Interfaces4分钟
Overview of Beeline and Impala Shell2分钟
Using Beeline8分钟
Using Impala Shell3分钟
5 个阅读材料
Instructions for Downloading and Installing the Exercise Environment30分钟
Troubleshooting the VM5分钟
(Optional) What about Spark SQL?10分钟
Expectations for Learners10分钟
(Optional) Using Other SQL Engines10分钟
2 个练习
Week 1 Core Quiz30分钟
Week 1 Honors Quiz5分钟
完成时间为 3 小时
SQL SELECT Essentials
完成时间为 3 小时
16 个视频 （总计 83 分钟）, 4 个阅读材料, 2 个测验
16 个视频
Introduction2分钟
SQL SELECT Building Blocks2分钟
Introduction to the SELECT List7分钟
Expressions and Operators7分钟
Data Types6分钟
Column Aliases5分钟
Built-In Functions7分钟
Data Type Conversion5分钟
The DISTINCT Keyword5分钟
Introduction to the FROM Clause3分钟
Identifiers7分钟
Formatting SELECT Statements4分钟
Using Beeline in Non-Interactive Mode5分钟
Using Impala Shell in Non-Interactive Mode4分钟
Formatting the Output of Beeline and Impala Shell4分钟
Saving Hive and Impala Query Results to a File5分钟
4 个阅读材料
Order of Operations5分钟
Division and Modulo Operators15分钟
Common String Functions15分钟
Case (In)Sensitivity in SQL10分钟
2 个练习
Week 2 Core Quiz30分钟
Week 2 Honors Quiz5分钟
完成时间为 3 小时
Filtering Data
完成时间为 3 小时
14 个视频 （总计 85 分钟）, 6 个阅读材料, 2 个测验
14 个视频
Introduction1分钟
About the Datasets4分钟
Introduction to the WHERE Clause2分钟
Using Expressions in the WHERE Clause9分钟
Comparison Operators9分钟
Data Types and Precision4分钟
Logical Operators7分钟
Other Relational Operators4分钟
Understanding Missing Values8分钟
Handling Missing Values6分钟
Conditional Functions9分钟
Using Variables with Beeline and Impala Shell7分钟
Calling Beeline and Impala Shell from Scripts6分钟
Querying Hive and Impala in Scripts and Applications2分钟
6 个阅读材料
Data Reference5分钟
(Optional) Unicode Characters10分钟
Working with Literal Strings15分钟
Missing Values with Logical Operators10分钟
Missing Values in String Columns5分钟
(Optional Exercise) Change VM Desktop Color30分钟
2 个练习
Week 3 Core Quiz30分钟
Week 3 Honors Quiz5分钟
完成时间为 3 小时
Grouping and Aggregating Data
完成时间为 3 小时
15 个视频 （总计 82 分钟）, 6 个阅读材料, 2 个测验
15 个视频
Introduction1分钟
Introduction to Aggregation2分钟
Common Aggregate Functions2分钟
Using Aggregate Functions in the SELECT Statement8分钟
Introduction to the GROUP BY Clause6分钟
Choosing an Aggregate Function and Grouping Column4分钟
Grouping Expressions6分钟
Grouping and Aggregation, Together and Separately5分钟
NULL Values in Grouping and Aggregation4分钟
The COUNT Function7分钟
Tips for Applying Grouping and Aggregation7分钟
Filtering on Aggregates2分钟
The HAVING Clause8分钟
Understanding Hive and Impala Version Differences10分钟
Understanding Hue Version Differences2分钟
6 个阅读材料
COUNT(*) and SUM(1)5分钟
Interpreting Aggregates: Populations and Samples10分钟
The least and greatest Functions5分钟
Why Aggregate Expressions Ignore NULL Values5分钟
(Optional) Shortcuts for Grouping10分钟
How Grouping and Aggregation Can Mislead10分钟
2 个练习
Week 4 Core Quiz30分钟
Week 4 Honors Quiz10分钟
审阅
来自ANALYZING BIG DATA WITH SQL的热门评论
由 MN 提供Aug 5, 2020
How amazing the course was! From the video lectures, the reading materials, to the practical exercises and the teachers as well, everything was fantastic in this course. Highly recommended!
由 JC 提供Apr 15, 2020
Excellent course even if you have an sql knowledge with a bachelor. Especially the part where it explains the handling of NULLs which is not obvious and I didn't know about.
由 HD 提供Jun 12, 2020
It is no common for me to put 5 star score to courses, but this courser was literally comprehensive. Thanks to all staff and instructor.
由 FT 提供Jul 9, 2020
I have took many SQL courses but this is one of the best ,I highly recommend this course to beginners, It takes you from zero to hero.
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.
常见问题
我什么时候能够访问课程视频和作业？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
- 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。
Is financial aid available?
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。
