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
顶尖授课教师

20,605 人已注册

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Modern Big Data Analysis with SQL 专项课程Cloudera

课程信息

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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.
By the end of the course, you will be able to
• explore and navigate databases and tables using different tools;
• understand the basics of SELECT statements;
• understand how and why to filter results;
• explore grouping and aggregation to answer analytic questions;
• work with sorting and limiting results; and 
• combine multiple tables in different ways.

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 2 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18 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

Understand the basics of SELECT statements

Understand how and why to filter results

Explore grouping and aggregation to answer analytic questions

Work with sorting and limiting results

您将获得的技能

Apache Hive
Apache Impala
Data Analysis
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 2 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18 小时

英语（English）

授课教师

授课教师评分

4.91/5 （102 个评分）

Ian Cook
顶尖授课教师

Staff Curriculum Developer

Cloudera

22,212 个学生

2 门课程

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

内容评分95%（1,984 个评分）

周

周 1

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

Welcome to the Course4分钟

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

周

周 2

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

周

周 3

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

周

周 4

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

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来自ANALYZING BIG DATA WITH SQL的热门评论

由 AS 提供Dec 9, 2020

Great course! I would just add 1 more full business task for practicing before the final one. Anyway, I find the course very useful with clear and understandable explanation.\n\nThank you!

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 SC 提供Mar 25, 2021

Awesome course. Lots of practical use of analyzing big data with SQL. Thanks Ian for teaching the course. Highly recommend this course if you would like to improve/refresh your SQL skills.

由 ES 提供Nov 23, 2020

Great overview of SQL. Some decent hands-on and well thought-of quiz questions. Recommended even for people who might know SQL somewhat, but never had a structured overview of it.

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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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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。

Analyzing Big Data with SQL