本課程是 Modern Big Data Analysis with SQL 專項課程專項課程的一部分

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241 個評分

Ian Cook 另外 +1 位授課教師
頂尖授課教師

9,159 人已註冊

提供方

Modern Big Data Analysis with SQL 專項課程Cloudera

課程信息

14,527 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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完成後獲得證書

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第 3 門課程（共 3 門）

Modern Big Data Analysis with SQL 專項課程

初級

完成時間大約為21 小時

英語（English）

字幕：阿拉伯語（Arabic）, 法語（French）, （歐洲人講的）葡萄牙語, 意大利語, 越南語, 德語（German）, 俄語（Russian）, 英語（English）, 西班牙語（Spanish）

您將學到的內容有

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

您將獲得的技能

Data Management
Distributed File Systems
Cloud Storage
Big Data
SQL

可靈活調整截止日期

根據您的日程表重置截止日期。

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

第 3 門課程（共 3 門）

Modern Big Data Analysis with SQL 專項課程

初級

完成時間大約為21 小時

英語（English）

授課教師

授課教師評分

4.88/5 （44 個評分）

Ian Cook
頂尖授課教師

Staff Curriculum Developer

Cloudera

22,292 個學生

2 門課程

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.

授課大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 3 小時

Orientation to Data in Clusters and Cloud Storage

完成時間為 3 小時

7 個視頻（總計 56 分鐘）, 3 個閱讀材料, 1 個測驗

7 個視頻

Welcome to the Course4分鐘

Browsing Tables with Hue7分鐘

Browsing Tables with SQL Utility Statements6分鐘

Browsing HDFS with the Hue File Browser13分鐘

Browsing HDFS from the Command Line9分鐘

Understanding S3 and Other Cloud Storage Platforms6分鐘

Browsing S3 Buckets from the Command Line8分鐘

3 個閱讀材料

Review and Preparation30分鐘

Instructions for Downloading and Installing the Exercise Environment30分鐘

Troubleshooting the VM5分鐘

1 個練習

Week 1 Graded Quiz30分鐘

週

週 2

完成時間為 5 小時

Defining Databases, Tables, and Columns

完成時間為 5 小時

7 個視頻（總計 33 分鐘）, 12 個閱讀材料, 2 個測驗

7 個視頻

Week 2 Introduction3分鐘

Introduction to the CREATE TABLE Statement5分鐘

Using Different Schemas on the Same Data12分鐘

Specifying TBLPROPERTIES2分鐘

Examining, Modifying, and Removing Tables1分鐘

Hive and Impala Interoperability2分鐘

Impala Metadata Refresh3分鐘

12 個閱讀材料

Creating Databases and Tables with Hue30分鐘

Creating Databases and Tables with SQL15分鐘

Permissions to Create Databases and Tables5分鐘

The ROW FORMAT Clause25分鐘

The STORED AS Clause15分鐘

The LOCATION Clause20分鐘

CREATE TABLE Shortcuts10分鐘

Using Hive SerDes15分鐘

Working with Unstructured and Semi-Structured Data15分鐘

Examining Table Structure10分鐘

Dropping Databases and Tables5分鐘

Modifying Existing Tables35分鐘

2 個練習

Week 2 Practice Quiz30分鐘

Week 2 Graded Quiz30分鐘

週

週 3

完成時間為 3 小時

Data Types and File Types

完成時間為 3 小時

5 個視頻（總計 14 分鐘）, 12 個閱讀材料, 2 個測驗

5 個視頻

Week 3 Introduction1分鐘

Overview of Data Types1分鐘

Choosing the Right Data Types4分鐘

Overview of File Types3分鐘

Choosing the Right File Types3分鐘

12 個閱讀材料

Integer Data Types5分鐘

Decimal Data Types10分鐘

Character String Data Types10分鐘

Other Data Types5分鐘

Examining Data Types10分鐘

Out-of-Range Values5分鐘

Text Files5分鐘

Avro Files5分鐘

Parquet Files5分鐘

ORC Files5分鐘

Other File Types5分鐘

Creating Tables with Avro and Parquet Files20分鐘

2 個練習

Week 3 Practice Quiz20分鐘

Week 3 Graded Quiz30分鐘

週

週 4

完成時間為 5 小時

Managing Datasets in Clusters and Cloud Storage

完成時間為 5 小時

8 個視頻（總計 48 分鐘）, 13 個閱讀材料, 3 個測驗

8 個視頻

Week 4 Introduction3分鐘

Refresh Impala's Metadata Cache after Loading Data2分鐘

Loading Files into HDFS with Hue's Table Browser10分鐘

Loading Files into HDFS with Hue's File Browser6分鐘

Loading Files into HDFS from the Command Line8分鐘

Loading Files into S3 from the Command Line10分鐘

Using Hive and Impala to Load Data into Tables3分鐘

Conclusion2分鐘

13 個閱讀材料

More about HDFS Shell Commands10分鐘

Chaining and Scripting with HDFS Commands5分鐘

HDFS Permissions5分鐘

Other Ways to Load Files into S35分鐘

S3 Permissions10分鐘

Missing Values15分鐘

Character Sets5分鐘

Using Sqoop to Import Data15分鐘

More Sqoop Import Options5分鐘

Using Sqoop to Export Data5分鐘

SQL LOAD DATA Statements10分鐘

SQL INSERT Statements10分鐘

SQL INSERT ... SELECT and CTAS Statements15分鐘

2 個練習

Week 4 Practice Quiz30分鐘

Week 4 Graded Quiz30分鐘

審閱

4.7

55 條評論

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2 stars
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1 star
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來自MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE的熱門評論

由 PZ 提供2020年9月3日

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2020年2月29日

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2019年12月15日

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 AZ 提供2020年5月3日

Although more reading than video, I found readings to be more convenient when you need to get back to a particular lesson and recap something.

查看所有評論

關於 Modern Big Data Analysis with SQL 專項課程

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。
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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。
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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)

還有其他問題嗎？請訪問學生幫助中心。

Managing Big Data in Clusters and Cloud Storage