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.
This course is part of the Modern Big Data Analysis with SQL Specialization
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About this Course
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Course 3 of 3 in the
Flexible deadlines
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Beginner Level
Approx. 21 hours to complete
English
Subtitles: English
What you will learn
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
Skills you will gain
Data ManagementDistributed File SystemsCloud StorageBig DataSQL
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 3 of 3 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 21 hours to complete
English
Subtitles: English
Offered by
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.
Syllabus - What you will learn from this course
3 hours to complete
Orientation to Data in Clusters and Cloud Storage
3 hours to complete
7 videos (Total 56 min), 3 readings, 1 quiz
7 videos
Browsing Tables with Hue7m
Browsing Tables with SQL Utility Statements6m
Browsing HDFS with the Hue File Browser13m
Browsing HDFS from the Command Line9m
Understanding S3 and Other Cloud Storage Platforms6m
Browsing S3 Buckets from the Command Line8m
3 readings
Review and Preparation30m
Instructions for Downloading and Installing the Exercise Environment30m
Troubleshooting the VM5m
1 practice exercise
Week 1 Graded Quiz30m
5 hours to complete
Defining Databases, Tables, and Columns
5 hours to complete
7 videos (Total 33 min), 12 readings, 2 quizzes
7 videos
Introduction to the CREATE TABLE Statement5m
Using Different Schemas on the Same Data12m
Specifying TBLPROPERTIES2m
Examining, Modifying, and Removing Tables1m
Hive and Impala Interoperability2m
Impala Metadata Refresh3m
12 readings
Creating Databases and Tables with Hue30m
Creating Databases and Tables with SQL15m
Permissions to Create Databases and Tables5m
The ROW FORMAT Clause25m
The STORED AS Clause15m
The LOCATION Clause20m
CREATE TABLE Shortcuts10m
Using Hive SerDes15m
Working with Unstructured and Semi-Structured Data15m
Examining Table Structure10m
Dropping Databases and Tables5m
Modifying Existing Tables35m
2 practice exercises
Week 2 Practice Quiz30m
Week 2 Graded Quiz30m
3 hours to complete
Data Types and File Types
3 hours to complete
5 videos (Total 14 min), 12 readings, 2 quizzes
5 videos
Overview of Data Types1m
Choosing the Right Data Types4m
Overview of File Types3m
Choosing the Right File Types3m
12 readings
Integer Data Types5m
Decimal Data Types10m
Character String Data Types10m
Other Data Types5m
Examining Data Types10m
Out-of-Range Values5m
Text Files5m
Avro Files5m
Parquet Files5m
ORC Files5m
Other File Types5m
Creating Tables with Avro and Parquet Files20m
2 practice exercises
Week 3 Practice Quiz20m
Week 3 Graded Quiz30m
5 hours to complete
Managing Datasets in Clusters and Cloud Storage
5 hours to complete
8 videos (Total 48 min), 13 readings, 3 quizzes
8 videos
Refresh Impala's Metadata Cache after Loading Data2m
Loading Files into HDFS with Hue's Table Browser10m
Loading Files into HDFS with Hue's File Browser6m
Loading Files into HDFS from the Command Line8m
Loading Files into S3 from the Command Line10m
Using Hive and Impala to Load Data into Tables3m
Conclusion2m
13 readings
More about HDFS Shell Commands10m
Chaining and Scripting with HDFS Commands5m
HDFS Permissions5m
Other Ways to Load Files into S35m
S3 Permissions10m
Missing Values15m
Character Sets5m
Using Sqoop to Import Data15m
More Sqoop Import Options5m
Using Sqoop to Export Data5m
SQL LOAD DATA Statements10m
SQL INSERT Statements10m
SQL INSERT ... SELECT and CTAS Statements15m
2 practice exercises
Week 4 Practice Quiz30m
Week 4 Graded Quiz30m
Reviews
TOP REVIEWS FROM MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE
by PZSep 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.
by SYFeb 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 ,
by AMDec 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.
by MAApr 13, 2020
This is one of the systematic specializations which makes the harder and otherwise overwhelming subject so easy to navigate, follow and learn.
About the Modern Big Data Analysis with SQL Specialization
This Specialization teaches the essential skills for working with large-scale data using SQL.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
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. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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)
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.
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