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.
Этот курс входит в специализацию ''Специализация Modern Big Data Analysis with SQL'
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Курс 3 из 3 в программе
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Начальный уровень
Прибл. 20 часов на выполнение
Английский
Субтитры: Английский
Чему вы научитесь
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
Приобретаемые навыки
Data ManagementDistributed File SystemsCloud StorageBig DataSQL
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 3 из 3 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Начальный уровень
Прибл. 20 часов на выполнение
Английский
Субтитры: Английский
от партнера
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.
Программа курса: что вы изучите
3 ч. на завершение
Orientation to Data in Clusters and Cloud Storage
3 ч. на завершение
7 видео ((всего 56 мин.)), 3 материалов для самостоятельного изучения, 1 тест
7 видео
Browsing Tables with Hue7мин
Browsing Tables with SQL Utility Statements6мин
Browsing HDFS with the Hue File Browser13мин
Browsing HDFS from the Command Line9мин
Understanding S3 and Other Cloud Storage Platforms6мин
Browsing S3 Buckets from the Command Line8мин
3 материала для самостоятельного изучения
Review and Preparation30мин
Instructions for Downloading and Installing the Exercise Environment30мин
Troubleshooting the VM5мин
1 практическое упражнение
Week 1 Graded Quiz30мин
5 ч. на завершение
Defining Databases, Tables, and Columns
5 ч. на завершение
7 видео ((всего 33 мин.)), 12 материалов для самостоятельного изучения, 2 тестов
7 видео
Introduction to the CREATE TABLE Statement5мин
Using Different Schemas on the Same Data12мин
Specifying TBLPROPERTIES2мин
Examining, Modifying, and Removing Tables1мин
Hive and Impala Interoperability2мин
Impala Metadata Refresh3мин
12 материалов для самостоятельного изучения
Creating Databases and Tables with Hue30мин
Creating Databases and Tables with SQL15мин
Permissions to Create Databases and Tables5мин
The ROW FORMAT Clause25мин
The STORED AS Clause15мин
The LOCATION Clause20мин
CREATE TABLE Shortcuts10мин
Using Hive SerDes15мин
Working with Unstructured and Semi-Structured Data15мин
Examining Table Structure10мин
Dropping Databases and Tables5мин
Modifying Existing Tables35мин
2 практических упражнения
Week 2 Practice Quiz20мин
Week 2 Graded Quiz30мин
3 ч. на завершение
Data Types and File Types
3 ч. на завершение
5 видео ((всего 14 мин.)), 12 материалов для самостоятельного изучения, 2 тестов
5 видео
Overview of Data Types1мин
Choosing the Right Data Types4мин
Overview of File Types3мин
Choosing the Right File Types3мин
12 материалов для самостоятельного изучения
Integer Data Types5мин
Decimal Data Types10мин
Character String Data Types10мин
Other Data Types5мин
Examining Data Types10мин
Out-of-Range Values5мин
Text Files5мин
Avro Files5мин
Parquet Files5мин
ORC Files5мин
Other File Types5мин
Creating Tables with Avro and Parquet Files20мин
2 практических упражнения
Week 3 Practice Quiz20мин
Week 3 Graded Quiz30мин
5 ч. на завершение
Managing Datasets in Clusters and Cloud Storage
5 ч. на завершение
8 видео ((всего 48 мин.)), 13 материалов для самостоятельного изучения, 3 тестов
8 видео
Refresh Impala's Metadata Cache after Loading Data2мин
Loading Files into HDFS with Hue's Table Browser10мин
Loading Files into HDFS with Hue's File Browser6мин
Loading Files into HDFS from the Command Line8мин
Loading Files into S3 from the Command Line10мин
Using Hive and Impala to Load Data into Tables3мин
Conclusion2мин
13 материалов для самостоятельного изучения
More about HDFS Shell Commands10мин
Chaining and Scripting with HDFS Commands5мин
HDFS Permissions5мин
Other Ways to Load Files into S35мин
S3 Permissions10мин
Missing Values15мин
Character Sets5мин
Using Sqoop to Import Data15мин
More Sqoop Import Options5мин
Using Sqoop to Export Data5мин
SQL LOAD DATA Statements10мин
SQL INSERT Statements10мин
SQL INSERT ... SELECT and CTAS Statements15мин
2 практических упражнения
Week 4 Practice Quiz20мин
Week 4 Graded Quiz30мин
Рецензии
Лучшие отзывы о курсе MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE
от партнера SY29 февр. 2020 г.
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 ,
от партнера AM15 дек. 2019 г.
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.
от партнера MA13 апр. 2020 г.
This is one of the systematic specializations which makes the harder and otherwise overwhelming subject so easy to navigate, follow and learn.
от партнера AZ3 мая 2020 г.
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.
Специализация Modern Big Data Analysis with SQL: общие сведения
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.
Часто задаваемые вопросы
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.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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)
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