Об этом курсе

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Гибкие сроки
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Начальный уровень
Прибл. 20 часов на выполнение
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.
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Начальный уровень
Прибл. 20 часов на выполнение
Субтитры: Английский

от партнера

Логотип Cloudera


Программа курса: что вы изучите


Неделя 1

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

Неделя 2

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

Неделя 3

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

Неделя 4

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
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



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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....
Modern Big Data Analysis with SQL

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