课程信息

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初级
完成时间大约为20 小时
英语(English)
字幕:英语(English)

您将学到的内容有

  • 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

您将获得的技能

Data ManagementDistributed File SystemsCloud StorageBig DataSQL
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。
可灵活调整截止日期
根据您的日程表重置截止日期。
初级
完成时间大约为20 小时
英语(English)
字幕:英语(English)

提供方

Cloudera 徽标

Cloudera

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 3 小时

Orientation to Data in Clusters and Cloud Storage

完成时间为 3 小时
7 个视频 (总计 56 分钟), 3 个阅读材料, 1 个测验
7 个视频
Browsing Tables with Hue7分钟
Browsing Tables with SQL Utility Statements6分钟
Browsing HDFS with the Hue File Browser13分钟
Browsing HDFS from the Command Line9分钟
Understanding S3 and Other Cloud Storage Platforms6分钟
Browsing S3 Buckets from the Command Line8分钟
3 个阅读材料
Review and Preparation30分钟
Instructions for Downloading and Installing the Exercise Environment30分钟
Troubleshooting the VM5分钟
1 个练习
Week 1 Graded Quiz30分钟
2

2

完成时间为 5 小时

Defining Databases, Tables, and Columns

完成时间为 5 小时
7 个视频 (总计 33 分钟), 12 个阅读材料, 2 个测验
7 个视频
Introduction to the CREATE TABLE Statement5分钟
Using Different Schemas on the Same Data12分钟
Specifying TBLPROPERTIES2分钟
Examining, Modifying, and Removing Tables1分钟
Hive and Impala Interoperability2分钟
Impala Metadata Refresh3分钟
12 个阅读材料
Creating Databases and Tables with Hue30分钟
Creating Databases and Tables with SQL15分钟
Permissions to Create Databases and Tables5分钟
The ROW FORMAT Clause25分钟
The STORED AS Clause15分钟
The LOCATION Clause20分钟
CREATE TABLE Shortcuts10分钟
Using Hive SerDes15分钟
Working with Unstructured and Semi-Structured Data15分钟
Examining Table Structure10分钟
Dropping Databases and Tables5分钟
Modifying Existing Tables35分钟
2 个练习
Week 2 Practice Quiz20分钟
Week 2 Graded Quiz30分钟
3

3

完成时间为 3 小时

Data Types and File Types

完成时间为 3 小时
5 个视频 (总计 14 分钟), 12 个阅读材料, 2 个测验
5 个视频
Overview of Data Types1分钟
Choosing the Right Data Types4分钟
Overview of File Types3分钟
Choosing the Right File Types3分钟
12 个阅读材料
Integer Data Types5分钟
Decimal Data Types10分钟
Character String Data Types10分钟
Other Data Types5分钟
Examining Data Types10分钟
Out-of-Range Values5分钟
Text Files5分钟
Avro Files5分钟
Parquet Files5分钟
ORC Files5分钟
Other File Types5分钟
Creating Tables with Avro and Parquet Files20分钟
2 个练习
Week 3 Practice Quiz20分钟
Week 3 Graded Quiz30分钟
4

4

完成时间为 5 小时

Managing Datasets in Clusters and Cloud Storage

完成时间为 5 小时
8 个视频 (总计 48 分钟), 13 个阅读材料, 3 个测验
8 个视频
Refresh Impala's Metadata Cache after Loading Data2分钟
Loading Files into HDFS with Hue's Table Browser10分钟
Loading Files into HDFS with Hue's File Browser6分钟
Loading Files into HDFS from the Command Line8分钟
Loading Files into S3 from the Command Line10分钟
Using Hive and Impala to Load Data into Tables3分钟
Conclusion2分钟
13 个阅读材料
More about HDFS Shell Commands10分钟
Chaining and Scripting with HDFS Commands5分钟
HDFS Permissions5分钟
Other Ways to Load Files into S35分钟
S3 Permissions10分钟
Missing Values15分钟
Character Sets5分钟
Using Sqoop to Import Data15分钟
More Sqoop Import Options5分钟
Using Sqoop to Export Data5分钟
SQL LOAD DATA Statements10分钟
SQL INSERT Statements10分钟
SQL INSERT ... SELECT and CTAS Statements15分钟
2 个练习
Week 4 Practice Quiz20分钟
Week 4 Graded Quiz30分钟

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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....
Modern Big Data Analysis with SQL

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