課程信息

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初級
完成時間大約為20 小時
英語(English)
字幕:英語(English)

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 ManagementDistributed File SystemsCloud StorageBig DataSQL
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。
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為20 小時
英語(English)
字幕:英語(English)

提供方

Cloudera 徽標

Cloudera

教學大綱 - 您將從這門課程中學到什麼

1

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
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
2

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
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 Quiz20分鐘
Week 2 Graded Quiz30分鐘
3

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
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
4

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
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 Quiz20分鐘
Week 4 Graded Quiz30分鐘

審閱

來自MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE的熱門評論

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....
Modern Big Data Analysis with SQL

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