課程信息

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初級
完成時間大約為18 小時
英語(English)
字幕:英語(English)

您將學到的內容有

  • Understand the basics of SELECT statements

  • Understand how and why to filter results

  • Explore grouping and aggregation to answer analytic questions

  • Work with sorting and limiting results

您將獲得的技能

Apache HiveApache ImpalaData AnalysisBig 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18 小時
英語(English)
字幕:英語(English)

講師

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 SQL on Big Data

完成時間為 3 小時
9 個視頻 (總計 47 分鐘), 5 個閱讀材料, 2 個測驗
9 個視頻
Review and Preparation4分鐘
Using the Hue Query Editors7分鐘
Running SQL Utility Statements6分鐘
Running SQL SELECT Statements5分鐘
Understanding Different SQL Interfaces4分鐘
Overview of Beeline and Impala Shell2分鐘
Using Beeline8分鐘
Using Impala Shell3分鐘
5 個閱讀材料
Instructions for Downloading and Installing the Exercise Environment30分鐘
Troubleshooting the VM5分鐘
(Optional) What about Spark SQL?10分鐘
Expectations for Learners10分鐘
(Optional) Using Other SQL Engines10分鐘
2 個練習
Week 1 Core Quiz30分鐘
Week 1 Honors Quiz5分鐘
2

2

完成時間為 3 小時

SQL SELECT Essentials

完成時間為 3 小時
16 個視頻 (總計 83 分鐘), 4 個閱讀材料, 2 個測驗
16 個視頻
SQL SELECT Building Blocks2分鐘
Introduction to the SELECT List7分鐘
Expressions and Operators7分鐘
Data Types6分鐘
Column Aliases5分鐘
Built-In Functions7分鐘
Data Type Conversion5分鐘
The DISTINCT Keyword5分鐘
Introduction to the FROM Clause3分鐘
Identifiers7分鐘
Formatting SELECT Statements4分鐘
Using Beeline in Non-Interactive Mode5分鐘
Using Impala Shell in Non-Interactive Mode4分鐘
Formatting the Output of Beeline and Impala Shell4分鐘
Saving Hive and Impala Query Results to a File5分鐘
4 個閱讀材料
Order of Operations5分鐘
Division and Modulo Operators15分鐘
Common String Functions15分鐘
Case (In)Sensitivity in SQL10分鐘
2 個練習
Week 2 Core Quiz30分鐘
Week 2 Honors Quiz5分鐘
3

3

完成時間為 3 小時

Filtering Data

完成時間為 3 小時
14 個視頻 (總計 85 分鐘), 6 個閱讀材料, 2 個測驗
14 個視頻
About the Datasets4分鐘
Introduction to the WHERE Clause2分鐘
Using Expressions in the WHERE Clause9分鐘
Comparison Operators9分鐘
Data Types and Precision4分鐘
Logical Operators7分鐘
Other Relational Operators4分鐘
Understanding Missing Values8分鐘
Handling Missing Values6分鐘
Conditional Functions9分鐘
Using Variables with Beeline and Impala Shell7分鐘
Calling Beeline and Impala Shell from Scripts6分鐘
Querying Hive and Impala in Scripts and Applications2分鐘
6 個閱讀材料
Data Reference5分鐘
(Optional) Unicode Characters10分鐘
Working with Literal Strings15分鐘
Missing Values with Logical Operators10分鐘
Missing Values in String Columns5分鐘
(Optional Exercise) Change VM Desktop Color30分鐘
2 個練習
Week 3 Core Quiz30分鐘
Week 3 Honors Quiz5分鐘
4

4

完成時間為 3 小時

Grouping and Aggregating Data

完成時間為 3 小時
15 個視頻 (總計 82 分鐘), 6 個閱讀材料, 2 個測驗
15 個視頻
Introduction to Aggregation2分鐘
Common Aggregate Functions2分鐘
Using Aggregate Functions in the SELECT Statement8分鐘
Introduction to the GROUP BY Clause6分鐘
Choosing an Aggregate Function and Grouping Column4分鐘
Grouping Expressions6分鐘
Grouping and Aggregation, Together and Separately5分鐘
NULL Values in Grouping and Aggregation4分鐘
The COUNT Function7分鐘
Tips for Applying Grouping and Aggregation7分鐘
Filtering on Aggregates2分鐘
The HAVING Clause8分鐘
Understanding Hive and Impala Version Differences10分鐘
Understanding Hue Version Differences2分鐘
6 個閱讀材料
COUNT(*) and SUM(1)5分鐘
Interpreting Aggregates: Populations and Samples10分鐘
The least and greatest Functions5分鐘
Why Aggregate Expressions Ignore NULL Values5分鐘
(Optional) Shortcuts for Grouping10分鐘
How Grouping and Aggregation Can Mislead10分鐘
2 個練習
Week 4 Core Quiz30分鐘
Week 4 Honors Quiz10分鐘

審閱

來自ANALYZING BIG DATA WITH SQL的熱門評論

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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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