In this course, you'll get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Modern Big Data Analysis with SQL
Analyzing Big Data with SQL
von
Über diesen Kurs
43,029 kürzliche Aufrufe
Was Sie lernen werden
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
Kompetenzen, die Sie erwerben
Apache HiveApache ImpalaData AnalysisBig DataSQL
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 2 von 3 in
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 28 Stunden zum Abschließen
Empfohlen: 9 hours/week
Englisch
Untertitel: Englisch
Lehrplan - Was Sie in diesem Kurs lernen werden
3 Stunden zum Abschließen
Orientation to SQL on Big Data
3 Stunden zum Abschließen
9 Videos (Gesamt 47 min), 5 Lektüren, 2 Quiz
9 Videos
Review and Preparation4m
Using the Hue Query Editors7m
Running SQL Utility Statements6m
Running SQL SELECT Statements5m
Understanding Different SQL Interfaces4m
Overview of Beeline and Impala Shell2m
Using Beeline8m
Using Impala Shell3m
5 Lektüren
Instructions for Downloading and Installing the Exercise Environment30m
Troubleshooting the VM5m
(Optional) What about Spark SQL?10m
Expectations for Learners10m
(Optional) Using Other SQL Engines10m
2 praktische Übungen
Week 1 Core Quiz30m
Week 1 Honors Quiz5m
3 Stunden zum Abschließen
SQL SELECT Essentials
3 Stunden zum Abschließen
16 Videos (Gesamt 83 min), 4 Lektüren, 2 Quiz
16 Videos
SQL SELECT Building Blocks2m
Introduction to the SELECT List7m
Expressions and Operators7m
Data Types6m
Column Aliases5m
Built-In Functions7m
Data Type Conversion5m
The DISTINCT Keyword5m
Introduction to the FROM Clause3m
Identifiers7m
Formatting SELECT Statements4m
Using Beeline in Non-Interactive Mode5m
Using Impala Shell in Non-Interactive Mode4m
Formatting the Output of Beeline and Impala Shell4m
Saving Hive and Impala Query Results to a File5m
4 Lektüren
Order of Operations5m
Division and Modulo Operators15m
Common String Functions15m
Case (In)Sensitivity in SQL10m
2 praktische Übungen
Week 2 Core Quiz30m
Week 2 Honors Quiz5m
3 Stunden zum Abschließen
Filtering Data
3 Stunden zum Abschließen
14 Videos (Gesamt 85 min), 6 Lektüren, 2 Quiz
14 Videos
About the Datasets4m
Introduction to the WHERE Clause2m
Using Expressions in the WHERE Clause9m
Comparison Operators9m
Data Types and Precision4m
Logical Operators7m
Other Relational Operators4m
Understanding Missing Values8m
Handling Missing Values6m
Conditional Functions9m
Using Variables with Beeline and Impala Shell7m
Calling Beeline and Impala Shell from Scripts6m
Querying Hive and Impala in Scripts and Applications2m
6 Lektüren
Data Reference5m
(Optional) Unicode Characters10m
Working with Literal Strings15m
Missing Values with Logical Operators10m
Missing Values in String Columns5m
(Optional Exercise) Change VM Desktop Color30m
2 praktische Übungen
Week 3 Core Quiz30m
Week 3 Honors Quiz5m
3 Stunden zum Abschließen
Grouping and Aggregating Data
3 Stunden zum Abschließen
15 Videos (Gesamt 82 min), 6 Lektüren, 2 Quiz
15 Videos
Introduction to Aggregation2m
Common Aggregate Functions2m
Using Aggregate Functions in the SELECT Statement8m
Introduction to the GROUP BY Clause6m
Choosing an Aggregate Function and Grouping Column4m
Grouping Expressions6m
Grouping and Aggregation, Together and Separately5m
NULL Values in Grouping and Aggregation4m
The COUNT Function7m
Tips for Applying Grouping and Aggregation7m
Filtering on Aggregates2m
The HAVING Clause8m
Understanding Hive and Impala Version Differences10m
Understanding Hue Version Differences2m
6 Lektüren
COUNT(*) and SUM(1)5m
Interpreting Aggregates: Populations and Samples10m
The least and greatest Functions5m
Why Aggregate Expressions Ignore NULL Values5m
(Optional) Shortcuts for Grouping10m
How Grouping and Aggregation Can Mislead10m
2 praktische Übungen
Week 4 Core Quiz30m
Week 4 Honors Quiz10m
Bewertungen
Top-Bewertungen von ANALYZING BIG DATA WITH SQL
von RJOct 25, 2019
Good course to understand the need of SQL in data analysis/big data using good examples and real life data and problem sets.
von TPOct 8, 2019
I have used many platforms to get started with SQL but this has been the best by far. Thank you Cloudera.
von YNMar 26, 2020
A great course to go over the basic SQL. However, this course doesn't go cover Subquery concept :(
von HANov 9, 2019
One of the best course I learned so far on SQL. Comprehensive and Clear in all Terms
von VSMar 25, 2020
Great Course to learn SQL language, and you also get to learn Impala and Hive.
von JSFeb 14, 2020
Excellent course on Hive and Impala SQL engines for big data!
von
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.
Über den Spezialisierung Modern Big Data Analysis with SQL
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.
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Sobald Sie sich für ein Zertifikat angemeldet haben, haben Sie Zugriff auf alle Videos, Quizspiele und Programmieraufgaben (falls zutreffend). Aufgaben, die von anderen Kursteilnehmern bewertet werden, können erst dann eingereicht und überprüft werden, wenn Ihr Unterricht begonnen hat. Wenn Sie sich den Kurs anschauen möchten, ohne ihn zu kaufen, können Sie womöglich auf bestimmte Aufgaben nicht zugreifen.
Was bekomme ich, wenn ich diese Spezialisierung abonniere?
Wenn Sie sich für den Kurs anmelden, erhalten Sie Zugriff auf alle Kurse der Spezialisierung und Sie erhalten nach Abschluss aller Arbeiten ein Zertifikat. Ihr elektronisches Zertifikat wird zu Ihrer Seite „Errungenschaften“ hinzugefügt – von dort können Sie Ihr Zertifikat ausdrucken oder es zu Ihrem LinkedIn Profil hinzufügen. Wenn Sie nur lesen und den Inhalt des Kurses anzeigen möchten, können Sie kostenlos als Gast an dem Kurs teilnehmen.
Wie erfolgen Rückerstattungen?
Ist finanzielle Unterstützung möglich?
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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