This course is all about big data. It’s for students with SQL experience that want to take the next step on their data journey by learning distributed computing using Apache Spark. Students will gain a thorough understanding of this open-source standard for working with large datasets. Students will gain an understanding of the fundamentals of data analysis using SQL on Spark, setting the foundation for how to combine data with advanced analytics at scale and in production environments. The four modules build on one another and by the end of the course you will understand: the Spark architecture, queries within Spark, common ways to optimize Spark SQL, and how to build reliable data pipelines.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Learn SQL Basics for Data Science
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Spezialisierung Learn SQL Basics for Data ScienceUniversity of California, DavisÃœber diesen Kurs
47.327 kürzliche Aufrufe
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100Â % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 3 von 4 in
Stufe „Mittel“
Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch, Spanisch
Was Sie lernen werden
U​se the collaborative Databricks workspace to write scalable Spark SQL code that executes against a cluster of machines
Inspect the Spark UI to analyze query performance and identify bottlenecks
Create an end-to-end pipeline that reads data, transforms it, and saves the result
B​uild a medallion (bronze, silver, gold) lakehouse architecture with Delta Lake to ensure the reliability, scalability, and performance of your data
Kompetenzen, die Sie erwerben
- Data Science
- Apache Spark
- Delta Lake
- SQL
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100Â % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 3 von 4 in
Stufe „Mittel“
Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch, Spanisch
von
University of California, Davis
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
Lehrplan - Was Sie in diesem Kurs lernen werden
3 Stunden zum Abschließen
Introduction to Spark
In this module, you will be able to discuss the core concepts of distributed computing and be able to recognize when and where to apply them. You'll be able to identify the basic data structure of Apache Sparkâ„¢, known as a DataFrame. Additionally, you will use the collaborative Databricks workspace and write SQL code that executes against a cluster of machines.
3 Stunden zum Abschließen
6 Videos (Gesamt 43 min), 3 Lektüren, 2 Quiz
3 Stunden zum Abschließen
Spark Core Concepts
In this module, you will be able to explain the core concepts of Spark. You will learn common ways to increase query performance by caching data and modifying Spark configurations. You will also use the Spark UI to analyze performance and identify bottlenecks, as well as optimize queries with Adaptive Query Execution.
3 Stunden zum Abschließen
6 Videos (Gesamt 36 min), 2 Lektüren, 2 Quiz
4 Stunden zum Abschließen
Engineering Data Pipelines
In this module, you will be able to identify and discuss the general demands of data applications. You'll be able to access data in a variety of formats and compare and contrast the tradeoffs between these formats. You will explore and examine semi-structured JSON data (common in big data environments) as well as schemas and parallel data writes. You will be able to create an end-to-end pipeline that reads data, transforms it, and saves the result.
4 Stunden zum Abschließen
7 Videos (Gesamt 62 min), 2 Lektüren, 2 Quiz
4 Stunden zum Abschließen
Data Lakes, Warehouses and Lakehouses
In this module, you will identify the key characteristics of data lakes, data warehouses, and lakehouses. Lakehouses combine the scalability and low-cost storage of data lakes with the speed and ACID transactional guarantees of data warehouses. You will build a production grade lakehouse by combining Spark with the open-source project, Delta Lake. Whoever said time travel isn't possible hasn't been to a lakehouse!
4 Stunden zum Abschließen
8 Videos (Gesamt 52 min), 2 Lektüren, 3 Quiz
Bewertungen
- 5 stars65,42Â %
- 4 stars23,77Â %
- 3 stars6,87Â %
- 2 stars1,76Â %
- 1 star2,16Â %
Top-Bewertungen von DISTRIBUTED COMPUTING WITH SPARK SQL
von D11. Feb. 2020
This has been an amazing course. What is worth mentioning is how the content was delivered. Nice hands on. Highly recommended for anyone who is new to Spark
von OD25. März 2020
Great course, really well taught and delivered. Only thing I would say is you would really need knowledge of python to really understand this course 100%
von KS13. Mai 2020
Amazing course that really cuts through the fundamentals of using distributed computing power to analyze and manipulate data. Well organised structure on fundamentals
von SJ19. Aug. 2020
Great course to learn more in depth about Apache Spark. Good instructors and course content. Thanks UC Davis and Coursera!
Ãœber den Spezialisierung Learn SQL Basics for Data Science
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, Delta Lake and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.
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