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.
Ce cours fait partie de la Spécialisation Learn SQL Basics for Data Science
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Spécialisation Learn SQL Basics for Data ScienceUniversité de Californie à DavisÀ propos de ce cours
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Certificat partageable
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100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 4 dans le
Niveau intermédiaire
Approx. 14 heures pour terminer
Anglais
Sous-titres : Anglais, Espagnol
Ce que vous allez apprendre
Use 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
Build a medallion (bronze, silver, gold) lakehouse architecture with Delta Lake to ensure the reliability, scalability, and performance of your data
Compétences que vous acquerrez
- Data Science
- Apache Spark
- Delta Lake
- SQL
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 4 dans le
Niveau intermédiaire
Approx. 14 heures pour terminer
Anglais
Sous-titres : Anglais, Espagnol
Offert par
Université de Californie à 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.
Programme de cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
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 Spark™, known as a DataFrame. Additionally, you will use the collaborative Databricks workspace and write SQL code that executes against a cluster of machines.
3 heures pour terminer
6 vidéos (Total 43 min), 3 lectures, 2 quiz
3 heures pour terminer
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 heures pour terminer
6 vidéos (Total 36 min), 2 lectures, 2 quiz
4 heures pour terminer
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 heures pour terminer
7 vidéos (Total 62 min), 2 lectures, 2 quiz
4 heures pour terminer
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 heures pour terminer
8 vidéos (Total 52 min), 2 lectures, 3 quiz
Avis
- 5 stars65,33 %
- 4 stars23,84 %
- 3 stars7,01 %
- 2 stars1,60 %
- 1 star2,20 %
Meilleurs avis pour DISTRIBUTED COMPUTING WITH SPARK SQL
par D11 févr. 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
par TM25 avr. 2020
The information was very beneficial, and the ability to use data bricks helped put into practice the information learned.
par AK12 févr. 2021
Good course. Maybe little more details on how Spark works, Spark architecture would make the story complete
par SK12 juin 2022
A good course to learn the fundamentals of databricks, distribtued computing, and spark unified analytics platform.
À propos du Spécialisation 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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