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.
Este curso faz parte do Programa de cursos integrados Learn SQL Basics for Data Science
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oferecido por
Programa de cursos integrados Learn SQL Basics for Data ScienceUniversidade da Califórnia, DavisInformações sobre o curso
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Prazos flexÃveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
NÃvel intermediário
Aprox. 14 horas para completar
Inglês
Legendas: Inglês, Espanhol
O que você vai aprender
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
Habilidades que você terá
- Data Science
- Apache Spark
- Delta Lake
- SQL
Prazos flexÃveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
NÃvel intermediário
Aprox. 14 horas para completar
Inglês
Legendas: Inglês, Espanhol
oferecido por
Universidade da Califórnia, 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.
Programa - O que você aprenderá com este curso
3 horas para concluir
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 horas para concluir
6 vÃdeos (Total 43 mÃn.), 3 leituras, 2 testes
3 horas para concluir
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 horas para concluir
6 vÃdeos (Total 36 mÃn.), 2 leituras, 2 testes
4 horas para concluir
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 horas para concluir
7 vÃdeos (Total 62 mÃn.), 2 leituras, 2 testes
4 horas para concluir
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 horas para concluir
8 vÃdeos (Total 52 mÃn.), 2 leituras, 3 testes
Avaliações
- 5 stars65,69%
- 4 stars23,58%
- 3 stars6,82%
- 2 stars1,75%
- 1 star2,14%
Principais avaliações do DISTRIBUTED COMPUTING WITH SPARK SQL
por SK12 de jun de 2022
A good course to learn the fundamentals of databricks, distribtued computing, and spark unified analytics platform.
por JB5 de jan de 2020
Extremely informative for those who are seeking to learn the fundamentals for distributed computing using Spark SQL.
por IT22 de fev de 2020
Great introduction to Spark SQL and ML Flow. I love that they give extra resources if you want to learn more. It was a fun learning journey.
por KS13 de mai de 2020
Amazing course that really cuts through the fundamentals of using distributed computing power to analyze and manipulate data. Well organised structure on fundamentals
Sobre Programa de cursos integrados 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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