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所在平台: Udemy |
课程主页: https://www.udemy.com/course/duckdb-ultimate-guide/
课程评论：没有评论
课程名称：DuckDB - 终极指南 课程概述：在过去两年中，DuckDB的搜索量增长了1200%，它的受欢迎程度正在急速上升。与Apache Hadoop和Spark等庞大的大数据基础设施相比，DuckDB是处理数据问题的一个极佳解决方案。DuckDB类似于PostgreSQL，具备强大的分析能力，可以在本地轻松运行，并且完全免费，支持多种集成方式，如DuckDB Python、duckdb dbt、duckdb Streamlit、duckdb s3、wasm与Docker等，几乎可以实现各种需求。此外，DuckDB支持数据导出（如duckdb csv、duckdb parquet、duckdb json），方便分享分析结果。Python集成非常简单，只需“pip install duckdb”即可开始使用。 课程将深入探讨DuckDB与Python的集成。相较于每位开发者都需要一个PostgreSQL或MariaDB实例，DuckDB可以通过设置生成内存中的实例，使用起来更加方便。DuckDB Httpfs包的学习将帮助获取互联网数据。DuckDB适合在本地进行大数据的列式数据库分析，胜于PySpark。课程还将展示DuckDB Pivot如何帮助创建类似电子表格的表格。 DuckDB学习曲线平滑，适合在SQLite基础上进阶，特别是在处理有限列的聚合查询时表现出色。课程将比较DuckDB与SQLite及Clickhouse的异同。与Pandas不同，DuckDB可以处理超出内存的更大数据集，并利用所有CPU核心，实现300%以上的性能提升。 在课程结束后，学员将学习如何架构和实现以DuckDB为数据库的分析解决方案，理解DuckDB的高速原理，掌握DuckDB与其他数据库的区别，以及如何在Python环境和命令行环境中使用DuckDB。此外，还将学习如何将DuckDB作为Streamlit Python分析应用的后端数据库，并组合使用DuckDB和dbt以简化数据仓库的开发。课程涵盖如何在MotherDuck（DuckDB的云原生环境）中工作，以及在Docker环境中与DuckDB交互，并了解DuckDB在分析服务微服务架构中的角色。 课程内容包括：视频讲座（带互动注释）、练习案例大纲PDF、演示资源、完整的实践项目代码库、终生访问以及未来更新、课程完成证书和30天退款保证。课程不是静态的，将根据学生反馈持续改进，并计划于2024年提供多项更新课程内容。 课程将使学生全面掌握DuckDB这一新兴技术，为数据分析领域的工作提供强大支持。
Why should I learn DuckDB?+ 1200% of searches in the last 2 yearsIts popularity is growing RAPIDLY!Data lakes and bulky Big Data Infrastructure (like Apache Hadoop & Spark) are not optimal solution to every Data problemDuckDB is an awesome solution for running a database very similar to PostgreSQL, but with HUGE Analytical Capabilities, locally without any fuss100% free & supports dozens of various integrationsduckdb Python, duckdb dbt, duckdb Streamlit, duckdb s3 & wasm & Docker + many more: you can almost anything with it. Additionally, you can easily do data exports: duckdb csv, duckdb parquet, duckdb json are all ways to share your analysis results in no time! Python integration is as easy as doing "pip install duckdb" & you're ready to go! We will dive deep into duckdb Python integration in one of the cases.Ease of useRather than having a PostgreSQL/Mariadb for each developer on the team, you can setup configuration to spawn an in memory instance of DuckDB. If you need to fetch data from the Internet, it's no problem either: Duckdb Httpfs is a package that we'll also study.Local Analysis of BigDataIf you want to run a columnar database locally on pretty big data, there isn't really anything else like it. You could instead run PySpark locally but that would be much more of a headache. Duckdb Pivot can even help you create Spreadsheet-like tables.Easy to learn after SQLiteIt's a step forward to Analytics field from SQLite. DuckDB performs great when running aggregate queries on limited columns whereas SQLite works great when fetching one or more rows using filters. In the Course we will compare and contrast duckdb vs Sqlite and duckdb vs Clickhouse.300%+ faster than PandasPandas loads all data into memory and runs on a single thread. Hence it can't operate on larger than memory datasets and also doesn't use all of your CPU cores. Whereas DuckDB can operate on datasets larger than memory. Moreover, it can distribute load across all the CPU cores. All that using SQL language by default!This Course is not just a duckdb tutorial: it's a packaged solution to master this new & rapidly growing technology.Expected OutcomesAfter this Course:You will learn how to Architect & Implement Analytics Solutions that use duck db as the databaseYou will learn the underlying principles that make DuckDB so fast on any machine (Theory)You will understand how DuckDB is different from other data bases: both Analytical (Clickhouse, Redshift, Cassandra) and OLTP (PostgreSQL, SQLite)You will learn to work with DuckDB from Python environment (Practice)You will learn to work with DuckDB from CLI (command line) environment (Practice)Use DuckDB as a backend database for your Streamlit Python Analytics Apps (Practice)Use a DuckDB dbt (Data Build Tool) combo to streamline Analytics Data Warehouse development (Practice)You will learn to work in MotherDuck: a Cloud-native environment (SaaS) for duck db (Practice). You can think of it as DuckDB GUI that you might miss in CLILearn to interact with DuckDB inside Docker environmentUnderstand how DuckDB fits into Micro-service architecture of Analytical servicesUse Rill: a DuckDB-powered BI-as-Code "last-mile ETL" platform for blazing fast DashboardingWhat's insideVideo lectures (with interactive annotations)PDFs with Practice Cases OutlinesDemo ResourcesFully packaged code base for Practice ProjectsFull lifetime access with all future updatesCertificate of course completion30-Day Money-Back GuaranteeThe course isn't static! I collect students' feedback and work on improving it[Course Updates]:01.2024: + Bonus Section: Let's build a DuckDB-powered Recommender Micro-service02.2024: + "Rill Data" Section: DuckDB-powered BI-as-Code "last-mile ETL" platform05.2024: + Updates in MotherDuck section: explore new AI-powered features in the platform06.2024: + "DuckDB in Data Pipelines" Section: use case to learn how DuckDB can play the "data transformer" roleDigital assets used:-Image from freepik with free licence from freepik dot com "Free vector gradient dynamic blue lines background"
