Oreilly – DuckDB in Action, Video Edition 2024-8

Description

DuckDB in Action Video Edition course. This course introduces you to the practical use of the DuckDB database. DuckDB is an advanced SQL database that allows you to analyze large data sets easily from your laptop. In this course, you’ll learn everything you need to know to get the most out of this great tool, keep your data safe on-premises, and reduce your costs in the cloud. From data entry to advanced data pipelines, you’ll learn everything you need to get the most out of DuckDB—all through practical examples.

What you will learn

• Read and process data from CSV, JSON and Parquet sources locally and remotely
• Write analytical SQL queries, including summaries, joint table expressions, window functions, special join types, and pivot tables
• DuckDB’s use of Python, both with SQL and its “relational” API, interacts with databases as well as dataframes.
• Prepare, retrieve and query large data sets
• Building a cloud data pipeline
• Extending DuckDB with custom capabilities

This course is suitable for people who

• They are familiar with Python and CLI tools.

DuckDB in Action Video Edition course specifications

• Publisher: Oreilly
• Instructor: Michael Hunger , Mark Needham, Michael Simons
• Training level: beginner
• Training duration: 7 hours and 40 minutes

Course headings

• Chapter 1. An introduction to DuckDB
• Chapter 1. Why should you care about DuckDB?
• Chapter 1. When should you use DuckDB?
• Chapter 1. When should you not use DuckDB?
• Chapter 1. Use cases
• Chapter 1. Where does DuckDB fit in?
• Chapter 1. Steps of the data processing flow
• Chapter 1. Summary
• Chapter 2. Getting started with DuckDB
• Chapter 2. Installing the DuckDB CLI
• Chapter 2. Using the DuckDB CLI
• Chapter 2. DuckDB’s extension system
• Chapter 2. Analyzing a CSV file with the DuckDB CLI
• Chapter 2. Summary
• Chapter 3. Executing SQL queries
• Chapter 3. Analyzing energy production
• Chapter 3. Data definition language queries
• Chapter 3. Data manipulation language queries
• Chapter 3. DuckDB-specific SQL extensions
• Chapter 3. Summary
• Chapter 4. Advanced aggregation and analysis of data
• Chapter 4. Summarizing data
• Chapter 4. On subqueries
• Chapter 4. Grouping sets
• Chapter 4. Window functions
• Chapter 4. Conditions and filtering outside the WHERE clause
• Chapter 4. The PIVOT statement
• Chapter 4. Using the ASOF JOIN
• Chapter 4. Using table functions
• Chapter 4. Using LATERAL joins
• Chapter 4. Summary
• Chapter 5. Exploring data without persistence
• Chapter 5. Inferring file type and schema
• Chapter 5. Shredding nested JSON
• Chapter 5. Translating CSV to Parquet
• Chapter 5. Analyzing and querying Parquet files
• Chapter 5. Querying SQLite and other databases
• Chapter 5. Working with Excel files
• Chapter 5. Summary
• Chapter 6. Integrating with the Python ecosystem
• Chapter 6. Using the relational API
• Chapter 6. Querying pandas DataFrames
• Chapter 6. User-defined functions
• Chapter 6. Interoperability with Apache Arrow and Polars
• Chapter 6. Summary
• Chapter 7. DuckDB in the cloud with MotherDuck
• Chapter 7. Getting started with MotherDuck
• Chapter 7. Making the best possible use of MotherDuck
• Chapter 7. Summary
• Chapter 8. Building data pipelines with DuckDB
• Chapter 8. Data ingestion with dlt
• Chapter 8. Data transformation and modeling with dbt
• Chapter 8. Orchestrating data pipelines with Dagster
• Chapter 8. Summary
• Chapter 9. Building and deploying data apps
• Chapter 9. Building a BI dashboard with Apache Superset
• Chapter 9. Summary
• Chapter 10. Performance considerations for large datasets
• Chapter 10. Query planning and execution
• Chapter 10. Exporting the Stack Overflow data to Parquet
• Chapter 10. Exploring the New York Taxi dataset from Parquet files
• Chapter 10. Summary
• Chapter 11. Conclusion
• Chapter 11. Upcoming stable versions of DuckDB
• Chapter 11. Aspects we did not cover
• Chapter 11. Where can you learn more?
• Chapter 11. What is the future of data engineering with DuckDB?
• appendix A. Client APIs for DuckDB
• appendix A. A word on concurrency
• appendix A. Use cases
• appendix A. Importing large amounts of data
• appendix A. Using DuckDB from Java via the JDBC Driver
• appendix A. Additional connection options
• appendix A. Summary

Pictures of DuckDB in Action Video Edition course

Sample video of the course

download link

Download part 1 – 1 GB

Download part 2 – 24 MB

File(s) password: www.downloadly.ir

File size

1.02 GB