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Item #:
248784311
DuckDB in Action
Item #:
248784311
USD 84
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DuckDB makes data analytics fast and fun! You don't need to set up a Spark or run a cloud data warehouse just to process a few hundred gigabytes of data.
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- Dive into DuckDB and start processing gigabytes of data with ease―all with no data warehouse. DuckDB is a cutting-edge SQL database that makes it incredibly easy to analyze big data sets right from your laptop. In DuckDB in Action you'll learn everything you need to know to get the most out of this awesome tool, keep your data secure on prem, and save you hundreds on your cloud bill. From data ingestion to advanced data pipelines, you'll learn everything you need to get the most out of DuckDB―all through hands-on examples. Open up DuckDB in Action and learn how to: Read and process data from CSV, JSON and Parquet sources both locally and remoteWrite analytical SQL queries, including aggregations, common table expressions, window functions, special types of joins, and pivot tablesUse DuckDB from Python, both with SQL and its Relational-API, interacting with databases but also data framesPrepare, ingest and query large datasetsBuild cloud data pipelinesExtend DuckDB with custom functionality Pragmatic and comprehensive, DuckDB in Action introduces the DuckDB database and shows you how to use it to solve common data workflow problems. You won't need to read through pages of documentation―you'll learn as you work. Get to grips with DuckDB's unique SQL dialect, learning to seamlessly load, prepare, and analyze data using SQL queries. Extend DuckDB with both Python and built-in tools such as MotherDuck, and gain practical insights into building robust and automated data pipelines. About the technology DuckDB makes data analytics fast and fun! You don't need to set up a Spark or run a cloud data warehouse just to process a few hundred gigabytes of data. DuckDB is easily embeddable in any data analytics application, runs on a laptop, and processes data from almost any source, including JSON, CSV, Parquet, SQLite and Postgres.
| Publisher | Manning Publications |
| Publication date | 26 Aug. 2024 |
| Edition | 1st |
| Language | English |
| Print length | 312 pages |
| ISBN-10 | 1633437256 |
| ISBN-13 | 978-1633437258 |
| Item weight | 544 g |
| Dimensions | 18.73 x 1.78 x 23.5 cm |
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Customer Questions & Answers
-
Question:
What data formats can I work with in DuckDB?
Answer: You can work with CSV, JSON, Parquet, SQLite, and Postgres formats. -
Question:
Is DuckDB suitable for cloud data processing?
Answer: Yes, it allows cloud data pipeline creation while saving costs compared to traditional warehouses. -
Question:
Do I need prior SQL knowledge to use DuckDB?
Answer: No, the book provides comprehensive learning starting from fundamentals to advanced queries.
Data Mining Editorial Review
DuckDB In Action, published by Manning Publications, is set to be an essential read for data enthusiasts when it releases on August 26, 2024. This 1st edition book spans 312 pages and offers insights into the DuckDB database system, catering to a variety of readers looking to enhance their data analysis skills. The authors delve into practical examples and applications, making it highly accessible for those working with data in real-world scenarios. With an ISBN-10 of 1633437256, this comprehensive guide aims to instruct and inspire users to leverage DuckDB effectively in their projects.
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Pros
- Comprehensive guide to DuckDB for data analysis
- Practical examples make learning accessible
- Well-structured for both beginners and experts
- Advises on real-world data applications
- Latest insights on database technology
Cons
- No prior knowledge required, making it beginner-friendly
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USD 84
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Features & Benefits
- Learn to analyze big data sets easily from your laptop with DuckDB.
- Master advanced SQL queries and data pipeline creation through hands-on examples.
- Save on cloud costs and keep your data secure with on-prem solutions.
- Work with various data formats like CSV, JSON, and Parquet effortlessly.
- Enhance DuckDB functionality with Python integration and built-in tools.
- Pragmatic approach: learn as you work without extensive documentation.
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