In-Memory Analytics with Apache Arrow, 2nd Edition

eBook Details:

• Paperback: 406 pages
• Publisher: WOW! eBook; 2nd edition (September 30, 2024)
• Language: English
• ISBN-10: 1835461220
• ISBN-13: 978-1835461228

eBook Description:

In-Memory Analytics with Apache Arrow, 2nd Edition: Accelerate data analytics for efficient processing of flat and hierarchical data structures. Harness the power of Apache Arrow to optimize tabular data processing and develop robust, high-performance data systems with its standardized, language-independent columnar memory format.

Apache Arrow is an open source, columnar in-memory data format designed for efficient data processing and analytics. This In-Memory Analytics with Apache Arrow, 2nd Edition book harnesses the author’s 15 years of experience to show you a standardized way to work with tabular data across various programming languages and environments, enabling high-performance data processing and exchange.

This updated In-Memory Analytics with Apache Arrow, Second Edition gives you an overview of the Arrow format, highlighting its versatility and benefits through real-world use cases. It guides you through enhancing data science workflows, optimizing performance with Apache Parquet and Spark, and ensuring seamless data translation. You’ll explore data interchange and storage formats, and Arrow’s relationships with Parquet, Protocol Buffers, FlatBuffers, JSON, and CSV. You’ll also discover Apache Arrow subprojects, including Flight, SQL, Database Connectivity, and nanoarrow. You’ll learn to streamline machine learning workflows, use Arrow Dataset APIs, and integrate with popular analytical data systems such as Snowflake, Dremio, and DuckDB. The latter chapters provide real-world examples and case studies of products powered by Apache Arrow, providing practical insights into its applications.

• Use Apache Arrow libraries to access data files, both locally and in the cloud
• Understand the zero-copy elements of the Apache Arrow format
• Improve the read performance of data pipelines by memory-mapping Arrow files
• Produce and consume Apache Arrow data efficiently by sharing memory with the C API
• Leverage the Arrow compute engine, Acero, to perform complex operations
• Create Arrow Flight servers and clients for transferring data quickly
• Build the Arrow libraries locally and contribute to the community

By the end of this In-Memory Analytics with Apache Arrow, 2nd Edition book, you’ll have all the building blocks to create efficient and powerful analytical services and utilities with Apache Arrow.