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In-Memory Analytics with Apache Arrow. Perform fast and efficient data analytics on both flat and hierarchical structured data

(ebook) (audiobook) (audiobook) Książka w języku 1
In-Memory Analytics with Apache Arrow. Perform fast and efficient data analytics on both flat and hierarchical structured data Matthew Topol, Wes McKinney - okladka książki

In-Memory Analytics with Apache Arrow. Perform fast and efficient data analytics on both flat and hierarchical structured data Matthew Topol, Wes McKinney - okladka książki

In-Memory Analytics with Apache Arrow. Perform fast and efficient data analytics on both flat and hierarchical structured data Matthew Topol, Wes McKinney - audiobook MP3

In-Memory Analytics with Apache Arrow. Perform fast and efficient data analytics on both flat and hierarchical structured data Matthew Topol, Wes McKinney - audiobook CD

Serie wydawnicze:
Learning
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
392
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Apache Arrow is designed to accelerate analytics and allow the exchange of data across big data systems easily.
In-Memory Analytics with Apache Arrow begins with a quick overview of the Apache Arrow format, before moving on to helping you to understand Arrow’s versatility and benefits as you walk through a variety of real-world use cases. You'll cover key tasks such as enhancing data science workflows with Arrow, using Arrow and Apache Parquet with Apache Spark and Jupyter for better performance and hassle-free data translation, as well as working with Perspective, an open source interactive graphical and tabular analysis tool for browsers. As you advance, you'll explore the different data interchange and storage formats and become well-versed with the relationships between Arrow, Parquet, Feather, Protobuf, Flatbuffers, JSON, and CSV. In addition to understanding the basic structure of the Arrow Flight and Flight SQL protocols, you'll learn about Dremio’s usage of Apache Arrow to enhance SQL analytics and discover how Arrow can be used in web-based browser apps. Finally, you'll get to grips with the upcoming features of Arrow to help you stay ahead of the curve.
By the end of this book, you will have all the building blocks to create useful, efficient, and powerful analytical services and utilities with Apache Arrow.

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O autorach książki

Matthew Topol is an Apache Arrow contributor and a principal software architect at FactSet Research Systems, Inc. Since joining FactSet in 2009, Matt has worked in both infrastructure and application development, led development teams, and architected large-scale distributed systems for processing analytics on financial data. In his spare time, Matt likes to bash his head against a keyboard, develop and run delightfully demented games of fantasy for his victims—er—friends, and share his knowledge with anyone interested enough to listen.

Wes McKinney ― twórca oprogramowania open source, autor projektu pandas i współtwórca Apache Arrow. Członek The Apache Software Foundation, a także PMC Apache Parquet. Obecnie pełni funkcję dyrektora technicznego Voltron Data, gdzie zajmuje się przyspieszonymi technologiami obliczeniowymi opartymi na Apache Arrow.

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