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Inmemory Analytics With Apache Arrow Perform Fast And Efficient Data Analytics On Both Flat And Hierarchical Structured Data 1st Edition Matthew Topol

  • SKU: BELL-55707068
Inmemory Analytics With Apache Arrow Perform Fast And Efficient Data Analytics On Both Flat And Hierarchical Structured Data 1st Edition Matthew Topol
$ 31.00 $ 45.00 (-31%)

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Inmemory Analytics With Apache Arrow Perform Fast And Efficient Data Analytics On Both Flat And Hierarchical Structured Data 1st Edition Matthew Topol instant download after payment.

Publisher: -.-
File Extension: PDF
File size: 7.55 MB
Pages: 391
Author: Matthew Topol
ISBN: 9781801071031, 1801071039, 1801991039
Language: English
Year: 2022
Edition: 1

Product desciption

Inmemory Analytics With Apache Arrow Perform Fast And Efficient Data Analytics On Both Flat And Hierarchical Structured Data 1st Edition Matthew Topol by Matthew Topol 9781801071031, 1801071039, 1801991039 instant download after payment.

Process tabular data and build high-performance query engines on modern CPUs and GPUs using Apache Arrow, a standardized language-independent memory format, for optimal performance Key Features: Learn about Apache Arrow's data types and interoperability with pandas and Parquet Work with Apache Arrow Flight RPC, Compute, and Dataset APIs to produce and consume tabular data Reviewed, contributed, and supported by Dremio, the co-creator of Apache Arrow Book Description: 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. What You Will Learn: 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 read performance by

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