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In-Memory Analytics with Apache Arrow

You're reading from   In-Memory Analytics with Apache Arrow Perform fast and efficient data analytics on both flat and hierarchical structured data

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801071031
Length 392 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Matthew Topol Matthew Topol
Author Profile Icon Matthew Topol
Matthew Topol
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Overview of What Arrow Is, its Capabilities, Benefits, and Goals
2. Chapter 1: Getting Started with Apache Arrow FREE CHAPTER 3. Chapter 2: Working with Key Arrow Specifications 4. Chapter 3: Data Science with Apache Arrow 5. Section 2: Interoperability with Arrow: pandas, Parquet, Flight, and Datasets
6. Chapter 4: Format and Memory Handling 7. Chapter 5: Crossing the Language Barrier with the Arrow C Data API 8. Chapter 6: Leveraging the Arrow Compute APIs 9. Chapter 7: Using the Arrow Datasets API 10. Chapter 8: Exploring Apache Arrow Flight RPC 11. Section 3: Real-World Examples, Use Cases, and Future Development
12. Chapter 9: Powered by Apache Arrow 13. Chapter 10: How to Leave Your Mark on Arrow 14. Chapter 11: Future Development and Plans 15. Other Books You May Enjoy

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "When we call ListFlights, it returns a stream that we can then use to retrieve each one of our FlightInfo objects."

A block of code is set as follows:

...
    // add these imports
    "fmt"
    "github.com/apache/arrow/go/v8/arrow/arrio" 
...

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

...
flights = list(client.list_flights(b'2009'))
data = client.do_get(flights[0].endpoints[0].ticket)
print(data.read_all())

Any command-line input or output is written as follows:

$ pip install pyodbc

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "After clicking the button, you'll have a window pop open; click the Save button in the bottom-right corner."

Tips or Important Notes

Appear like this.

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