Getting Started

The following articles demonstrate installation, use, and a basic understanding of Arrow. These articles will get you setup quickly using Arrow and give you a taste of what the library is capable of. Specifically, it contains: an installation and linking guide; documentation of conventions used in the codebase and suggested for users; and tutorials, including:

• Building Arrow arrays and tabular structures

• Reading and writing Parquet, Arrow, and CSV files

• Executing compute kernels on arrays

• Reading and writing multi-file partitioned datasets

Start here to gain a basic understanding of Arrow, and move on to the User Guide to explore more specific topics and underlying concepts, or the API Reference to explore Arrow’s API.

• Using Arrow C++ in your own project
  • CMake
    • Basic usage
    • Available variables and targets
    • Other available packages
  • pkg-config
    • Basic usage
    • Available packages
  • A Note on Linking
  • Runtime Dependencies
• Conventions
  • Language version
  • Namespacing
  • Safe pointers
  • Immutability
  • Error reporting
• Basic Arrow Data Structures
  • Pre-requisites
  • Setup
    • Includes
    • Main()
  • Making an Arrow Array
    • Building int8 Arrays
    • Building int16 Arrays
  • Making a RecordBatch
    • Defining a Schema
    • Building a RecordBatch
  • Making a ChunkedArray
  • Making a Table
  • Ending Program
  • Wrapping Up
• Arrow File I/O
  • Pre-requisites
  • Setup
    • Includes
    • Main()
    • Generating Files for Reading
  • I/O with Arrow Files
    • Opening a File
    • Opening an Arrow file Reader
    • Reading an Open Arrow File to RecordBatch
    • Prepare a FileOutputStream
    • Write Arrow File from RecordBatch
  • I/O with CSV
    • Opening a CSV File
    • Preparing a Table
    • Read a CSV File to Table
    • Write a CSV File from Table
  • File I/O with Parquet
    • Opening a Parquet File
    • Setting up a Parquet Reader
    • Reading a Parquet File to Table
    • Writing a Parquet File from Table
  • Ending Program
• Arrow Compute
  • Pre-requisites
  • Setup
    • Includes
    • Main()
    • Generating Tables for Computation
  • Calculating a Sum over an Array
    • Prepare Memory for Output with Datum
    • Call Sum()
    • Get Results from Datum
  • Calculating Element-Wise Array Addition with CallFunction()
    • Prepare Memory for Output with Datum
    • Use CallFunction() with “add”
    • Get Results from Datum
  • Searching for a Value with CallFunction() and Options
    • Prepare Memory for Output with Datum
    • Configure “index” with IndexOptions
    • Use CallFunction() with “index” and IndexOptions
    • Get Results from Datum
  • Ending Program
• Arrow Datasets
  • Pre-requisites
  • Setup
    • Includes
    • Main()
    • Generating Files for Reading
  • Reading a Partitioned Dataset
    • Preparing a FileSystem Object
    • Creating a FileSystemDatasetFactory
    • Build Dataset using Factory
    • Move Dataset into Table
  • Writing a Dataset to Disk from Table
    • Prepare Data from Table for Writing
    • Create Scanner for Moving Table Data
    • Prepare Schema, Partitioning, and File Format Variables
    • Configure FileSystemDatasetWriteOptions
    • Write Dataset to Disk
  • Ending Program

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C++ Implementation

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Using Arrow C++ in your own project