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HDF5 Last Updated on 2025-04-29
The HDF5 Field Guide
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Navigate back: Main / Getting Started with HDF5 / Learning the Basics
An extendible dataset is one whose dimensions can grow. HDF5 allows you to define a dataset to have certain initial dimensions, then to later increase the size of any of the initial dimensions.
HDF5 requires you to use chunking to define extendible datasets. This makes it possible to extend datasets efficiently without having to excessively reorganize storage. (To use chunking efficiently, be sure to see the advanced topic, Chunking in HDF5.)
The following operations are required in order to extend a dataset:
See Examples from Learning the Basics for the examples used in the Learning the Basics tutorial.
The example shows how to create a 3 x 3 extendible dataset, write to that dataset, extend the dataset to 10x3, and write to the dataset again.
For details on compiling an HDF5 application: [ Compiling HDF5 Applications ]
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Navigate back: Main / Getting Started with HDF5 / Learning the Basics