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Upgrade HDF5 c library ffm to 1.12.1. #138

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Merged
JohnLCaron merged 2 commits into from
May 27, 2025
Merged

Upgrade HDF5 c library ffm to 1.12.1. #138

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1f5b0e3
Upgrade HDF5 c library ffm to 1.12.1.
JohnLCaron May 27, 2025
1f14dd8
tweak readme.
JohnLCaron May 27, 2025
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16 changes: 7 additions & 9 deletions Readme.md
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# netchdf
_last updated: 5/24/2025_
_last updated: 5/26/2025_

This is a rewrite in Kotlin of parts of the devcdm and netcdf-java libraries.

Expand All @@ -12,7 +12,7 @@ Please contact me if you'd like to help out. Especially needed are test datasets

* Download Java 21 JDK and set JAVA_HOME.
* Download git and add to PATH.
*

````
cd <your_build_dir>
git clone https://github.com/JohnLCaron/netchdf.git
Expand Down Expand Up @@ -66,12 +66,10 @@ conversions, and arguably its impossible to process HDF-EOS without them. So the
library for data access is less clear. For now, we will provide a "best-effort" to expose the internal
contents of the file.

Currently, the Netcdf-4 and HDF4 libraries are not thread safe, even when operating on different files.
The HDF5 library can be built with MPI-IO for parallel file systems. The serial HDF5 library is apparently thread safe
but does not support concurrent reading. These are serious limitations for high performance, scalable applications.

Our library tries to ameliorate these problems for scientists and the interested public to access the data without
having to become specialists in the file formats and legacy APIs.
Currently, the Netcdf-4 and HDF4 libraries are apparently not thread safe, although the details are complex.
See [Toward Multi-Threaded Concurrency in HDF5](https://www.hdfgroup.org/wp-content/uploads/2022/05/Toward-MT-HDF5.pdf),
and [RFC:Multi-Thread HDF5](https://support.hdfgroup.org/releases/hdf5/documentation/rfc/RFC_multi_thread.pdf)
for more information.

### Why Kotlin?

Expand Down Expand Up @@ -200,7 +198,7 @@ local to the variable they are referenced by.

#### Compare with HDF5 data model
* Creation order is ignored
* We dont include symbolic links in a group, as these point to an existing dataset (variable)
* We dont include soft (aka symbolic) links in a group, as these point to an existing dataset (variable).
* Opaque: hdf5 makes arrays of Opaque all the same size, which gives up some of its usefulness. If there's a need,
we will allow Opaque(*) indicating that the sizes can vary.
* Attributes can be of type REFERENCE, with value the full path name of the referenced dataset.
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