We are currently planning for a Q2 2016 release of the product. In the meantime, we are working with a few early adopters on finalizing the initial feature set. If you have additional questions about HDF5/ODBC, or if you would like to become an early adopter, please contact us
Joel Plutchak, The HDF Group The HDF Group’s support for and use of the Java Programming Language consists of Java wrappers for the HDF4 and HDF5 C libraries, an Object Model definition and implementation, and HDFView, a graphical file viewing application. In this article we’ll discuss what we’re doing now with Java, and look toward
The current improvement of using collective I/O to reduce the number of independent processes accessing the file system helped to improve the metadata reads for cgp_open substantially, yielding 100-1000 times faster execution times over the previous implementation.
* With Python’s Help Gerd Heber, The HDF Group Before the recent release of our PyHexad Excel add-in for HDF5[1], the title might have sounded like the slogan of a global coffee and baked goods chain. That was then. Today, it is an expression of hope for the spreadsheet users who run this country and
Elena Pourmal and Quincey Koziol – The HDF Group UPDATE: Check our support pages for the newest version of HDF5-1.10.0. Concurrent Access to an HDF5 File: Single Writer / Multiple Reader (SWMR) Virtual Dataset (VDS) Scalable Chunk Indexing Persistent Free Filespace Tracking Collective Metadata I/O Integration of Java HDF5 JNI into HDF5 Many changes have
HDF Group has just announced “HDF Server” – a freely available service that enables remote access to HDF5 content using a RESTful API. In our scenario, using HDF Server, we upload our Monopoly simulation results to the server and then interested parties can make requests for any desired content to the server – no file size issues, no downloading entire files…
